#Building Information Modeling Software Market product segment

[global-research-report]

Emerging Trends in the No-code AI Platform Market Unveiled

No-code AI Platform Market Growth & Trends

The global no-code AI platform market is projected to witness substantial expansion, with the market size anticipated to reach USD 24.42 billion by 2030, growing at a compound annual growth rate (CAGR) of 30.6% from 2024 to 2030, according to a recent report published by Grand View Research, Inc. This significant growth trajectory reflects the increasing demand for accessible and user-friendly artificial intelligence (AI) development tools.

No-code AI represents a specialized segment within the broader AI ecosystem that seeks to democratize the use and development of AI technologies. These platforms enable users to design and deploy AI and machine learning (ML) models through a visual, code-free, drag-and-drop interface, eliminating the need for traditional programming. A range of tools offer these capabilities—including automation software and purpose-built no-code AI platforms—which integrate AI functionalities into interfaces that can be navigated without technical expertise.

These no-code platforms empower non-technical users—including business analysts, marketers, and other operational professionals—to rapidly analyze and classify data, and to build accurate predictive models with ease. This accessibility allows businesses to utilize AI without requiring teams of highly specialized data scientists.

Across industries, organizations are increasingly motivated to invest in AI/ML technologies to gain a competitive advantage by enhancing customer experiences and boosting workforce productivity. Traditional AI model development typically demands significant time, effort, and expertise, which can pose a barrier for many businesses. In contrast, no-code AI platforms streamline this process, reducing development time from weeks or months to mere minutes, thereby enabling swift deployment and integration of AI solutions into business operations.

A case in point is Writesonic, Inc., which in May 2023 introduced Botsonic, a no-code AI chatbot builder powered by GPT-4 technology. This tool allows businesses to effortlessly add intelligent chat capabilities to their websites, aligning perfectly with no-code integration strategies and requiring minimal setup time.

Creating custom AI solutions traditionally involves a complex and time-consuming series of steps such as data cleaning, organizing, coding, debugging, and model training. For individuals and teams without data science backgrounds, these processes can be daunting. No-code AI platforms overcome these challenges by offering intuitive workflows that allow users to bypass technical intricacies while still creating effective ML models. Additionally, the increasing availability of affordable, high-quality automation tools is expected to fuel further market expansion in the coming years.

No-code AI Platform Market Report Highlights

By Component: The no-code AI platforms segment emerged as the market leader, accounting for the largest revenue share of 76.8% in 2023. These platforms allow individuals with little to no programming background to develop and deploy AI systems. Users can leverage the platform’s capabilities to efficiently analyze datasets, classify information, and create reliable models for predictive analytics.

By Technology: The natural language processing (NLP) segment led the market by technology, capturing a revenue share of 55.6% in 2023. NLP enables machines to interpret and process human language, fostering deeper contextual understanding. Users can employ pre-built NLP engines or develop custom NLP solutions using no-code interfaces to automate text-based tasks and communication workflows.

By Deployment: In terms of deployment, the on-premises segment held the dominant position, representing 0% of the market revenue in 2023. On-premises no-code AI platforms provide organizations with the ability to build, manage, and deploy AI applications within their own infrastructure, ensuring greater control over data and compliance while minimizing dependency on external cloud environments.

By Region: North America led the global market with a revenue share of 39.5% in 2023. The region hosts a strong ecosystem of startups, technology enterprises, and cloud service providers, all of which are actively innovating and offering a wide array of no-code AI platforms tailored for various industries and use cases. This dynamic environment has contributed significantly to the region's leadership position in the global market.

Get a preview of the latest developments in the No-code AI Platform Market? Download your FREE sample PDF copy today and explore key data and trends

No-code AI Platform Market Segmentation

Grand View Research has segmented the global no-code AI platform market report based on component, technology, deployment, enterprise size, vertical, and region:

No-code AI Platform Component Outlook (Revenue, USD Billion, 2017 - 2030)

No-code AI Platforms

Services

No-code AI Platform Technology Outlook (Revenue, USD Billion, 2017 - 2030)

Natural Language Processing

Computer Vision

Predictive Analytics

Others

No-code AI Platform Deployment Outlook (Revenue, USD Billion, 2017 - 2030)

Cloud

On-Premise

No-code AI Platform Enterprise Size Outlook (Revenue, USD Billion, 2017 - 2030)

SMEs

Large Enterprises

No-code AI Platform Vertical Outlook (Revenue, USD Billion, 2017 - 2030)

BFSI

Healthcare

Retail & E-Commerce

IT & Telecom

Energy & Utilities

Government & Public Sector

Others

No-code AI Platform Regional Outlook (Revenue, USD Billion, 2017 - 2030)

North America

US

Canada

Europe

Germany

UK

France

Asia Pacific

China

Japan

India

South Korea

Australia

Latin America

Brazil

Mexico

Middle East & Africa

Kingdom of Saudi Arabia

UAE

South Africa

Key Players in the No-code AI Platform Market

Akkio Inc.

com, Inc.

Apple Inc.

Caspio, Inc.

Clarifai, Inc.

DataRobot, Inc.

Google LLC

Levity AI GmbH

Microsoft

Quickbase, Inc.

Order a free sample PDF of the Market Intelligence Study, published by Grand View Research.

[forbiddenhoardtreasure]

Low Carbon Building Market is driven by green construction policies

The Low Carbon Building Market encompasses the design, construction, and operation of structures that minimize carbon emissions through advanced materials, energy-efficient systems, and sustainable practices. Low carbon buildings employ high-performance insulation, solar photovoltaic panels, LED lighting, and smart HVAC controls to reduce energy consumption, optimize resource usage, and curb greenhouse gas output. These solutions offer long-term cost savings via lower utility bills, enhanced occupant comfort, and increased asset value. Rising concerns over climate change and stringent environmental regulations have amplified the need for buildings that comply with green certification standards such as LEED and BREEAM.

 Developers and property owners are therefore seeking innovative building envelope materials, renewable energy integration, and intelligent building management systems. Market participants leverage cross-laminated timber, recycled steel, and Low Carbon Building Market­­­ to achieve superior structural performance alongside environmental benefits. Technological advancements in IoT-enabled sensors and building automation facilitate real-time monitoring and predictive maintenance, driving operational efficiency. Comprehensive market research and market insights highlight robust growth potential in both residential and commercial segments, with analysts projecting a steady increase in market share for sustainable building solutions.

The low carbon building market is estimated to be valued at USD 733.42 Bn in 2025 and is expected to reach USD 1621.36 Bn by 2032, growing at a compound annual growth rate (CAGR) of 12.00% from 2025 to 2032. Key Takeaways

Key players operating in the Low Carbon Building Market are:

-Siemens AG

-Honeywell International Inc.

-Johnson Controls International plc

-Schneider Electric SE

-Trane Technologies plc

These market leaders have secured strong footholds through strategic collaborations, targeted R&D investments, and product diversification aimed at addressing growing demand for eco-friendly construction. Siemens AG focuses on smart building technologies and integrated energy management platforms, while Honeywell International Inc. leverages its automation expertise to develop high-efficiency safety and HVAC systems. Johnson Controls International plc offers advanced climate control and fire safety products tailored for low-carbon structures, and Schneider Electric SE provides comprehensive building automation solutions. Trane Technologies plc specializes in high-performance HVAC equipment and refrigerants with reduced global warming potential. Together, these market companies drive innovation, expand their global footprint, and capitalize on emerging market opportunities across Asia-Pacific, Europe, and North America using robust market growth strategies. With increasing environmental awareness among consumers, corporations, and regulators, the Low Carbon Building Market is witnessing accelerating demand for sustainable construction solutions. Developers prioritize green building certifications, investing in energy-efficient materials to meet sustainability targets and reduce operational expenditures. The push for net-zero emissions by major urban centers and adoption of green mortgage incentives further fuel market growth. Demand for advanced building information modeling (BIM), energy simulation tools, and life cycle assessment software is on the rise, enabling stakeholders to optimize design, construction, and maintenance processes. This surge is driven by key market trends such as digitalization, the circular economy, and decarbonization strategies. Moreover, public–private partnerships are unlocking new market opportunities, fostering innovation in renewable energy integration, and addressing market challenges related to high upfront costs and supply chain complexity.

