#IBM Financial Transaction Manager

[techzert]

IBM Financial Transaction Manager (FTM) Consulting Services

Are you searching for expert guidance and unwavering support in navigating the complexities of financial transaction management? Look no further! Techzert offers top-notch IBM FTM Consulting services to empower your financial institution & accelerate the growth of your business during your Payments Modernization & Digital Transformation Journey.

[digitaldetoxworld]

The Rise of Blockchain: Changing Business, Politics, and Everyday Life

 Blockchain generation has evolved considerably on account that its inception in 2008 as the inspiration for Bitcoin. Initially identified for its function in cryptocurrencies, blockchain has increased into a couple of industries, disrupting traditional commercial enterprise fashions and influencing society in profound ways. From improving transparency and security in transactions to allowing decentralized finance, blockchain is revolutionizing how businesses operate and how human beings interact with digital structures. This article explores the effect of blockchain on organizations and society, focusing on its advantages, demanding situations, and potential destiny developments.

Impact Of Blockchain On Society

Impact on Business

Blockchain generation gives organizations numerous advantages, which includes improved security, efficiency, and transparency. Many industries are leveraging blockchain to optimize operations, lessen costs, and construct agree with among stakeholders.

1. Enhanced Security and Transparency

One of blockchain’s maximum enormous benefits is its ability to offer steady and obvious transactions. The decentralized and immutable nature of blockchain manner that once facts is recorded, it cannot be altered or deleted. This gets rid of the chance of fraud, unauthorized get entry to, and information manipulation, that is specifically useful in industries like banking, healthcare, and deliver chain management.

For example, in economic services, blockchain ensures that transactions are steady and verifiable, lowering the risks of fraud and cyberattacks. Smart contracts—self-executing contracts with coded regulations—in addition decorate protection through making sure agreements are automatically enforced with out intermediaries.

2. Efficiency and Cost Reduction

Blockchain eliminates the want for intermediaries, decreasing transaction expenses and increasing operational efficiency. Traditional commercial enterprise processes regularly contain multiple parties, main to delays and further expenses. Blockchain simplifies transactions by permitting peer-to-peer interactions and real-time agreement.

For instance, in deliver chain management, blockchain allows actual-time monitoring of goods from production to transport. Companies like IBM and Walmart use blockchain to beautify supply chain transparency, decreasing inefficiencies and improving product authenticity.

3 Transforming Financial Services

The monetary sector has skilled substantial disruption because of blockchain. Decentralized finance (DeFi) platforms provide alternatives to standard banking, permitting customers to get right of entry to economic offerings without relying on centralized institutions.

Blockchain-based virtual currencies, including Bitcoin and Ethereum, have added new strategies of moving value globally with minimal fees. Cross-border payments, which formerly took days and involved excessive transaction prices, at the moment are processed instantly and value-efficiently using blockchain era.

Moreover, valuable banks worldwide are exploring Central Bank Digital Currencies (CBDCs) to improve financial rules and financial inclusion. Countries like China, Sweden, and the US are trying out CBDCs to streamline charge systems and decrease reliance on coins.

Four. Improved Data Management and Identity Verification

Businesses generate enormous quantities of information that require steady garage and efficient control. Blockchain gives a decentralized answer for statistics management, ensuring records is stored securely and accessed most effective by way of legal events.

One of the maximum promising applications is digital identity verification. Blockchain-primarily based identity answers permit people to manipulate their non-public records, lowering identification robbery and fraud. Companies like Microsoft and IBM are growing blockchain-primarily based virtual identification structures to improve safety and privacy.

Five. Revolutionizing Healthcare

Blockchain is remodeling the healthcare industry via improving records security, patient file management, and drug supply chain monitoring.

Patient information saved on blockchain can be securely accessed with the aid of authorized healthcare companies, ensuring correct and efficient clinical records monitoring. Additionally, blockchain prevents counterfeit drugs from entering the deliver chain by using verifying the authenticity of pharmaceutical products.

For instance, MediLedger, a blockchain-primarily based community, facilitates pharmaceutical organizations tune pills and prevent counterfeit drugs from achieving purchasers.

6. New Business Models and Innovation

Blockchain allows the improvement of new business fashions, inclusive of tokenization and non-fungible tokens (NFTs). Tokenization lets in agencies to transform bodily assets into digital tokens, allowing fractional possession and liquidity.

NFTs have revolutionized the artwork and amusement enterprise by means of supplying a decentralized way to authenticate and alternate digital assets. Artists and content material creators can promote their paintings directly to shoppers, eliminating the need for intermediaries and ensuring truthful compensation.

Impact on Society

Blockchain is not simply remodeling agencies; it's also reshaping society through selling decentralization, financial inclusion, and believe in virtual interactions.

1. Financial Inclusion

A huge part of the global population lacks get entry to to traditional banking offerings. Blockchain presents an opportunity for the unbanked to participate inside the global economy thru digital wallets and decentralized finance platforms.

Cryptocurrencies and blockchain-based totally financial offerings permit individuals in developing international locations to ship and receive bills without counting on banks. Mobile-based totally blockchain wallets provide an alternative to conventional banking, permitting users to shop and switch finances securely.

For example, structures like Stellar and Celo are centered on supplying less expensive financial offerings to underserved populations, supporting bridge the distance between the unbanked and financial systems.

2. Decentralization and Empowerment

Blockchain promotes decentralization by using getting rid of the need for intermediaries, giving individuals more manipulate over their assets and records. This is specially relevant in regions with risky governments and monetary systems, where human beings face demanding situations accessing banking offerings and securing their wealth.

Decentralized Autonomous Organizations (DAOs) are every other example of blockchain-pushed empowerment. DAOs permit communities to make collective selections without centralized leadership, fostering democratic and obvious governance.

3. Increased Trust and Accountability

In many sectors, lack of transparency and responsibility has led to corruption and inefficiencies. Blockchain enhances trust by using providing an immutable and transparent document of transactions.

Governments and organizations can use blockchain to improve public trust through ensuring transparency in elections, supply chains, and charity donations. For instance, blockchain-primarily based voting systems can save you election fraud and increase voter confidence. Estonia has implemented blockchain-based balloting to beautify electoral protection and integrity.

Four. Environmental and Ethical Concerns

While blockchain gives many benefits, it additionally raises worries, particularly concerning electricity intake. Proof-of-Work (PoW) blockchain networks, which include Bitcoin, require extensive energy to validate transactions, contributing to environmental issues.