‣ Get More Insights On: Low Carbon Building Market­­­

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‣ Read More Related Articles- Carbon Strips: The Future of Electricity Storage

[neuentdecken]

Effective Digital Branding Through Storytelling

In today's interconnected earth, electronic advertising has surfaced as a transformative force reshaping the way in which organizations promote their services and products, talk making use of their readers, and build their company identity. With consumers increasingly turning to on the web systems for data, amusement, and searching, digital marketing offers unmatched possibilities for organizations to reach global audiences, target messages with detail, and analyze performance in true time. The change from standard advertising to digital techniques reflects a broader change in customer conduct and technical improvement, rendering it required for organizations of shapes to purchase digital channels.

One of the very most outstanding areas of digital advertising is its power to modify material for different segments of the prospective audience. Through methods such as e-mail marketing, social networking advertising, and behavioral monitoring, companies may supply tailored material that resonates with personal tastes, thus enhancing wedding and conversion rates. That amount of customization not just improves an individual knowledge but in addition strengthens customer associations and model loyalty. More over, automation methods let marketers to routine campaigns, monitor answers, and alter techniques in real-time, raising efficiency and return on investment.

Se optimization (SEO) represents a essential role in ppc by increasing a website's presence on research motors like Google. By optimizing quite happy with appropriate keywords, producing high-quality backlinks, and ensuring a mobile-friendly software, companies can rise the se rankings and entice normal traffic. In similar, pay-per-click (PPC) promotion offers immediate effects by placing targeted advertisements facing potential clients who are actively looking for connected services and products or services. The mix of natural and paid search strategies produces a powerful synergy that increases on the web visibility and manufacturer recognition.

Social networking tools such as for example Facebook, Instagram, LinkedIn, and TikTok have become crucial aspects of electronic marketing. These channels provide an area for firms to talk about content, connect to users, and foster community building. Innovative content such as for instance videos, infographics, and stay revenues may produce viral traction, improve brand consciousness, and get traffic to sites or e-commerce platforms. Influencer collaborations and user-generated content campaigns also add a human touch to model conversation, making it more relatable and trustworthy in the eyes of the consumer.

Mail marketing, nevertheless one of many oldest kinds of electronic transmission, remains extremely effective when performed strategically. Newsletters, solution announcements, and individualized offers delivered via e-mail keep direct lines of communication with consumers and prospects. Combined with analytics instruments that measure start prices, click-throughs, and conversions, email advertising becomes a powerful asset in nurturing brings and increasing repeat sales.

Analytics and information interpretation would be the backbone of digital advertising success. Systems like Bing Analytics, Meta Company Suite, and CRM methods provide in-depth insights in to consumer behavior, plan performance, and ROI. Marketers may power that data to improve their methods, spend budgets more effectively, and make educated choices that align with organization goals. The energy to calculate just about any facet of a strategy makes digital marketing an energetic and results-oriented discipline.

Finally, digital marketing is not really a one-size-fits-all solution but a continually developing ecosystem. Companies that embrace advancement, remain updated with developments, and adjust to new systems are most useful situated to succeed in this aggressive landscape. Whether through content development, influencer outreach, data analytics, or automation, the main element is based on creating a electronic technique that offers value, builds trust, and drives maintained development in the digital economy.

Influence Digital Agency 2517 Raeford Rd, Suite C, Fayetteville, NC 28305, United States (910) 900-4848 https://maps.app.goo.gl/dosvHQThrZg7CauN9

[bisresearch0]

Latin America NGS Market - Analysis and Forecast, 2024-2034 | BIS Research

Next-generation sequencing (NGS) is transforming healthcare by enabling comprehensive genomic analysis for personalized medicine. NGS facilitates the use of targeted medicines, accurate tumor profiling, and the discovery of actionable mutations in oncology. Through the use of circulating tumor DNA, it enables non-invasive cancer surveillance in liquid biopsies. Rapid pathogen identification and non-invasive prenatal diagnostics also depend on NGS. The use of NGS is accelerating in Latin America due to the increased rates of genetic diseases and cancer. With the help of public-private partnerships, nations like Brazil and Mexico are making investments in precision medicine and genomic testing. The Latin American NGS industry is expected to grow significantly as clinical laboratories use NGS into diagnosis and research collaborations increase.

In 2024, The Latin America NGS Market was valued at $268.04 million. It is projected to grow at a compound annual growth rate (CAGR) of 8.34%, reaching $597.20 million by 2034.

What are the emerging trends in the Latin America NGS market?

Growing Adoption of Personalized Medicine: The Latin America NGS market is growing rapidly due to its expanding role in oncology and infectious disease research, driven by the rising demand for precision medicine and its critical applications in cancer mutation detection and virological studies such as COVID-19 and HBV.

Increasing Local Production and Infrastructure: Countries in Latin America are investing in local NGS infrastructure by establishing genomics centers and bioinformatics training programs, such as the CABANA model in Mexico, to reduce reliance on international services and enhance regional genomic research capabilities.

Expansion of Genomic Data Accessibility: Efforts to increase the accessibility of genomic data are growing, with partnerships such as Lifebit, Omica.bio, and gen-t in Brazil and Mexico enhancing local data representation in global datasets to support more inclusive and accurate population health research.

Market Segmentation

By Offering

Instruments

Kits and Consumables

Software

Services

By Technology

Ion Torrent Semiconductor Sequencing

Reversible Terminator Sequencing (SBS)

Single Molecule Real-Time Sequencing

Nanopore Sequencing Technologies

By Application

Clinical

Translational Research

By End User

Hospitals and Clinics

Academic and Research Institutes

Pharmaceutical and Biotechnology Companies

Government Labs

What are the main challenges or barriers to NGS adoption in Latin America?

Cost-Effectiveness: The high expense of next-generation sequencing (NGS) testing continues to prevent its broad use in the region, which in turn prevents the Latin America NGS market from expanding, especially in countries with much lower average incomes like Brazil, Mexico, and Argentina. Notwithstanding worldwide cost decreases, issues with affordability still prevent NGS from being fully incorporated into regional healthcare systems.

Lack of Funding and Reimbursement:The region's public healthcare systems lack the funds necessary to build the necessary infrastructure for genetic testing, which forces reliance on expensive private labs and impedes the expansion of the Latin American NGS industry. NGS uptake and sustainability in the region are further limited by the high cost of clinical exome sequencing and low reimbursement rates, especially in the public sector.

Lack of Education, Awareness, and Specialists: One of the main obstacles to the wider adoption of genomic technologies in Brazil is the lack of knowledge among patients and healthcare professionals about these technologies, including whole genome and exome sequencing, as well as a lack of medical education and specialized professionals. The efficient use of these technologies is hampered by this knowledge gap, unclear guidelines, and restricted access to experts.

Get Informed: Explore the Influence of Increasing Investments in The Latin America NGS Market Market – Access Our Sample Report!

Learn more about Healthcare Vertical. Click Here!

Conclusion

The Latin America NGS market is poised for significant growth, driven by increasing demand for personalized medicine, advancements in genomic infrastructure, and expanding research collaborations. Opportunities in fields including growing genetic data, setting up diagnostic centers, and incorporating NGS into healthcare systems present a bright future despite obstacles like exorbitant costs, a lack of funding, and a shortage of skilled workers. The Latin American NGS market is anticipated to play a significant role in the advancement of global healthcare as local genomic capabilities increase and accessibility improves.

[aimarketresearch]

Molecular Modelling Market Size, Share, Trends, Industry Growth and Competitive Outlook

Global Molecular Modelling Market - Size, Share, Demand, Industry Trends and Opportunities

Global Molecular Modelling Market, By Product (Software, Services), Approach (Molecular Mechanics Approach, Quantum Chemistry Approach), Application (Drug Development, Drug Discovery, Others), End-User (Pharmaceutical and Biotechnology Companies, Research Centers and Academic Institutions, Others) - Industry Trends.

Access Full 350 Pages PDF Report @

**Segments**

- **By Product**: Software (Molecular Dynamics, Small Molecule Modelling, QSAR, Homology Modelling, Visualization and Analytical Tools) and Services (Model Building, and Model Assessment). - **By Application**: Drug Development, Drug Discovery, Materials Science, and Others. - **By End-User**: Pharmaceutical and Biotechnology Companies, Research Centers, and Others.