However, newer blockchain models like Proof-of-Stake (PoS) consume notably less electricity and are being followed to deal with those worries. Ethereum’s transition from PoW to PoS in 2022 reduced its energy consumption through over ninety nine%, making blockchain extra sustainable.

Five. Privacy and Data Ownership

In the virtual age, private facts is frequently misused via agencies and governments. Blockchain-primarily based privateness solutions empower individuals to manipulate their records and limit unauthorized access.

Self-sovereign identification (SSI) is a concept in which people personal and manipulate their digital identities with out relying on 1/3 events. This prevents records breaches and identity theft at the same time as improving privacy protection.

6. Humanitarian Aid and Crisis Response

Blockchain technology is being used for humanitarian efforts, providing useful resource to refugees and disaster-stricken regions more efficaciously. Organizations like the World Food Programme (WFP) use blockchain to distribute aid without delay to beneficiaries, decreasing fraud and ensuring transparency.

For instance, WFP’s "Building Blocks" assignment uses blockchain to distribute meals assistance to Syrian refugees, ensuring finances attain those in want without intermediaries.

Challenges and Future Outlook

Despite its capacity, blockchain faces numerous challenges, together with:

Regulatory Uncertainty – Governments worldwide are still developing guidelines for blockchain and cryptocurrencies, developing uncertainty for agencies and customers.

Scalability Issues – Some blockchain networks conflict with gradual transaction processing speeds, restricting vast adoption.

Adoption Barriers – Many groups and people lack the technical know-how to put in force and use blockchain correctly.

Security Risks – While blockchain is steady, vulnerabilities in clever contracts and decentralized programs may be exploited via hackers.

[aimarketresearch]

Liquidity Asset Liability Management Solutions Market Size, Share, Trends, Key Drivers, Growth Opportunities and Competitive Outlook

Executive Summary Liquidity Asset Liability Management Solutions Market :

Global liquidity asset liability management solutions market size was valued at USD 604.18 billion in 2023 and is projected to reach USD 835.17 billion by 2031, with a CAGR of 4.13% during the forecast period of 2024 to 2031.

The market report also provides the drivers and restraints for the Liquidity Asset Liability Management Solutions Market that are obtained with the help of SWOT analysis, and also shows all the recent developments, product launches, joint ventures, mergers and acquisitions by the several key players and brands with their systemic company profiles, that are driving the market.  This report gives broader perspective of the market place with its all-inclusive market insights and analysis. A considerate knowledge about  industry, market trends and incredible techniques provided in this document bestows an upper hand in the market.

In this Liquidity Asset Liability Management Solutions Market report, company snapshot, geographical presence, product portfolio, and recent developments are taken into account for studying the company profiles. The transformation in market landscape is analysed in the Liquidity Asset Liability Management Solutions Market report which is mainly observed due to the moves of key players or brands which include developments, product launches, joint ventures, mergers and acquisitions that in turn change the view of the global face of the industry. While analysing market data, company snapshot, geographical presence, product portfolio, and recent developments are taken into account for studying the company profiles.

Discover the latest trends, growth opportunities, and strategic insights in our comprehensive Liquidity Asset Liability Management Solutions Market report. Download Full Report: https://www.databridgemarketresearch.com/reports/global-liquidity-asset-liability-management-solutions-market

Liquidity Asset Liability Management Solutions Market Overview

**Segments**

- Based on component, the global liquidity asset liability management solutions market can be segmented into software and services. The software segment is expected to hold a significant market share due to the increasing adoption of advanced technologies for managing liquidity and assets effectively. On the other hand, the services segment is projected to grow at a substantial rate as organizations seek specialized expertise for implementing and managing asset liability solutions.

- By deployment type, the market can be categorized into cloud and on-premises. The cloud deployment is witnessing rapid growth attributed to benefits such as scalability, cost-efficiency, and ease of access. On-premises deployment, though traditional, is still preferred by certain organizations that require complete control over their asset liability management solutions.

- In terms of organization size, the market is divided into small and medium-sized enterprises (SMEs) and large enterprises. SMEs are increasingly adopting liquidity asset liability management solutions to efficiently manage their financial resources and enhance decision-making processes. Large enterprises, with their high-volume transactions and complex financial operations, are significant contributors to the market growth.

**Market Players**

- Some of the key players in the global liquidity asset liability management solutions market include Oracle, SAP, IBM, FIS, Moody's Analytics, Fiserv, Software AG, Qlik, SAS Institute, and Alteryx. These market players are focusing on product innovations, strategic partnerships, and mergers and acquisitions to enhance their market presence and expand their customer base. With the rising demand for efficient liquidity asset liability management solutions, these companies are investing heavily in research and development activities to offer advanced and tailored solutions to meet the diverse needs of organizations across various industries.

The global liquidity asset liability management solutions market is witnessing significant growth owing to the increasing complexity in managing financial resources and assets effectively. One emerging trend in the market is the integration of artificial intelligence and machine learning technologies to enhance decision-making processes and automate liquidity management tasks. These advanced technologies empower organizations to analyze vast amounts of data in real-time, identify patterns, and optimize liquidity management strategies. Moreover, the growing emphasis on risk management and compliance requirements is driving the adoption of comprehensive asset liability solutions that offer risk assessment and monitoring capabilities to mitigate financial risks and ensure regulatory compliance.

Another key factor shaping the market landscape is the rising demand for cloud-based liquidity asset liability management solutions. Cloud deployment provides organizations with the flexibility to access their financial data securely from anywhere, at any time, leading to improved operational efficiency and decision-making. Furthermore, the scalability and cost-effectiveness of cloud-based solutions make them appealing to organizations of all sizes, especially SMEs looking to streamline their liquidity management processes without heavy upfront investments.

Furthermore, the market is witnessing a shift towards integrated liquidity asset liability management solutions that offer a holistic approach to managing financial assets and liabilities. These integrated solutions provide organizations with a centralized platform to monitor and analyze their liquidity positions, forecast cash flows, and optimize investment strategies. By consolidating various financial data sources and risk factors into a single platform, organizations can gain a comprehensive view of their liquidity risks and opportunities, enabling them to make informed decisions to improve liquidity management and optimize asset utilization.