The global molecular modeling market is segmented based on products, applications, and end-users. In terms of products, the market is categorized into software and services. Software includes molecular dynamics, small molecule modeling, quantitative structure-activity relationship (QSAR), homology modeling, visualization, and analytical tools. Services consist of model building and model assessment. When it comes to applications, molecular modeling finds its usage predominantly in drug development and drug discovery, but it also extends to materials science and various other fields. Lastly, the end-users of molecular modeling are primarily pharmaceutical and biotechnology companies, research centers, and others who rely on this technology for advancing their scientific endeavors.

**Market Players**

- Dassault Systèmes - Schrödinger, LLC - Simulations Plus - Certara - OpenEye Scientific Software - BIOVIA (Dassault Systèmes) - Chemical Computing Group - Collaborative Drug Discovery - Nanosyn - Genedata AG - Forge - SilcsBio

The global molecular modeling market boasts a robust ecosystem of market players catering to the diverse needs of customers across industries. Key market players include Dassault Systèmes, Schrödinger, LLC, Simulations Plus, Certara, OpenEye Scientific Software, and BIOVIA, a subsidiary of Dassault Systèmes. Other notable participants in the market are Chemical Computing Group, Collaborative Drug Discovery, Nanosyn, Genedata AG, Forge, and SilcsBio. These companies offer a wide range of products and services inThe global molecular modeling market is experiencing significant growth driven by the increasing demand for efficient and cost-effective drug development solutions, alongside the rising adoption of advanced technologies in pharmaceutical and biotechnology industries. The market players are continuously innovating to stay ahead in the competitive landscape, offering a wide array of products and services to cater to the varying needs of their clientele. Dassault Systèmes, a prominent player in the market, provides cutting-edge software solutions such as BIOVIA Materials Studio and BIOVIA Pipeline Pilot, which are widely used in drug discovery and materials science applications. Schrödinger, LLC, known for its advanced molecular simulation software, offers tools like Schrödinger Suite and LiveDesign for accurate molecular modeling and simulation.

Simulations Plus is another key player in the molecular modeling market, specializing in software solutions for pharmaceutical research and development. The company's products, such as GastroPlus and DDDPlus, are utilized in drug development processes to predict drug behavior and optimize formulation strategies. Certara, a leading provider of model-informed drug development and regulatory science solutions, offers software like Phoenix and Simcyp for pharmacokinetic modeling and simulation. OpenEye Scientific Software is renowned for its molecular modeling toolkits, including OEChem and OEDocking, enabling researchers to perform virtual screening and lead optimization effectively.

In addition, companies like Chemical Computing Group, Collaborative Drug Discovery, Nanosyn, Genedata AG, Forge, and SilcsBio are also making significant contributions to the molecular modeling market. Chemical Computing Group's MOE (Molecular Operating Environment) software is widely used for drug design and lead optimization processes. Collaborative Drug Discovery offers an integrated platform for collaborative drug discovery research, facilitating efficient data sharing and analysis among researchers. Nanosyn specializes in medicinal chemistry services, providing support for lead generation and optimization in drug discovery projects. Genedata AG focuses on software solutions for omics data analysis and high-throughput screening in pharmaceutical research.

Forge,**Segments**

Global Molecular Modelling Market, By Product (Software, Services), Approach (Molecular Mechanics Approach, Quantum Chemistry Approach), Application (Drug Development, Drug Discovery, Others), End-User (Pharmaceutical and Biotechnology Companies, Research Centers and Academic Institutions, Others) - Industry Trends and Forecast to 2030.

The global molecular modeling market is witnessing significant growth and evolution, driven by the increasing demand for advanced solutions in drug development, materials science, and other scientific applications. With a focus on products, the market is segmented into software and services, offering a range of tools for molecular dynamics, small molecule modeling, QSAR, homology modeling, visualization, and analytical needs. The diverse applications of molecular modeling span from drug development to materials science, indicating a broad spectrum of utility across industries. The end-users primarily include pharmaceutical and biotechnology companies, research centers, and academia, showcasing the widespread adoption of molecular modeling technology.

**Market Players**

The market for molecular modeling is characterized by a dynamic landscape of key players, each contributing their expertise and unique offerings to cater to the diverse requirements of customers. Leading companies such as Dassault Systèmes, Schrödinger, LLC, Simulations Plus, Certara, and OpenEye Scientific Software are at the forefront of providing innovative software solutions for molecular modeling and simulation. These market players are continuously pushing boundaries in technology to enhance drug discovery processes and accelerate scientific advancements in various fields.

Dassault Systèmes, through

TABLE OF CONTENTS

Part 01: Executive Summary

Part 02: Scope of the Report

Part 03: Research Methodology

Part 04: Market Landscape

Part 05: Pipeline Analysis

Part 06: Market Sizing

Part 07: Five Forces Analysis

Part 08: Market Segmentation

Part 09: Customer Landscape

Part 10: Regional Landscape

Part 11: Decision Framework

Part 12: Drivers and Challenges

Part 13: Market Trends

Part 14: Vendor Landscape

Part 15: Vendor Analysis

Part 16: Appendix

Core Objective of Molecular Modelling Market:

Every firm in the Molecular Modelling Market has objectives but this market research report focus on the crucial objectives, so you can analysis about competition, future market, new products, and informative data that can raise your sales volume exponentially.

Size of the Molecular Modelling Market and growth rate factors.

Important changes in the future Molecular Modelling Market.

Top worldwide competitors of the Market.

Scope and product outlook of Molecular Modelling Market.

Developing regions with potential growth in the future.

Tough Challenges and risk faced in Market.

Global Molecular Modelling top manufacturers profile and sales statistics.

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[aceworkforcevirtualstaffing]

Virtual Sales in 2025: Strategies for Success

The sales landscape has evolved enormously with virtual sales as a key building block of business models these days. Companies that ride the virtual sales wave in 2025 stand a better chance of beating the competition by using technology, information, and human touch in unconventional ways. This article analyzes the trends, technologies, and techniques that are influencing virtual sales this year and how businesses should stay a step ahead..

The Rise of Virtual Sales

Virtual sales that used to be a specialized method have gained mainstream popularity with the improvement in digital communications and changing consumer attitudes. More than 70% of the buyers in the B2B market prefer virtual interactions because of their convenience and ease of access. Virtual sales' flexibility enables businesses to access global markets and lower costs as well as change disposition as needs change.

Key drivers of virtual sales in 2025 include:

AI-Powered Tools: AI-driven CRM systems and chatbots streamline lead generation and customer follow-ups.

Immersive technologies such as virtual reality (VR) and augmented reality (AR) enrich product demonstrations with interactive experiences.

Hybrid work models: Remote sales teams work using cloud-based platforms for coordination..

Top Strategies for Virtual Sales Success

To thrive in 2025, businesses must adopt a strategic approach to virtual sales. Here are actionable strategies to maximize impact:

1. Utilize Machine Learning and Automation

Sales teams can leverage predictive analytics and automated email workflows such as sales automation tools to give high-value leads priority. Companies like Salesforce and HubSpot integrate AI into their platforms these days to offer real-time customer insight into behavior. Automation releases the time of sales representatives to enable them to engage in relationship building, which is an important element in closing a sale.

Tip: Leverage AI to personalize pitches based on customer information and boost conversion by 30%.

2. Master Video-Based Selling

Video calls continue to be a virtual salesmainstay, but a webcam is not all you need. Spend money on good audio-visual equipment and develop virtual presentation skills with your teams. Zoom, Microsoft Teams, and Loom software facilitate lively presentations, and interactive tools such as polling and whiteboard ensure that prospects stay engaged.

Pro-Tip: Record the sales calls for training and fine-tuning the message based on how the customer responds.

3. Adopt Immersive Technologies

Virtual reality and augmented reality are transforming product demonstrations. Real estate companies provide virtual property tours using VR, for instance, while industrial equipment manufacturers show off machinery using AR overlays. These technologies deliver memorable experiences and differentiate businesses in competitive markets.

Case Study: A 2024 study revealed that businesses that implement AR for sales demos observed a 25% boost in customer engagement when compared to other techniques.

4. Emphasize Personal

Customers want personalized experiences. Based on CRM system data, tailor pitches specifically for each individual's exact pain points and objectives. Personalized email, context-driven content, and AI-powered dynamic web experiences greatly enhance the level of engagement.

Pro Tip: Segment your audience by behavior and preference in order to provide hyper-relevant content.

5. Trust Building through Transparency

In a digital world, trustworthiness is everything. Be open with clients regarding costs, product functionality, and timelines. Invite clients to publish client feedback and assessments to gain credibility. Trustpilot and G2 enable companies to post genuine user feedback and give prospects peace of mind.