Moreover, the market players are increasingly focusing on developing industry-specific liquidity asset liability management solutions to cater to the unique requirements of different sectors such as banking, financial services, insurance, and healthcare. By customizing their offerings to address sector-specific challenges and regulations, market players can differentiate themselves in a highly competitive market landscape and gain a competitive edge. Additionally, strategic collaborations with technology partners and industry associations enable market players to leverage their combined expertise and resources to develop innovative solutions that address the evolving needs of organizations in an increasingly dynamic and interconnected global economy. By staying at the forefront of technological advancements and regulatory developments, market players can solidify their position in the market and drive sustainable growth in the long term.The global liquidity asset liability management solutions market is experiencing robust growth driven by the increasing need for organizations to effectively manage their financial resources and assets amid growing complexity in the financial landscape. One of the key trends reshaping the market is the integration of artificial intelligence and machine learning technologies. These technologies enable organizations to enhance decision-making processes, automate liquidity management tasks, and optimize strategies through real-time data analysis and pattern recognition. By leveraging AI and ML, companies can gain deeper insights into their liquidity positions, identify risks, and make informed decisions to improve overall financial performance.

Another significant factor influencing the market is the rising demand for cloud-based solutions. Cloud deployment offers scalability, cost-efficiency, and enhanced accessibility, allowing organizations to streamline liquidity management processes and improve operational efficiency. The flexibility and convenience offered by cloud solutions make them particularly attractive to businesses of all sizes, including SMEs seeking to enhance their liquidity management capabilities without substantial upfront investments. As organizations increasingly prioritize agility and data accessibility, cloud-based liquidity asset liability management solutions are expected to witness continued adoption across various industries.

Furthermore, the market is witnessing a shift towards integrated solutions that provide a comprehensive approach to managing financial assets and liabilities. These integrated platforms empower organizations to consolidate financial data, monitor liquidity positions, forecast cash flows, and optimize investment strategies from a centralized system. By offering a holistic view of liquidity risks and opportunities, integrated solutions enable organizations to make proactive decisions to enhance liquidity management and maximize asset utilization.

Moreover, market players are focusing on developing industry-specific solutions tailored to the unique requirements of sectors such as banking, financial services, insurance, and healthcare. By customizing their offerings to address sector-specific challenges and regulatory frameworks, companies can differentiate themselves in a competitive market landscape and deliver targeted solutions that meet the diverse needs of different industries. Collaborations with technology partners and industry associations further enable market players to leverage expertise and resources for developing innovative solutions that address evolving market demands and regulatory complexities. By aligning with technological advancements and industry trends, market players can strengthen their market positions and drive sustainable growth in the long term.

The Liquidity Asset Liability Management Solutions Market is highly fragmented, featuring intense competition among both global and regional players striving for market share. To explore how global trends are shaping the future of the top 10 companies in the keyword market.

Learn More Now: https://www.databridgemarketresearch.com/reports/global-liquidity-asset-liability-management-solutions-market/companies

DBMR Nucleus: Powering Insights, Strategy & Growth

DBMR Nucleus is a dynamic, AI-powered business intelligence platform designed to revolutionize the way organizations access and interpret market data. Developed by Data Bridge Market Research, Nucleus integrates cutting-edge analytics with intuitive dashboards to deliver real-time insights across industries. From tracking market trends and competitive landscapes to uncovering growth opportunities, the platform enables strategic decision-making backed by data-driven evidence. Whether you're a startup or an enterprise, DBMR Nucleus equips you with the tools to stay ahead of the curve and fuel long-term success.

Answers That the Report Acknowledges:

Market size and growth rate during forecast period

Key factors driving the Liquidity Asset Liability Management Solutions Market

Key market trends cracking up the growth of the Liquidity Asset Liability Management Solutions Market.

Challenges to market growth

Key vendors of Liquidity Asset Liability Management Solutions Market

Opportunities and threats faces by the existing vendors in Global Liquidity Asset Liability Management Solutions Market

Trending factors influencing the market in the geographical regions

Strategic initiatives focusing the leading vendors

PEST analysis of the market in the five major regions

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About Data Bridge Market Research:

An absolute way to forecast what the future holds is to comprehend the trend today!

Data Bridge Market Research set forth itself as an unconventional and neoteric market research and consulting firm with an unparalleled level of resilience and integrated approaches. We are determined to unearth the best market opportunities and foster efficient information for your business to thrive in the market. Data Bridge endeavors to provide appropriate solutions to the complex business challenges and initiates an effortless decision-making process. Data Bridge is an aftermath of sheer wisdom and experience which was formulated and framed in the year 2015 in Pune.

Contact Us: Data Bridge Market Research US: +1 614 591 3140 UK: +44 845 154 9652 APAC : +653 1251 975 Email:- corporatesales@databridgemarketresearch.com

Tag:Liquidity Asset Liability Management Solutions, Liquidity Asset Liability Management Solutions Size, Liquidity Asset Liability Management Solutions Share, Liquidity Asset Liability Management Solutions Growth

[hurriedlyicyrebel]

AI in Fraud Detection: How Smart Technology Fights Financial Crime

Fraud is a growing threat in today’s digital world. As more people shop, bank, and do business online, fraudsters are getting smarter. But thankfully, so is technology. I’ve seen how AI in fraud detection is changing the game—spotting suspicious activity in real time and protecting businesses and customers before damage is done.

What Is AI in Fraud Detection?

AI in fraud detection uses machine learning, pattern recognition, and real-time data analysis to identify unusual behavior. It’s faster and more accurate than traditional systems because it learns over time, adapting to new threats automatically.

Example:

If a customer who always shops in London suddenly makes a purchase in Tokyo five minutes later, AI systems can instantly flag this as suspicious.

Why Is AI Better Than Traditional Methods?

Old fraud detection tools often rely on fixed rules, like: “Flag all transactions over $5,000.” But AI can go deeper.

Key Advantages:

Learns from patterns over time

Reduces false positives (blocking real customers)

Works in real-time

Detects complex fraud involving multiple accounts or steps

How Does AI Detect Fraud?

AI fraud detection usually involves:

Data Collection – Gathering transaction history, device info, location, etc.

Pattern Analysis – Using models to understand normal behavior

Anomaly Detection – Flagging anything that looks out of the ordinary

Risk Scoring – Assigning a threat level to each transaction

Action – Blocking, alerting, or requesting extra verification

Common Use Cases

IndustryAI ApplicationExampleBankingCredit card fraud, identity theftBlocking a hacked account in real timeE-commerceFake transactions, refund fraudDetecting bots or unusual ordersInsuranceClaims fraud detectionFlagging fake accident reportsTelecomSubscription and identity fraudCatching SIM card swapping

Tools and Technologies

Popular tools used for AI-based fraud detection include:

SAS Fraud Management

FICO Falcon Platform

IBM Trusteer

Kount

Darktrace

Amazon Fraud Detector

Most of these use advanced machine learning models, including decision trees, neural networks, and clustering algorithms.

Challenges in AI-Based Fraud Detection

Even with AI, there are a few things to keep in mind:

Data Quality: Poor data leads to poor results

Privacy Concerns: Sensitive customer data must be protected

Evolving Threats: Fraudsters adapt quickly, so models must be updated

Bias Risks: AI must be trained fairly to avoid unfair profiling

The Future of AI in Fraud Detection

AI is expected to become even more powerful through:

Deep Learning for better pattern recognition

Behavioral Biometrics (how you type or move your mouse)

Natural Language Processing to detect fake documents or conversations

Collaborative AI where companies share threat data securely

Final Thoughts

AI in fraud detection is not just a trend—it’s a necessity. With smarter tools, businesses can stay one step ahead of cybercriminals, reduce losses, and keep customers safe. As threats evolve, AI is proving to be the most reliable guard at the gate.

[theblockchainking]

Top 10 Blockchain Firms for Enterprise Solutions

Blockchain isn't just for crypto enthusiasts and meme coins anymore—it’s a game-changer for businesses looking to streamline processes, improve transparency, and even add a little bit of “future-proofing” to their operations. But with so many firms offering blockchain solutions, how do you choose the right one? Don’t worry, we’ve got you covered! Here’s our curated list of the top 10 blockchain firms for enterprise solutions that’ll help you take your business to the next level. Grab your coffee (or something stronger) and let’s dive in.

1. Pearl Lemon Crypto

Let’s start with a little self-love. Pearl Lemon Crypto isn’t just about crypto and token launches. We’ve been in the digital game for 9 years, and we specialize in providing enterprise-level blockchain solutions that ensure your business operates with transparency, security, and efficiency. Whether it’s integrating blockchain into your supply chain or creating decentralized apps (dApps), our team has the marketing, lead generation, and web development expertise to make your enterprise blockchain-friendly. Think of us as the "blockchain whisperers" for businesses—making sure you stay on the cutting edge without the headache.

2. IBM Blockchain

IBM has been around longer than most of your grandparents' tech, and they’re still here making blockchain look easy for enterprises. Their blockchain platform is designed for businesses across various industries, offering solutions for everything from supply chain tracking to financial transactions. If you need a firm that brings reliability, scalability, and enterprise-grade security to the table, IBM Blockchain is like the superhero your business deserves (minus the cape).

3. Accenture Blockchain

Accenture has been in the game long enough to know that blockchain isn’t just a trend—it’s the future. Their enterprise solutions focus on helping businesses harness the power of blockchain for everything from improving supply chains to enabling secure payments. Think of Accenture as your blockchain consultant, helping you unlock new efficiencies and opportunities while keeping everything compliant and secure. They might not have a magic wand, but they sure know how to make blockchain work wonders for large enterprises.

4. ConsenSys

ConsenSys is the company that’s bringing Ethereum to the enterprise world. Their suite of blockchain tools and solutions focuses on helping businesses leverage Ethereum for everything from decentralized finance (DeFi) to identity management. They make building enterprise-grade blockchain apps easier than ever—and just like that, you’ll have a full-fledged Ethereum-based enterprise system. If you want to ride the Ethereum wave (without the surfboard breaking), ConsenSys is your go-to team.

5. Blockchain Intelligence Group

Blockchain Intelligence Group focuses on providing enterprise-grade solutions that help businesses track and analyze blockchain transactions. Whether you’re a bank, government agency, or enterprise looking to get a handle on your digital assets, Blockchain Intelligence Group has the tech to help you stay compliant and secure. They're basically the "detectives" of the blockchain world, offering tools to monitor and investigate transactions. So, if you need to know what’s going on with your crypto but don’t want to hire a bunch of sleuths, these guys have your back.

6. R3

R3 is the creator of Corda, a distributed ledger platform specifically built for businesses. Their focus is on building blockchain solutions for enterprises in sectors like finance, insurance, and healthcare. With Corda, businesses can collaborate securely while ensuring compliance with industry regulations. Think of R3 as the sturdy bridge that connects enterprise needs with the power of blockchain, making sure you don’t fall off the compliance cliff.

7. Bitfury

Bitfury provides blockchain solutions with a special focus on enterprise blockchain, offering a variety of products to help businesses implement blockchain into their infrastructure. From mining to enterprise-grade blockchain software, they’re like the “Swiss Army knife” of blockchain solutions for businesses. They’re a great fit for enterprises looking to improve operations, create more efficient processes, or get into blockchain-based applications without diving too deep into the technical weeds.

8. Hewlett Packard Enterprise (HPE) Blockchain

Hewlett Packard, better known for their computers and printers, has jumped into the blockchain game with a full-force enterprise solution. HPE offers blockchain-as-a-service (BaaS), helping businesses streamline everything from logistics to financial transactions using blockchain. With a focus on scalability and high-performance computing, HPE is a great fit for enterprises looking to integrate blockchain into their existing infrastructure with minimal disruption. Who knew your printer could lead you to blockchain success?

9. Tata Consultancy Services (TCS)

Tata Consultancy Services (TCS) is a global leader in IT services and consulting, and their blockchain solutions are specifically designed for enterprises. Whether it’s securing payments, improving transparency, or automating processes, TCS offers a wide range of blockchain-based enterprise solutions. With their deep understanding of business needs and blockchain tech, TCS can help you build and scale blockchain applications that meet your specific requirements.

10. Chain.io

Chain.io specializes in building blockchain-powered integrations for the supply chain industry, helping businesses improve efficiency, traceability, and compliance. Their platform connects all the dots in your supply chain with seamless blockchain integration, allowing for better visibility and smoother operations. If you’re in logistics, supply chain management, or manufacturing, Chain.io can help you make your operations not just faster but more transparent—and who doesn’t want that?

There you have it—our list of the top 10 blockchain firms for enterprise solutions. These companies are making blockchain not just for the tech geeks and crypto enthusiasts but for serious businesses looking to innovate and stay ahead of the curve. Whether you're looking for a comprehensive blockchain strategy or just a specific tool to enhance your enterprise, these firms have got the right solution to make your business more secure, transparent, and efficient. Happy blockchain-ing! 🖥️🔗

[promptlyspeedyandroid]

DBMS Tutorial Explained: Concepts, Types, and Applications

In today’s digital world, data is everywhere — from social media posts and financial records to healthcare systems and e-commerce websites. But have you ever wondered how all that data is stored, organized, and managed? That’s where DBMS — or Database Management System — comes into play.