6. Optimize for Mobile

With over 50% of B2B buyers researching on mobile devices, sales teams must ensure seamless mobile experiences. Responsive websites, mobile-friendly presentations, and SMS-based follow-ups are critical to capturing on-the-go decision-makers

Tools Shaping Virtual Sales in 2025

The right technology stack can make or break a virtual sales strategy. Here are some must-have tools for 2025:

CRM Platforms: Salesforce, Zoho CRM, and Pipedrive for lead management and analytics.

Video Conferencing: Zoom, Webex, and Google Meet for reliable virtual meetings.

Sales Enablement: Gong and Highspot for training and content management.

AR/VR Tools: Unity and Zappar for immersive product demos.

Collaboration Tools: Slack and Asana for team coordination.

Challenges and How to Overcome Them

While virtual sales offer immense opportunities, challenges persist:

Tech Fatigue: Combat Zoom fatigue by keeping meetings concise and engaging.

Data Privacy: Adhere to regulations like GDPR and CCPA to protect customer data.

Skill Gaps: Invest in ongoing training to keep teams updated on tools and techniques.

The Future of Virtual Sales

Looking forward, virtual selling will continue to transform with the innovation of AI, 5G, and the metaverse. Companies that remain nimble, embrace technology investment, and maintain a customer-first mindset will reign the marketplace. Combining human acumen with advanced tech tools enables virtual selling teams to form more substantial connections and facilitate unprecedented growth.

Ready to take your 2025 virtual sales up a notch? Join forces with Ace Workforce Virtual Staffing and unlock the best talent and customized solutions that support your sales initiative. Contact Ace Workforce Virtual Staffing for more information.

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[laptop-dubai]

Powering Productivity in the Emirates: A Deep Dive into Laptop Distribution in Dubai

In a city that thrives on innovation and rapid technological advancement, the demand for high-performance computing solutions is higher than ever. Dubai's tech-forward businesses, educational institutions, and professionals are always on the lookout for trusted sources of quality laptops and computing systems. That’s where specialized distributors and retailers play a vital role in ensuring the accessibility of top-tier brands in the region. From corporate-grade machines to student-friendly devices, Dubai’s diverse user base relies heavily on well-established distribution networks to fuel their digital needs.

Let’s explore how Dubai has become a hotspot for laptop distribution and what consumers and businesses can expect when seeking out brands like Dell and HP.

Dell Dubai Distributor: A Backbone for Corporate Computing

A Dell Dubai Distributor holds a crucial position in the city’s business ecosystem. As organizations increasingly adopt remote and hybrid work models, the reliability and performance of their hardware become essential. Dell, known for its enterprise-grade laptops and workstations, is a brand often chosen by corporations, startups, and government entities in Dubai.

These distributors ensure a streamlined supply chain that brings the latest Dell technologies directly into the hands of professionals. From bulk enterprise procurement to after-sales technical support, a certified distributor delivers value beyond just product sales. Their partnerships with businesses include configuration services, warranty management, and technical consultations tailored to each client’s infrastructure. Dubai's strategic position as a logistics and business hub also allows these distributors to serve clients across the MENA region, extending their influence and boosting the local economy.

Exploring the Variety of HP Laptop Dubai Options

Dubai’s consumer market is just as dynamic as its commercial sector. Whether it’s a student in need of a lightweight notebook or a creative professional looking for a power-packed workstation, HP laptops in Dubai offer a wide array of options tailored to every user type. HP Laptop Dubai offerings can be found in numerous configurations—ranging from entry-level devices for everyday tasks to high-performance machines equipped with the latest processors and graphics capabilities.

Dubai’s HP resellers and retail platforms often feature multilingual support, international warranty options, and frequent promotional bundles to attract a diverse clientele. Moreover, tech-savvy customers in the city often rely on expert advice from these outlets to make informed decisions about specifications, battery life, software compatibility, and upgrade possibilities. HP laptops are popular not only for their hardware but also for their sleek design and reliable customer service.

Dell Laptop Dubai: Versatility for Every Need

Whether for professional use, educational purposes, or personal entertainment, Dell laptops have carved out a substantial presence in the city. Dell Laptop Dubai availability is vast and includes models from the Inspiron, XPS, Latitude, and Precision series. Each line is carefully designed to cater to a specific segment of users.

In particular, Dell’s XPS series is highly favored by developers and digital creatives, thanks to its superior screen quality, robust performance, and elegant build. Meanwhile, Latitude laptops are known for their enterprise-level security features and long battery life, making them ideal for Dubai’s business leaders on the go. Retailers and distributors in Dubai often work directly with Dell to ensure they provide the latest releases, extended warranty options, and genuine accessories—ensuring a complete and trusted customer experience.

HP Dubai Distributor: Enhancing Access to Global Innovation

A trusted HP Dubai Distributor serves as a vital bridge between global tech innovation and local consumer demand. These authorized distributors provide more than just access to devices—they also deliver training, technical workshops, and integration solutions for large organizations.

Given HP’s extensive lineup, from the popular Pavilion and Envy series to the high-end Spectre and EliteBook lines, the distributor’s role is essential in helping customers navigate their choices. They play a significant part in supply chain logistics, custom configurations for enterprise clients, and even localized software optimization to ensure compatibility with regional regulatory requirements. For tech-driven institutions such as schools, hospitals, and government agencies, HP distributors in Dubai enable customized procurement strategies that align with budget and usage expectations.

After-Sales Service and Technical Support

Dubai’s reputation as a global tech hub isn't solely dependent on product availability—it also thrives due to the superior service infrastructure surrounding these products. Most certified distributors offer after-sales support such as device setup, warranty servicing, data recovery, and even software troubleshooting. These services are often crucial in business continuity, especially when a system failure can translate into lost hours or even missed deadlines.

Furthermore, some top-tier resellers in Dubai even offer on-site technical support, instant replacement policies, and remote diagnostics, enhancing user satisfaction and minimizing downtime. With increasingly tech-savvy consumers and organizations, such offerings are no longer optional—they're a necessity.

Buying Smart: Tips for Choosing the Right Laptop in Dubai

If you’re in the market for a new laptop in Dubai, there are a few key considerations to keep in mind:

Define Your Usage: Are you buying for casual use, business operations, or creative work? Each purpose has specific requirements in terms of RAM, CPU, storage, and screen resolution.

Set a Budget: With frequent discounts and seasonal promotions, it’s possible to find premium features even at mid-range prices.

Verify Warranty: Ensure your device is covered by international or local warranty for peace of mind.

Consider After-Sales Support: Choose distributors or retailers who offer responsive technical service.

Check Authenticity: Purchase only from authorized dealers to avoid counterfeit or refurbished products without proper disclosure.

Laptop-Dubai.com: Connecting You to Top-Tier Technology

Dubai’s growing reliance on digital technologies across all sectors means that reliable access to quality laptops is more important than ever. Websites like laptop-dubai.com serve as a central marketplace that brings together a wide range of devices from leading brands. Whether you are a corporate buyer looking to upgrade your company’s devices or a student preparing for a new academic year, having a trusted platform simplifies your shopping experience.

This online portal combines ease of navigation with detailed product descriptions, customer reviews, and dedicated customer support. By providing quick access to both HP and Dell products, laptop-dubai.com aligns with the city’s fast-paced lifestyle and ensures timely delivery and satisfaction.

Conclusion: Empowering a Smarter Future in Dubai

Dubai continues to position itself as a leader in technology and innovation, and access to reliable, high-performance computing solutions is a big part of that success. Whether through a Dell Dubai Distributor ensuring seamless enterprise integration, or an HP Dubai Distributor bringing cutting-edge design to individual users, the city remains well-equipped to handle the digital demands of the modern world.

[jcmarchi]

Apple developing custom chips for smart glasses and more

New Post has been published on https://thedigitalinsider.com/apple-developing-custom-chips-for-smart-glasses-and-more/

Apple developing custom chips for smart glasses and more

Apple continues its focus on hardware produced in-house, and is currently working on a new generation of chips for future hardware, according to Bloomberg.

The processors are thought to be destined for use in smart glasses, AI-capable servers, and the next generations of Macs.

One project involves a custom chip designed for smart glasses, which are thought to offer voice commands, photo capture, and audio playback, but will not be full augmented reality (AR) devices. The chip design is based on the low-power components used at present in the latest models of the Apple Watch, but modified to use less energy and support multiple cameras.

Apple has yet to comment on any of the rumoured projects ­ it’s a company with a strict policy of keeping the products it may, or may not be developing under wraps. However, production for the glasses chip is said to begin by late 2026 or early 2027. If that timeline holds true, devices could reach the market in two years. As with most of Apple’s chips, Taiwan Semiconductor Manufacturing Co. is expected to handle production.

Smart glasses have been in development at Apple for several years, industry insiders claim. The company aims to build full AR wearables that overlay digital information onto real-world views, but the technology is yet to be ready for everyday use. In this sector, Meta has already broken some ground, launching smart glasses in partnership with Ray-Ban. Apple seems to be pursuing a similar product, minus the AR features – at least, in any device’s first iteration.

Sources say Apple is developing both AR and non-AR glasses under the codename N401, previously N50. According to reports, Apple’s CEO Tim Cook hopes for the company to take a lead in this market segment. Meta, meanwhile, is expanding its own product line, planning to debut a high-end model of its Ray-Ban style device with a display later this year. The company is said to be targeting 2027 for its first, fully-AR glasses gadget.

Apple’s non-AR glasses could use cameras to scan the environment and apply AI to assist users, mirroring Meta’s current strategy. Apple is said to be biding its time, and waiting for AI software to mature before committing to a full product release.

In the meantime, Apple is exploring other avenues to improve its current product lines, with engineers reportedly testing features like cameras in AirPods and smartwatches, which will likely use Apple chips currently in development. Codename “Nevis” is slated for a camera-enabled Apple Watch, while “Glennie” is intended for AirPods. Both are thought to be planned for release by 2027.

Apple is said to be preparing a new set of processors specifically for Macs; the M6 (Komodo) and M7 (Borneo), and a higher-end chip “Sotra”. Apple is also thought to be planning to upgrade the iPad Pro and MacBook Pro with its M5 chip later this year.

Internal-to-Apple chip development efforts are part of Apple’s broader push to control the full hardware stack of its products. The hardware group, led by Johny Srouji, has been expanding its portfolio: Earlier this year, Apple launched its first in-house modem chip in the iPhone 16e, with a higher-end version, the C2, planned for release in 2026.

(Photo by Unsplash)

See also: Apple AI stresses privacy with synthetic and anonymised data

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

[shakshi09]

How do analysts find data trends?

Data analysts use a structured approach to discover trends within data, which involves collecting, processing, analyzing, and interpreting data to extract meaningful insights. The process begins with data collection from various sources such as databases, surveys, sensors, or business systems. This data can be structured (like SQL databases) or unstructured (such as logs or social media content).

Once the data is gathered, cleaning and preprocessing is essential to remove errors, duplicates, or irrelevant values. Tools like Excel, Python (with libraries such as Pandas and NumPy), or R are widely used for this step. Clean data ensures more accurate trend analysis.

The next step is exploratory data analysis (EDA), where analysts use statistical techniques to understand patterns. Visualizations play a key role in EDA — charts, histograms, scatter plots, and line graphs help identify relationships and anomalies. Software like Tableau, Power BI, or Matplotlib in Python assist in building these visuals.

Analysts then apply trend analysis methods, such as moving averages, regression analysis, and time series analysis, to detect patterns over time. They may segment data by categories (e.g., region, product, customer type) to spot trends that may not be visible in aggregate data.

To confirm these trends, analysts often run hypothesis tests or apply predictive models to forecast future behavior. Contextual knowledge about the domain (e.g., finance, marketing, healthcare) helps interpret the trends accurately and make informed business decisions.

Finally, findings are compiled into dashboards or reports for stakeholders, enabling strategic planning and action.

To build these skills and learn practical techniques, enrolling in an offline data analytics course can provide hands-on experience with real-world datasets and expert guidance.

[loyalty-program]

10 Game-Changing Loyalty Program Trends to Watch in 2025

Loyalty programs have evolved from straightforward point collection models. With advances in technology and increasing customer demands, brands today are compelled to rethink how they build and deploy loyalty. 2025 looks like a breakthrough year, which is going to be replete with innovation and customer-first thinking. In this blog, we dissect the best Loyalty Program Trends that are going to reframe the future of loyalty.

1. Personalization Will Take Center Stage

In 2025, loyalty programs will move beyond segmenting in the simplest way possible. Brands will leverage real-time information, AI, and machine learning to offer, reward, and communicate. Personalized loyalty is no longer a nice-to-have—it's necessary.

2. Omnichannel Loyalty Will Reign

As the consumer seamlessly switches between online and offline channels, omnichannel integration is what Loyalty Program Trends indicate is essential. Irrespective of whether customers are shopping on mobile, in-store, or through social media, their loyalty experience should be the same.

3. Sustainability Rewards Will Gain Momentum

Green consumers are pressuring brands to link rewards to green values. Look for more loyalty programs to include eco-rewards—such as planting trees, carbon offsetting, or giving to green causes—as a part of their loyalty initiatives.

4. Influencer and Affiliate Loyalty Models Will Expand

One of the most exciting loyalty trends is the rise of influencer and affiliate-based programs. Instead of just rewarding buyers, brands are creating systems that incentivize brand advocates, influencers, and affiliates for driving engagement and sales.

5. Tiered and Gamified Loyalty Schemes Will Boost Engagement

Loyalty programs with gamification elements—badges, milestones, spin-to-win—are becoming increasingly popular. Add in tiered benefits, and you’ve got a powerful tool for customer retention and growth.

6. Subscription-Based Loyalty Programs

Brands are merging the realms of loyalty and subscription. These Loyalty Program Trends have customers paying a subscription fee for access to premium rewards, special products, or quicker service—a model that's profitable and sticky.

7. AI-Powered Predictive Loyalty

AI is emerging as a major driver of loyalty marketing. Loyalty professionals forecast 2025 as the year where more companies employ AI to anticipate customer behavior, predict churn, and provide the appropriate incentives at the appropriate moment through their loyalty program software.

8. Hyperlocal and Community-Based Programs

The loyalty business is localizing. Whether it's regional neighborhood rewards or social initiatives, companies are employing localized loyalty programs to forge more emotional connections with their audiences.

9. Crypto and Digital Wallet Integrations

Blockchain and digital currency are starting to take a larger position in loyalty. Look for Loyalty Program Trends that enable users to accumulate crypto rewards or earn loyalty points in digital wallets for easier redemption.

10. More Powerful Analytics & Loyalty Management Platforms

Brands will require more powerful loyalty management platforms in 2025 to track customer insights, segment audiences, and personalize offers automatically. The demand for intelligent, data-based decision-making is greater than ever.

Final Thoughts

These trends in loyalty programs are not merely forecasts; they are markers of the direction the sector is taking. The moment to invest in innovative loyalty tactics and astute loyalty program software that promotes adaptability, integration, and customer-centricity has come if your company wants to stay ahead of the competition in the loyalty space.

You can make sure your loyalty programs promote both retention and long-term company success by keeping up with current trends and collaborating with reliable loyalty specialists.

[oliviiaagraceeeeee]

Exploring the Performance Landscape of ASX Technology Stocks

Highlights

Focus on companies listed in the technology sector of the Australian Securities Exchange

Overview of recent market themes influencing ASX Technology Stocks

Examines prominent sectors including software, AI, digital services, and cloud computing

The technology sector on the Australian Securities Exchange (ASX) represents a diverse range of enterprises involved in digital innovation, software development, cloud infrastructure, cybersecurity, and artificial intelligence. ASX Technology Stocks often align with global advancements in tech, adapting and expanding in areas like machine learning, digital transformation, and enterprise solutions.

Digital Platforms and Software Development Trends

Many ASX-listed companies in the technology segment are engaged in enterprise software and service delivery through cloud-based platforms. These entities are contributing to the increasing adoption of software-as-a-service (SaaS) frameworks. Businesses in this domain focus on functionality that enhances workflow automation, customer relationship management, and enterprise-level integration systems. ASX Technology Stocks related to software development often highlight scalable service models that cater to small and large-scale clients across various industries. These firms typically emphasize innovation in product development cycles and agile methodologies.

Cybersecurity and Data Protection Solutions

Cybersecurity remains a core segment within the ASX Technology Stocks universe. Several firms are providing network security, threat detection, and privacy protection tools, addressing rising concerns around data breaches and digital asset security. These entities serve sectors such as finance, healthcare, and education, where secure data handling is critical. The emphasis is on real-time monitoring tools and systems that prevent unauthorized access, ensuring compliance with evolving regulatory frameworks.