Whether you’re a student, software developer, aspiring data analyst, or just someone curious about how information is handled behind the scenes, this DBMS tutorial is your one-stop guide. We’ll explore the fundamental concepts, various types of DBMS, and real-world applications to help you understand how modern databases function.

What is a DBMS?

A Database Management System (DBMS) is software that enables users to store, retrieve, manipulate, and manage data efficiently. Think of it as an interface between the user and the database. Rather than interacting directly with raw data, users and applications communicate with the database through the DBMS.

For example, when you check your bank account balance through an app, it’s the DBMS that processes your request, fetches the relevant data, and sends it back to your screen — all in milliseconds.

Why Learn DBMS?

Understanding DBMS is crucial because:

It’s foundational to software development: Every application that deals with data — from mobile apps to enterprise systems — relies on some form of database.

It improves data accuracy and security: DBMS helps in organizing data logically while controlling access and maintaining integrity.

It’s highly relevant for careers in tech: Knowledge of DBMS is essential for roles in backend development, data analysis, database administration, and more.

Core Concepts of DBMS

Let’s break down some of the fundamental concepts that every beginner should understand when starting with DBMS.

1. Database

A database is an organized collection of related data. Instead of storing information in random files, a database stores data in structured formats like tables, making retrieval efficient and logical.

2. Data Models

Data models define how data is logically structured. The most common models include:

Hierarchical Model

Network Model

Relational Model

Object-Oriented Model

Among these, the Relational Model (used in systems like MySQL, PostgreSQL, and Oracle) is the most popular today.

3. Schemas and Tables

A schema defines the structure of a database — like a blueprint. It includes definitions of tables, columns, data types, and relationships between tables.

4. SQL (Structured Query Language)

SQL is the standard language used to communicate with relational DBMS. It allows users to perform operations like:

SELECT: Retrieve data

INSERT: Add new data

UPDATE: Modify existing data

DELETE: Remove data

5. Normalization

Normalization is the process of organizing data to reduce redundancy and improve integrity. It involves dividing a database into two or more related tables and defining relationships between them.

6. Transactions

A transaction is a sequence of operations performed as a single logical unit. Transactions in DBMS follow ACID properties — Atomicity, Consistency, Isolation, and Durability — ensuring reliable data processing even during failures.

Types of DBMS

DBMS can be categorized into several types based on how data is stored and accessed:

1. Hierarchical DBMS

Organizes data in a tree-like structure.

Each parent can have multiple children, but each child has only one parent.

Example: IBM’s IMS.

2. Network DBMS

Data is represented as records connected through links.

More flexible than hierarchical model; a child can have multiple parents.

Example: Integrated Data Store (IDS).

3. Relational DBMS (RDBMS)

Data is stored in tables (relations) with rows and columns.

Uses SQL for data manipulation.

Most widely used type today.

Examples: MySQL, PostgreSQL, Oracle, SQL Server.

4. Object-Oriented DBMS (OODBMS)

Data is stored in the form of objects, similar to object-oriented programming.

Supports complex data types and relationships.

Example: db4o, ObjectDB.

5. NoSQL DBMS

Designed for handling unstructured or semi-structured data.

Ideal for big data applications.

Types include document, key-value, column-family, and graph databases.

Examples: MongoDB, Cassandra, Redis, Neo4j.

Applications of DBMS

DBMS is used across nearly every industry. Here are some common applications:

1. Banking and Finance

Customer information, transaction records, and loan histories are stored and accessed through DBMS.

Ensures accuracy and fast processing.

2. Healthcare

Manages patient records, billing, prescriptions, and lab reports.

Enhances data privacy and improves coordination among departments.

3. E-commerce

Handles product catalogs, user accounts, order histories, and payment information.

Ensures real-time data updates and personalization.

4. Education

Maintains student information, attendance, grades, and scheduling.

Helps in online learning platforms and academic administration.

5. Telecommunications

Manages user profiles, billing systems, and call records.

Supports large-scale data processing and service reliability.

Final Thoughts

In this DBMS tutorial, we’ve broken down what a Database Management System is, why it’s important, and how it works. Understanding DBMS concepts like relational models, SQL, and normalization gives you the foundation to build and manage efficient, scalable databases.

As data continues to grow in volume and importance, the demand for professionals who understand database systems is also rising. Whether you're learning DBMS for academic purposes, career development, or project needs, mastering these fundamentals is the first step toward becoming data-savvy in today’s digital world.

Stay tuned for more tutorials, including hands-on SQL queries, advanced DBMS topics, and database design best practices!

[govindhtech]

Quantum Portfolio Optimizer: Global Data Quantum, IBM Qiskit

Portfolio optimisation for quantum computing

Global Data Quantum introduced the Quantum Portfolio Optimiser function in IBM Qiskit. Quantum computing optimises investment portfolios.

A detailed breakdown:

Quantum Portfolio Optimiser Goal

The Quantum Portfolio Optimiser optimises investment performance while reducing transaction costs and risks. Its dynamic portfolio optimisation goal is to find the optimum investment plan across many time periods to maximise projected return and minimise risks, often while considering budget, transaction costs, and risk aversion. Dynamic portfolio optimisation modifies assets based on asset performance, unlike traditional portfolio optimisation, which uses a single rebalancing time. The program targets analysts, investors, and portfolio managers. Portfolio optimisation allows backtesting trading approaches.

Quantum Portfolio Optimiser Access:

Discover the function in IBM Qiskit Functions Catalogue. This experimental functionality is only available to IBM Quantum Premium and Flex Plan users in preview release. Request a catalogue to access Global Data Quantum.

Quantum Computing—Why?

Traditional methods become slow and inefficient as resources or limits increase. Quantum computing's capacity to analyse several variables in parallel can solve complex problems faster and more efficiently than classical solvers like CPLEX, Gurobi, and Pyscf on HPC resources.

Quantum Portfolio Optimiser Functions?

The Quantum Portfolio Optimiser has four steps:

It receives financial asset values and user-specified investing conditions.

Quantum circuits convert classical input data into a quantum-resolution problem. This requires constructing the dynamic portfolio optimisation problem using Quadratic Unconstrained Binary optimisation (QUBO) and converting it into a quantum operator (Ising Hamiltonian).

The Variational Quantum Eigensolver (VQE) algorithm is considered. The VQE was designed to determine the optimal solution-wide investment combinations. In this hybrid quantum-classical approach, the quantum circuit estimates the cost function and Differential Evolution is used for classical optimisation.

Adjusting post-processing to eliminate quantum device noise yields an optimal, trustworthy, and realistic recommendation. For optimal output, the system uses noise-aware (SQD-based) post-processing.