Artificial Intelligence and Automation

Companies working with artificial intelligence and automation technologies represent a growing niche within ASX Technology Stocks. These firms typically develop platforms for machine learning, natural language processing, and robotic process automation. The implementation of AI is evident in areas like customer service automation, intelligent document processing, and predictive maintenance in industrial settings. Automation tools are also driving efficiencies in logistics, manufacturing, and financial operations, often with an emphasis on scalability and cost-effectiveness.

Cloud Computing and Infrastructure Development

Cloud computing infrastructure providers are central to the ASX Technology Stocks list. These businesses deliver services such as remote storage, virtual server provisioning, and hybrid cloud solutions. The focus is on enabling digital transformation for both public and private sector clients. Key areas of development include data center expansion, container orchestration, and secure cloud-based collaboration platforms. Companies in this space emphasize high availability and service continuity, which are crucial for operational resilience.

E-commerce and Digital Payment Technologies

Several firms within ASX Technology Stocks are operating in the digital commerce and payments space. These businesses build systems for online transaction processing, digital wallets, and integrated checkout solutions. Their platforms are used by retailers and service providers to support seamless, secure transactions across web and mobile channels. Some companies also specialize in customer identity verification, fraud prevention, and mobile point-of-sale technologies, aligning with increasing digital engagement across industries.

Call to Action

Explore the evolving world of ASX Technology Stocks to stay informed about developments in cybersecurity, AI, cloud infrastructure, and enterprise software. Stay connected with sector-specific news and updates to monitor how technology trends are shaping various industries.

[aestrax0]

Unlocking Business Opportunities with Data Analytics Solutions and Customer Data Management

In today's fast-paced digital world, businesses generate and collect massive amounts of data daily. However, raw data holds limited value unless transformed into actionable insights. This is where Data Analytics Solutions and Customer Data Management come into play. These powerful tools enable businesses to harness data effectively, optimize strategies, enhance customer experiences, and drive growth.

Understanding Data Analytics Solutions

Data Analytics Solutions encompass a range of technologies and methodologies used to analyze data anAd derive meaningful insights. These solutions utilize advanced techniques like machine learning, artificial intelligence, and statistical analysis to process data from various sources. By interpreting historical and real-time data, businesses can make informed decisions, predict trends, and improve overall efficiency.

Key Components of Data Analytics Solutions

Data Collection and Integration: Gathering data from diverse sources such as websites, social media, CRM systems, and more.

Data Processing: Cleaning and organizing data to ensure accuracy and relevance.

Data Analysis: Applying analytical models and algorithms to extract insights.

Data Visualization: Presenting data through dashboards and visual reports for easy understanding.

Predictive and Prescriptive Analytics: Using historical data to forecast future trends and recommending actionable strategies.

The Role of Customer Data Management

Customer Data Management (CDM) involves collecting, organizing, and maintaining customer information. It ensures that customer data is accurate, up-to-date, and accessible, enabling businesses to build strong customer relationships and personalize experiences.

Key Aspects of Customer Data Management

Data Collection: Gathering customer information through interactions, transactions, and surveys.

Data Storage: Storing data securely in centralized systems or cloud databases.

Data Segmentation: Categorizing customers based on demographics, behavior, and preferences.

Data Analysis: Understanding customer behavior and identifying trends.

Data Compliance: Ensuring data management practices align with data protection regulations.

How Data Analytics Solutions Enhance Customer Data Management

Combining Data Analytics Solutions with Customer Data Management creates a powerful synergy that helps businesses understand their customers better and offer tailored experiences.

Personalized Marketing Campaigns: Analyzing customer data to deliver targeted advertisements and offers.

Improved Customer Service: Using insights to predict customer needs and enhance support.

Increased Customer Retention: Identifying patterns that lead to churn and implementing proactive strategies.

Enhanced Product Development: Gathering customer feedback to guide innovation.

Implementing Effective Data Analytics Solutions

Define Objectives

Before implementing Data Analytics Solutions, businesses need to establish clear goals. Whether the aim is to improve sales, optimize marketing, or enhance customer service, having a defined objective ensures focused analysis.

Choose the Right Tools

Selecting the appropriate analytics tools is crucial. Depending on business needs, this might include software for data visualization, predictive analytics, or machine learning.

Data Collection and Management

Businesses must ensure that data is collected ethically and stored securely. Integrating Customer Data Management tools helps in organizing and maintaining high-quality data.

Data Analysis and Interpretation

Using analytical models and algorithms, businesses can extract valuable insights. Visualizing this data through dashboards helps teams make informed decisions quickly.

Apply Insights

The final step is translating insights into actionable strategies. Whether it’s launching a new product or adjusting marketing tactics, data-driven decisions lead to measurable outcomes.

Best Practices for Customer Data Management

Ensure Data Accuracy: Regularly update customer information to maintain accuracy.

Data Security: Implement robust security measures to protect customer data from breaches.

Compliance with Regulations: Adhere to GDPR, CCPA, and other data protection laws.

Customer Consent: Obtain permission before collecting and using customer data.

Data Transparency: Clearly communicate how customer data is used to build trust.

Real-World Examples

E-commerce

An e-commerce company implemented Data Analytics Solutions to analyze customer browsing and purchase patterns. By integrating Customer Data Management, they personalized product recommendations, resulting in a 20% increase in sales.

Healthcare

A healthcare provider used data analytics to streamline patient management systems. With effective Customer Data Management, they improved patient engagement and optimized appointment scheduling.

The Future of Data Analytics and Customer Data Management

The evolution of technology, including AI and machine learning, continues to transform Data Analytics Solutions and Customer Data Management. Businesses that adopt these technologies will gain a competitive edge, offering hyper-personalized experiences and making smarter decisions faster.

Conclusion

Data Analytics Solutions and Customer Data Management are no longer optional for businesses aiming for success. These tools offer insights that drive strategic decisions, improve customer experiences, and boost profitability. By investing in robust analytics and customer data strategies, businesses can stay ahead in today's data-driven world.

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[industrynewsupdates]

Self-supervised Learning Market Growth: A Deep Dive Into Trends and Insights

The global self-supervised learning market size is estimated to reach USD 89.68 billion by 2030, expanding at a CAGR of 35.2% from 2025 to 2030, according to a new report by Grand View Research, Inc. Self-supervised learning is a machine learning technique used prominently in Natural Language Processing (NLP), followed by computer vision and speech processing applications. Applications of self-supervised learning include paraphrasing, colorization, and speech recognition. 

The COVID-19 pandemic had a positive impact on the market. More businesses adopted AI and Machine Learning as a response to the COVID-19 pandemic. Many prominent market players such as U.S.-based Amazon Web Services, Inc., Google, and Microsoft witnessed a rise in revenue during the pandemic. Moreover, accelerated digitalization also contributed to the adoption of self-supervised learning applications. For instance, in April 2020, Google Cloud, a business segment of Google, launched an Artificial Intelligence (AI) chatbot that provides critical information to fight the COVID-19 pandemic.

Many market players offer solutions for various applications such as text-to-speech and language translation & prediction. Moreover, these players are researching in self-supervised learning. For instance, U.S.-based Meta has been advancing in self-supervised learning research and has developed various algorithms and models. In February 2022, Meta announced new advances in the company’s self-supervised computer vision model SEER. The model is more powerful and is expected to enable the company in building computer vision products. 

Request Free Sample PDF of Self-supervised Learning Market Size, Share & Trends Analysis Report

Self-supervised Learning Market Report Highlights

• In terms of end-use, the BFSI segment accounted for the largest revenue share of 18.3% in 2024 and is expected to retain its position over the forecast period. This can be attributed to the increasing adoption of technologies such as AI and ML in the segment. The Advertising & Media segment is anticipated to register lucrative growth over the forecast period.

• Based on technology, the natural language processing segment accounted for the dominant share in 2024 due to its ability to handle vast amounts of unstructured text data across multiple industries.. This can be attributed to the variety and penetration of NLP applications.

• North America held the largest share of 35.7% in 2024 and is expected to retain its position over the forecast period. This can be attributed to the presence of a large number of market players in the region. Moreover, the presence of specialists and developed technology infrastructure are aiding the growth of the market.

• In July 2024, Google LLC launched the Agricultural Landscape Understanding (ALU) tool in India, an AI-based platform that uses high-resolution satellite imagery and machine learning to provide detailed insights on drought preparedness, irrigation, and crop management at an individual farm level.

• In May 2024, Researchers from Meta AI, Google, INRIA, and University Paris Saclay created an automatic dataset curation technique for self-supervised learning (SSL) using embedding models and hierarchical k-means clustering. This method improves model performance by ensuring balanced datasets and reducing the costs and time associated with manual curation.

Self-supervised Learning Market Segmentation

Grand View Research has segmented the global Self-supervised Learning market based on application and region:

Self-supervised Learning End Use Outlook (Revenue, USD Million, 2018 - 2030)

• Healthcare

• BFSI

• Automotive & Transportation

• Software Development (IT)

• Advertising & Media

• Others

Self-supervised Learning Technology Outlook (Revenue, USD Million, 2018 - 2030)

• Natural Language Processing (NLP)

• Computer Vision

• Speech Processing

Self-supervised Learning Regional Outlook (Revenue, USD Million, 2018 - 2030)

• North America

o U.S.

o Canada

o Mexico

• Europe

o UK

o Germany

o France

• Asia Pacific

o China

o Japan

o India

o Australia

o South Korea

• Latin America

o Brazil

• Middle East & Africa (MEA)

o KSA

o UAE

o South Africa

List of Key Players in Self-supervised Learning Market

• Amazon Web Services, Inc.

• Apple Inc.

• Baidu, Inc.

• Dataiku

• Databricks

• DataRobot, Inc.

• IBM Corporation

• Meta

• Microsoft

• SAS Institute Inc.

• Tesla

• The MathWorks, Inc.

Order a free sample PDF of the Self-supervised Learning Market Intelligence Study, published by Grand View Research.

[athulyavijayan]

Data Science vs. Machine Learning vs. Artificial

Intelligence: What Is the Difference

Technology advancement has popularized many buzzwords, and Data Science,

Machine Learning (ML), and Artificial Intelligence (AI) are the three most

commonly mixed terms. Although all of these domains share a wide range of

overlapping functions, they play distinct roles in the arena of technology and

business. Knowledge about their distinction is essential for experts, businesses,

and students pursuing a career in data-driven decision-making.

What is Data Science?

Definition

Data Science is a multi-disciplinary area that integrates statistics, mathematics,

programming, and domain expertise to extract useful information from data. It is

centered on data gathering, cleaning, analysis, visualization, and interpretation to

support decision-making

Key Components of Data Science

1. Data Collection – Extracting raw data from multiple sources, including

databases, APIs, and web scraping.

2. Data Cleaning – Deleting inconsistencies, missing values, and outliers to

ready data for analysis.

3. Exploratory Data Analysis (EDA) – Grasping data trends, distributions, and

patterns using visualizations.

4. Statistical Analysis – Using probability and statistical techniques to make

conclusions from data.5. Machine Learning Models – Utilizing algorithms to predict and automate

insights.

6. Data Visualization – Making graphs and charts to present findings clearly.

Real-World Applications of Data Science

Business Analytics – Firms employ data science for understanding customer

behavior and optimizing marketing efforts.

Healthcare – Doctors utilize data science for disease prediction and drug

development.

Finance – Banks use data science for fraud detection and risk evaluation.

E-commerce – Businesses understand customer ratings and product interest to

make recommendations better.

What is Machine Learning?

Definition

Machine Learning (ML) is a branch of artificial intelligence that deals with the

creation of algorithms that enable computers to learn from data and get better

over time without being directly programmed. It makes it possible for systems to

make predictions, classifications, and decisions based on patterns in data.

Key Elements of Machine Learning

1. Supervised Learning – The model is trained on labeled data (e.g., spam

filtering, credit rating).2. Unsupervised Learning – The model learns patterns from unlabeled data (e.g.,

customer segmentation, anomaly detection).

3. Reinforcement Learning – The model learns by rewards and penalties to

maximize performance (e.g., self-driving cars, robotics).

4. Feature Engineering – Variable selection and transformation to enhance model

accuracy.

5. Model Evaluation – Model performance evaluation using metrics such as

accuracy, precision, and recall.

Real-World Applications of Machine Learning

Chatbots & Virtual Assistants – Siri, Alexa, and Google Assistant learn user

preferences to enhance responses.

Fraud Detection – Banks utilize ML models to identify suspicious transactions.

Recommendation Systems �� Netflix, YouTube, and Spotify utilize ML to

recommend content based on user behavior.

Medical Diagnosis – Machine learning assists in identifying diseases from X-rays

and MRIs.

What is Artificial Intelligence?

Definition

Artificial Intelligence (AI) is a more general term that focuses on building

machines with the ability to emulate human intelligence. It encompasses

rule-based systems, robots, and machine learning algorithms to accomplish

tasks usually requiring human intelligence.

Types of Artificial Intelligence1. Narrow AI (Weak AI) – Built for particular functions (e.g., facial recognition,

search engines).

2. General AI (Strong AI) – Seeks to be able to do any intellectual task that a

human can accomplish (not yet fully achieved).

3. Super AI – A hypothetical phase in which machines are more intelligent than

humans.

Important Elements of AI

Natural Language Processing (NLP) – AI's capacity to process and create human

language (e.g., chatbots, voice assistants).

Computer Vision – The capability of machines to interpret and process images

and videos (e.g., facial recognition).

Expert Systems – AI-powered software that mimics human decision-making.

Neural Networks – A subset of machine learning inspired by the human brain,

used for deep learning.

Real-World Applications of AI

Self-Driving Cars – AI enables autonomous navigation and decision-making.

Smart Assistants – Google Assistant, Alexa, and Siri process voice commands

using AI.

Healthcare Innovations – AI helps in robotic surgeries and personalized

medicine.

Cybersecurity – AI detects cyber threats and prevents cyberattacks.

Data Science vs. Machine Learning vs. AI: Main Differences

How These Disciplines Interact

AI is the most general discipline that machine learning is a part of.

Machine learning is an approach applied in AI to create self-improving models.

Data science uses machine learning for business intelligence and predictive

analytics.

For instance, in a Netflix recommendation engine:

Data Science gathers and examines user action

Machine Learning forecasts what content a user will enjoy given past decisions.

Artificial Intelligence personalizes the recommendations through deep learning

and NLP.

Conclusion

Data Science, Machine Learning, and Artificial Intelligence are related but have

different applications and purposes. Data science is all about data analysis and

visualization to derive insights, machine learning is about constructing models

that can learn from data, and AI is concerned with developing machines that can

emulate human intelligence.

Knowing these distinctions will assist professionals in selecting the ideal career

path and companies in optimizing these technologies to their advantage.

Whether you aspire to have a career in data analytics, construct AI-based

applications, or work on machine learning models, there are promising avenues

in each one of these professions in the modern data-centric age

[technorucs]

Maximizing Business Efficiency with Microsoft Dynamics 365: The Power of ERP & CRM Customization

Introduction

In today’s fast-paced business landscape, organizations need intelligent solutions to manage operations, enhance customer relationships, and drive efficiency. microsoft dynamics 365 is a powerful suite that integrates Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) into one seamless platform. However, the true potential of Dynamics 365 is unlocked through customization, which allows businesses to tailor the software to their specific needs.

This article explores how Microsoft Dynamics 365 can be customized to enhance business operations and improve customer relationships, helping organizations stay ahead in the competitive market.

Understanding Microsoft Dynamics 365: ERP and CRM

Microsoft Dynamics 365 is a cloud-based solution that combines ERP and CRM functionalities.

ERP (Enterprise Resource Planning) focuses on managing financials, supply chain, human resources, and operations.

CRM (Customer Relationship Management) helps businesses nurture customer relationships, manage sales pipelines, and improve marketing campaigns.

By integrating both aspects into a single platform, Dynamics 365 eliminates data silos and enhances decision-making through real-time insights.

Why Customization is Essential

Every business has unique requirements, and a one-size-fits-all approach does not work when it comes to enterprise software. Customization enables companies to:

Improve Workflow Efficiency: Automate processes and reduce manual intervention.

Enhance User Experience: Create intuitive dashboards and interfaces tailored to business roles.

Integrate with Third-Party Applications: Seamlessly connect with other tools and software.

Optimize Reporting and Analytics: Generate customized reports and dashboards for better decision-making.

Ensure Compliance: Align the system with industry-specific regulations and policies.

Customization Options in Microsoft Dynamics 365

Microsoft Dynamics 365 offers several customization options to cater to the specific needs of different industries and business models. Let’s explore some key customization methods.