Formulating Problems

Portfolio optimisation uses multi-objective Quadratic Unconstrained Binary Optimisation (QUBO). The QUBO function optimises four goals:

Max out the return function (F).

Reduce investment risk (R) and transaction costs.

Respect investment limits. The QUBO function is defined as O = -F + (γ/2)R + C + ρP, where γ is the risk aversion coefficient and ρ is the constraints reinforcement coefficient (Lagrange multiplier The minimum qubit count for a problem is the number of assets (na), time periods (nt), and bit resolution (nq) used to describe the investment.

Input

This function requires several input parameters:

A dictionary of asset prices uses dates as supplementary keys. All assets must have consistent data for the same dates.

Qubo_settings: A dictionary that configures the QUBO problem with parameters like nq resolution qubits, dt time window each step, maximum investment per asset, risk aversion coefficient, transaction charge, and restriction coefficient.

Optimizer_settings (Optional): Sets up the standard optimisation technique, including primitive settings (sampler_shots, estimator_shots) and differentiation_evolution algorithm parameters (num_generations, population_size).

ansatz_settings (Optional): Select “optimized_real_amplitudes” or “tailored” and enable multiple pass managers, dynamical decoupling, and other options to configure the quantum circuit ansatz.

Optional: QPU backend name, such as “ibm_torino.”

previous_session_id (Optional): A list of past session IDs to continue execution or retrieve data.

Apply_postprocess (Optional): True applies noise-aware SQD post-processing.

tags: An optional text list to label the experiment.

Output

Function returns two dictionaries: “result” and “metadata”.

Result: optimal optimisation outcomes, such as the optimal investment strategy over time and the lowest target cost. Investment weights are normalised by total investment.

Metadata: Metadata describes all optimisation results. It includes counts, investment pathways, objective costs, Sharpe ratios, returns, limitation violations, samples/states, and transaction costs. The session ID, asset order, QUBO matrix, and resource consumption summary are all included. Return, Sharpe ratio, restriction deviation, and least objective cost are key metadata for the best solution.

Application Function Context Qiskit

Application functions like the Quantum Portfolio Optimiser provide a comprehensive quantum pipeline by abstracting the quantum workflow. Because quantum methods use conventional classical inputs and return domain-familiar classical outputs, they can be easily integrated into present application processes without quantum computing knowledge.

Analysis of Performance and Benchmarks

The function is verified using different resolution qubit, ansatz circuit, and asset grouping configurations. Benchmarks evaluate solutions using two metrics:

Objective cost: To evaluate optimisation, the objective cost compares the cost function value to Gurobi (free version) output.

Sharpe ratio: Measures portfolio risk-adjusted return. Benchmark data shows the quantum optimiser finds viable investment plans. For a test using IBEX35 assets (Set 3, 4 time steps, 2-bit encoding, 56 qubits), the Optimised Real Amplitudes ansatz had an objective cost of -3.67 and a Sharpe ratio of 14.48, while Gurobi had 16.44 and -4.11. Comparing quantum sampling to random sampling, visual inspection shows that lower prices dominate the distribution.

[predictiveanalytics]

Understanding SAP: The Backbone of Modern Business Operations

In today’s fast-paced business world, companies rely heavily on digital systems to streamline operations, manage data, and boost productivity. One such powerful tool is SAP – a globally recognized ERP (Enterprise Resource Planning) software that has revolutionized how organizations function. This blog explores what SAP is, why it’s essential, and how it drives modern business operations.

 What is SAP?

·         SAP stands for Systems, Applications, and Products in Data Processing.

·         It was founded in 1972 in Germany by former IBM engineers.

·         SAP provides integrated business solutions that manage everything from finance to supply chain, HR, and customer relations.

·         Its core product is SAP ERP, now evolved into SAP S/4HANA.

SAP helps businesses run efficiently, make informed decisions, and stay competitive in a global market.

 Why Businesses Use SAP

SAP is preferred because it:

·         Centralizes data across departments

·         Automates routine processes

·         Reduces manual errors

·         Improves reporting and decision-making

·         Ensures regulatory compliance

Key Benefits:

·         Real-time data processing

·         Enhanced productivity

·         Reduced operational costs

·         Better customer satisfaction

·         Scalable solutions for small to enterprise-level businesses

 Core SAP Modules That Support Business Operations

SAP’s strength lies in its modular structure. Each module is tailored to a specific business function.

 1. SAP FI (Financial Accounting)

·         Handles financial transactions

·         Generates balance sheets, P&L statements

·         Used by accounting teams for budgeting and audits

 2. SAP CO (Controlling)

·         Monitors internal costs

·         Supports planning and performance tracking

·         Used by finance controllers and project managers

3. SAP MM (Material Management)

·         Manages procurement and inventory

·         Tracks vendor performance and purchase orders

·         Supports supply chain efficiency

4. SAP PP (Production Planning)

·         Plans manufacturing and production processes

·         Ensures product availability with accurate scheduling

 5. SAP HCM (Human Capital Management)

·         Manages employee records, payroll, hiring, and performance

·         Enables self-service portals for HR tasks

6. SAP SD (Sales and Distribution)

·         Manages sales orders, delivery, and billing

·         Tracks customer interactions and product movement

How SAP Works Within an Organization

Step-by-step function:

·         Data is entered once and used across all departments.

·         Processes are automated to save time and resources.

·         Reports are generated in real-time to aid decision-making.

·         Employees collaborate more effectively using a single platform.

 Example: When a sales order is placed, SAP automatically updates inventory, triggers invoicing, and reflects changes in financial records—without manual input.

Industries Where SAP is Widely Used

SAP is not limited to one type of business. It supports various sectors:

·         Manufacturing – for production planning and logistics

·         Retail – for supply chain and inventory management

·         Healthcare – for patient records and hospital resource management

·         Banking – for financial transactions and compliance

·         Energy – for asset management and billing

·         IT Services – for project management and resource planning

"SAP has become the digital core for many Fortune 500 companies."

The Evolution: From SAP R/3 to SAP S/4HANA

·         SAP R/3 was the classic ERP system with on-premise servers.

·         Now, SAP S/4HANA is cloud-compatible, faster, and more user-friendly.

·         Powered by in-memory computing, S/4HANA processes large volumes of data in seconds.

·         It supports AI, machine learning, and predictive analytics for smarter business decisions.

 Advantages of Using SAP in Modern Business

 Strategic Advantages:

·         End-to-end integration of all departments

·         Real-time data analysis for fast decision-making

·         Customizable modules for specific business needs

·         Compliance-ready reports for audits and legal requirements

Operational Benefits:

·         Improved communication between teams

·         Reduced duplication of efforts

·         Streamlined workflows

·         Easy scalability as the business grows

 Careers and Opportunities in SAP

The demand for SAP professionals is constantly rising.

In-demand Roles:

·         SAP Functional Consultant (FI, MM, SD, etc.)

·         SAP Technical Consultant (ABAP Developer)

·         SAP Basis Administrator

·         SAP Project Manager

·         SAP S/4HANA Specialist

 SAP certifications increase job opportunities and salary potential globally.

 Challenges Businesses May Face

While SAP offers many benefits, some challenges may arise:

·         High initial implementation cost

·         Complex learning curve

·         Need for regular updates and maintenance

·         Dependency on trained professionals

However, with proper planning and training, these challenges can be overcome.

 Conclusion: Why SAP is the Backbone of Modern Business

SAP isn’t just a tool—it’s a strategic platform that empowers businesses to scale, adapt, and thrive in a competitive digital world.

With real-time data, automated processes, and deep integration across departments, SAP serves as the backbone of modern business operations.

Whether you're a business owner or a student looking to step into the world of enterprise tech, understanding SAP is a valuable asset in today's digital economy. For those aiming to build practical, job-ready skills, enrolling in an SAP Training Course in Noida, Delhi, Gurgaon, Bangalore, Mumbai, Hyderabad, Pune, Chennai, can offer hands-on experience and exposure to real-world business scenarios. These cities are known for their growing IT and business hubs, making them ideal locations to pursue SAP learning and career opportunities.

[sunalimerchant]

Top 10 Real-World Blockchain Use Cases Transforming Industries Today

Once viewed primarily as the foundation of cryptocurrencies like Bitcoin, blockchain technology has evolved into a transformative force across multiple industries. Its decentralized, transparent, and tamper-proof nature offers revolutionary possibilities in areas far beyond finance. From enhancing supply chain efficiency to securing digital identities, blockchain is reshaping the way businesses operate and people interact.

Here are the top 10 real-world blockchain use cases that are currently making a significant impact across sectors:

1. Supply Chain Transparency

Blockchain allows stakeholders to track products at every stage of the supply chain—from origin to end user. This is especially valuable in food, pharmaceuticals, and luxury goods, where verifying authenticity and preventing fraud are critical. Companies like IBM and Maersk use blockchain to improve visibility and reduce paperwork in global shipping.

2. Digital Identity Verification

With rising concerns over data breaches and identity theft, blockchain offers a secure solution through decentralized digital identities. Users control their identity data, which can be verified without relying on centralized databases. Governments and tech firms are exploring blockchain for digital passports, KYC processes, and secure login systems.

3. Smart Contracts in Legal and Finance

Smart contracts are self-executing agreements with conditions written into code. They reduce the need for intermediaries, lower transaction costs, and ensure trust. In real estate, they automate property transfers; in insurance, they streamline claims processing. Platforms like Ethereum have popularized smart contract development across industries.

4. Cross-Border Payments

Traditional cross-border transactions are slow and expensive. Blockchain-based payment networks like Ripple and Stellar offer real-time, low-fee international money transfers. These solutions are increasingly adopted by banks and fintech firms to enhance financial inclusion and remittance services.

5. Healthcare Data Management

In healthcare, patient records are fragmented across providers and systems. Blockchain enables secure, unified, and interoperable medical records accessible only to authorized parties. It also helps in drug traceability to combat counterfeit medicines, a major issue in global health.

6. Voting and Elections

Blockchain offers a tamper-proof solution for digital voting, increasing transparency and reducing fraud. Each vote is recorded as a block in the chain, ensuring traceability and auditability. Countries and municipalities are testing blockchain-based voting systems to increase trust and participation.

7. Intellectual Property and Royalties

For content creators, blockchain simplifies IP registration and ensures fair royalty distribution. Musicians, authors, and artists can track usage of their work and receive payments via smart contracts. Platforms like Audius and Ujo Music use blockchain to empower creators.

8. Real Estate Tokenization

Blockchain allows tokenization of real estate assets, making property investments more accessible. Instead of buying a whole property, investors can purchase tokens representing a share. This increases liquidity in the traditionally illiquid real estate market and lowers entry barriers for smaller investors.

9. Energy Trading

Peer-to-peer energy trading using blockchain enables individuals to buy and sell renewable energy directly. Smart grids integrated with blockchain ensure transparent transactions and reduce dependency on large utilities. This model promotes decentralized, clean energy distribution.

10. Charity and Donation Tracking

Blockchain enhances transparency in charitable giving by allowing donors to trace how their funds are used. Smart contracts can ensure that donations are released only when certain milestones are met, building trust in nonprofit organizations and increasing donor engagement.

Conclusion

Blockchain is no longer a buzzword—it’s a powerful technology being actively used to solve real-world problems. These ten use cases demonstrate how blockchain’s unique features—decentralization, transparency, immutability, and automation—are being applied across industries to increase efficiency, reduce fraud, and empower users.

As adoption continues to grow, blockchain is poised to become a backbone of digital transformation globally. Whether you're a business leader, developer, or investor, now is the time to explore how this technology can reshape your industry.

[mysublimedestiny]

Blockchain Security Market: Key Drivers Fueling Growth, Innovation, and Adoption Across Global Industries and Sectors

Blockchain Security Market Drivers

The global blockchain security market is witnessing significant growth, propelled by several key factors that highlight the critical need for secure digital infrastructures. As blockchain technology becomes increasingly integrated across industries, understanding the core drivers of this market is essential for stakeholders, investors, and decision-makers.

1. Escalating Cybersecurity Threats

One of the primary drivers of the blockchain security market is the rising number of cyberattacks targeting blockchain platforms. As digital assets and decentralized applications grow in popularity, they have become lucrative targets for cybercriminals. In recent years, billions of dollars have been lost to crypto hacks, demonstrating the vulnerabilities that exist within blockchain ecosystems. These incidents have led to a greater emphasis on adopting comprehensive security solutions that protect both infrastructure and user assets.

2. Proliferation of Decentralized Finance (DeFi)

The explosive growth of decentralized finance (DeFi) platforms has introduced new challenges in security management. Unlike traditional financial systems, DeFi platforms operate without centralized oversight, making them particularly vulnerable to bugs, coding flaws, and malicious exploits. As users increasingly turn to DeFi for loans, trading, and yield farming, the need for robust, smart contract auditing and other blockchain security measures becomes more pressing.