1. User Interface Customization

A well-structured user interface (UI) enhances user adoption and productivity. Businesses can:

Modify forms and views to display relevant data.

Add custom dashboards with role-specific KPIs.

Implement color schemes and branding for a consistent look.

Customize navigation menus for easier access to important functions.

2. Custom Workflows and Automation

Automation helps eliminate repetitive tasks and streamlines operations. Some automation possibilities include:

Auto-assigning leads based on predefined rules.

Sending automated follow-up emails and reminders.

Triggering notifications when specific conditions are met.

Creating approval workflows for finance and HR processes.

3. Custom Entities and Fields

Every business has unique data points that standard Dynamics 365 entities may not cover. Companies can:

Create new entities (e.g., project management, inventory tracking).

Add custom fields to store industry-specific information.

Define relationships between different entities for better data management.

Implement calculated fields to automate complex business calculations.

4. Business Rules and Logic

Businesses can define logic within the system to enforce specific rules without coding. Examples include:

Automatically setting discount percentages based on purchase volume.

Preventing order creation if stock levels are low.

Enforcing data validation to ensure accuracy.

Implementing dynamic pricing models based on customer segments.

5. PowerApps and Custom Applications

PowerApps enables businesses to build custom applications that integrate seamlessly with Dynamics 365. These applications can be used for:

Mobile workforce solutions.

Customer self-service portals.

Field service management tools.

Custom inventory tracking and reporting apps.

6. Integration with Third-Party Systems

Microsoft Dynamics 365 can be integrated with various third-party applications using APIs and connectors. Popular integrations include:

Payment gateways (PayPal, Stripe).

Marketing automation tools (HubSpot, Mailchimp).

E-commerce platforms (Shopify, WooCommerce).

HR and payroll systems for seamless employee management.

7. AI and Machine Learning Enhancements

With AI-powered tools like Microsoft Copilot, businesses can enhance automation and insights, enabling:

Predictive analytics for sales forecasting.

AI-driven chatbots for customer service.

Sentiment analysis for better customer engagement.

Intelligent data recommendations for sales and marketing teams.

Benefits of Customizing Dynamics 365

1. Increased Productivity

By tailoring workflows and automating repetitive tasks, employees can focus on strategic activities, leading to higher efficiency.

2. Better Customer Experience

Customized CRM features enable businesses to provide personalized interactions, track customer history, and improve service delivery.

3. Scalability and Flexibility

As businesses grow, their needs evolve. Customization ensures that Dynamics 365 can scale to accommodate new processes, departments, and users.

4. Cost Savings

Investing in customization reduces the need for additional third-party applications, lowering overall IT costs.

5. Data-Driven Decision Making

Customized dashboards and reports provide businesses with deeper insights into customer behavior, sales trends, and operational efficiency.

Best Practices for Customization

To maximize the benefits of Microsoft Dynamics 365 customization, businesses should follow these best practices:

1. Define Clear Objectives

Identify business challenges and goals before making changes to ensure alignment with overall strategy.

2. Engage Stakeholders

Involve key users from different departments to gather feedback and ensure the customized solution meets their needs.

3. Leverage Microsoft Power Platform

Use Power Automate, Power BI, and PowerApps to enhance customization and extend functionalities.

4. Test and Optimize

Regularly test customizations to ensure they function as expected and refine them based on user feedback.

5. Ensure Security and Compliance

Implement role-based access controls and follow industry regulations to protect sensitive data.

6. Continuous Monitoring and Updates

As technology evolves, businesses should continuously monitor their customized Dynamics 365 environment and update it to align with industry trends and security standards.

Conclusion

Microsoft Dynamics 365 provides a robust foundation for businesses, but its true potential is realized through customization. Whether it’s optimizing workflows, integrating with third-party systems, or leveraging AI-driven insights, customizing Dynamics 365 enables organizations to operate efficiently and deliver exceptional customer experiences.

With the right strategy, businesses can transform Dynamics 365 into a powerful tool tailored to their needs, ensuring long-term success in an ever-evolving market. Investing in customization is not just about enhancing software—it’s about creating a future-ready business environment that thrives on innovation and efficiency.

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How Technographic Data Transforms B2B Marketing and Sales?

Technographic data is revolutionizing sales and marketing strategies by providing deep insights into a company's technology stack. In today's competitive landscape, understanding your target audience requires more than just firmographic and demographic data. To create highly targeted marketing campaigns and personalized outreach, businesses must leverage technographic insights—detailed data on the software, tools, and infrastructure their prospects use. By analyzing a company’s tech stack, businesses can identify high-intent prospects, refine messaging, and drive more effective engagement.

Technographic data enables B2B marketing teams to refine their ABM (Account-Based Marketing) strategies and create data-driven marketing campaigns that resonate with their ideal customers. By leveraging this information, businesses can gain a competitive edge, improve lead qualification, and drive higher conversion rates.

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What is Technographic Data?

Technographic data refers to insights about the technologies, software, and tools a company uses. This includes everything from CRM systems and marketing automation platforms to cloud solutions and cybersecurity tools.

By analyzing technographic data, B2B marketers can determine which businesses are most likely to benefit from their products or services. This allows for more precise targeting and better resource allocation.

Why Technographic Data Matters in B2B Marketing

Traditional B2B marketing relies on broad segmentation, but technographic data provides granular insights into a company’s tech environment. This makes marketing efforts more strategic and efficient.

For instance, if your company provides cloud-based cybersecurity solutions, knowing which businesses currently use outdated security software can help you identify high-priority prospects. Instead of relying on generic messaging, you can craft tailored campaigns that address specific pain points.

The Role of Technographics in ABM (Account-Based Marketing)

ABM is all about precision. Instead of casting a wide net, businesses using ABM focus on high-value accounts with personalized, relevant content. Technographic data enhances this approach by ensuring that the accounts selected have a genuine need for your solution.

For example, if a company’s tech stack includes your competitor’s software, you can design a competitive displacement strategy that highlights your advantages. This allows for smarter, more effective engagement with decision-makers.

How Technographic Data Enhances Lead Scoring

Lead scoring helps marketing and sales teams prioritize leads based on their likelihood to convert. Incorporating technographic data into lead scoring models improves accuracy by identifying prospects who already use complementary technologies.

For example, if your software integrates with Salesforce, targeting companies that already use Salesforce means they are more likely to be interested in your solution. This shortens sales cycles and increases win rates.

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Personalizing Data-Driven Marketing Campaigns

Personalization is key to modern B2B marketing. Technographic data allows marketers to create highly targeted content and messaging that speaks directly to a prospect’s needs.

Imagine running a LinkedIn ad campaign specifically for companies using a particular email automation tool. By aligning your messaging with their existing tech stack, you increase engagement and conversion rates significantly.

Improving Sales Outreach with Technographic Insights

Sales teams often struggle with cold outreach. However, technographic data provides valuable context that enables more meaningful conversations.

Instead of sending a generic sales pitch, your sales reps can open discussions by referencing the technologies a prospect already uses. This builds credibility and trust, making prospects more likely to engage in meaningful conversations.

Using Technographics for Competitive Intelligence

Understanding your competitors’ customer base is a powerful growth strategy. Technographic data allows you to identify companies currently using competing solutions and create targeted campaigns aimed at converting them.

For instance, if a prospect is using a competing CRM, your marketing team can highlight features and benefits that differentiate your product. By positioning your solution as an upgrade, you increase the likelihood of conversion.

The Future of Technographic Data in B2B Marketing

As B2B marketing becomes increasingly data-driven, technographic insights will continue to play a crucial role. With advancements in AI and predictive analytics, businesses will be able to anticipate buyer needs before they even arise.

Moving forward, integrating technographic data with intent data and firmographics will create even more refined targeting models. Companies that adopt data-driven marketing strategies will stay ahead of the competition and drive higher revenue growth.

Final Thoughts

Technographic data is no longer a nice-to-have—it’s a must-have for any B2B marketing strategy looking to improve targeting, enhance ABM strategies, and drive higher conversions. By understanding the technologies your prospects use, you can deliver more personalized, impactful marketing campaigns that result in faster sales cycles and stronger customer relationships. For businesses looking to leverage technographic insights, now is the time to start. Whether you’re refining your lead generation strategy, optimizing sales outreach, or building a data-driven B2B marketing approach, technographic data will be the key to B2B success.