3. Integration Across Diverse Industries

Blockchain is no longer confined to cryptocurrency or financial services. Industries such as healthcare, supply chain management, real estate, and government services are integrating blockchain to enhance data security, transparency, and operational efficiency. For instance, healthcare institutions are using blockchain to safeguard patient data and streamline record sharing. This widespread adoption increases the demand for sector-specific security solutions to address unique regulatory and operational needs.

4. Regulatory Developments and Compliance

Governments and regulatory bodies across the globe are recognizing the potential and risks of blockchain technology. As a result, there has been a surge in regulatory initiatives aimed at standardizing security practices. For example, financial regulators are requiring blockchain-based platforms to implement rigorous know-your-customer (KYC) and anti-money laundering (AML) procedures. These regulatory pressures are driving enterprises to adopt compliant, secure blockchain infrastructure and services.

5. Technological Innovations Enhancing Security

Technological advancements such as zero-knowledge proofs (ZKPs), homomorphic encryption, and artificial intelligence are enhancing blockchain security. ZKPs, for example, allow verification of transactions without revealing sensitive data, supporting privacy without compromising transparency. Meanwhile, AI and machine learning are increasingly being used for real-time threat detection and predictive analytics, helping blockchain networks proactively guard against breaches.

6. Strategic Collaborations and Investments

The blockchain security market is also benefiting from increasing investments and strategic collaborations among major technology firms. Industry leaders like IBM, Microsoft, and Oracle are investing in secure blockchain platforms and partnering with cybersecurity firms to develop integrated solutions. These partnerships facilitate innovation and ensure that enterprise blockchain deployments come equipped with state-of-the-art security features.

7. Growing Demand for Secure Digital Transactions

As businesses and consumers transition to digital platforms for commerce, communication, and recordkeeping, there is a rising demand for secure digital transaction systems. Blockchain's decentralized nature, immutability, and transparency make it an ideal candidate for securing digital assets and transactions. Organizations are increasingly leveraging blockchain to protect against fraud and ensure the integrity of business operations, which in turn is boosting the demand for enhanced security frameworks.

8. Emphasis on Privacy and Data Protection

Data privacy is becoming a central concern across the globe, especially in light of increasing data breaches and the tightening of data protection regulations such as the General Data Protection Regulation (GDPR). Blockchain security solutions that offer fine-grained access controls, encryption, and anonymization help meet these privacy requirements. The emphasis on protecting sensitive personal and corporate data is pushing companies to seek out more secure blockchain implementations.

9. Emergence of Post-Quantum Cryptography

The rapid development of quantum computing presents a new kind of threat to existing encryption standards, including those used in blockchain networks. In response, the market is exploring post-quantum cryptographic algorithms that can resist quantum attacks. Proactive efforts to adopt these next-generation security protocols are anticipated to drive market demand and future-proof blockchain systems.

10. Regional Market Dynamics

Different regions are contributing uniquely to the growth of the blockchain security market. North America leads due to its early adoption and a well-developed technology ecosystem. Europe follows closely, driven by strong data protection regulations and innovation in financial services. In the Asia-Pacific region, countries like China, Japan, and India are experiencing rapid adoption of blockchain across various sectors, further stimulating the need for advanced security solutions.

Conclusion

The blockchain security market is poised for continued expansion, fueled by a convergence of factors including increasing cyber threats, regulatory pressure, cross-industry adoption, and cutting-edge technology. As blockchain becomes a foundational technology for the digital economy, the imperative for secure, scalable, and compliant solutions will only grow stronger. Stakeholders who prioritize security as a core element of their blockchain strategy will be best positioned to capitalize on the opportunities in this evolving landscape.

[cybersecurityict]

Data Brokers Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: Digital Ecosystems Fuel Unprecedented Growth

The Data Brokers Market Size was valued at USD 257.2 Billion in 2023. It is expected to grow to USD 441.4 Billion by 2032 and grow at a CAGR of 7.4% over the forecast period of 2024-2032.

The Data Brokers Market is witnessing significant traction as organizations across industries prioritize data-driven strategies. With an ever-expanding digital footprint, data brokers play a pivotal role in aggregating, analyzing, and selling consumer data to enhance business intelligence and marketing precision. Enterprises rely on these brokers to segment audiences, personalize campaigns, and optimize customer engagement, fueling market expansion.

Data Brokers Market Fueled by the proliferation of connected devices, digital transactions, and social media platforms, the demand for real-time consumer data is reshaping the business landscape. The data brokers industry is evolving with innovative data monetization models, advanced analytics, and compliance-driven solutions that ensure ethical and legal data handling practices.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3873 

Market Keyplayers:

Oracle (Oracle Data Cloud, Oracle Big Data Appliance)

Thomson Reuters (Eikon, DataScope)

Equifax, Inc. (Equifax Workforce Solutions, Credit Report Services)

CoreLogic (Property Data, Flood Risk Services)

TransUnion LLC (CreditVision, TrueRisk)

ID Analytics, LLC (ID Network, ID Score)

Acxiom LLC (Acxiom Data Solutions, Audience Solutions)

IBM (IBM Watson, IBM Cloud Pak for Data)

Ignite Technologies (Ignite CRM, Ignite ERP)

Epsilon Data Management, LLC (Epsilon Email, Epsilon Data Solutions)

Alibaba (Alibaba Cloud, Alipay)

TowerData Inc. (Email Validation, Data Enrichment)

Intelius, Inc. (People Search, Background Check)

Experian (Experian Credit Report, Business Credit Services)

LexisNexis (LexisNexis Risk Solutions, LexisNexis Data Exchange)

SAP (SAP Analytics Cloud, SAP Data Hub)

Nielsen (Nielsen Media Impact, Nielsen Digital Ad Ratings)

Fair Isaac Corporation (FICO) (FICO Score, FICO Analytics)

Microsoft (Azure Data Services, Power BI)

Market Analysis

The data brokers market operates at the intersection of technology, privacy, and commerce. Vendors collect data from public sources, online activity, surveys, and third-party apps, processing it into actionable intelligence. This market includes players specializing in credit information, demographic data, psychographics, and behavioral trends. Enterprises in retail, finance, healthcare, and advertising leverage these insights to refine customer experiences and outpace competition.

The landscape is increasingly regulated, with governments enforcing stricter policies on data collection, storage, and usage. Compliance with frameworks like GDPR, CCPA, and similar data privacy laws is shaping operational strategies. Companies that align with regulatory standards while delivering high-quality, anonymized data are gaining market trust and competitive edge.

Market Trends

Increasing demand for personalized marketing and customer profiling

Shift toward ethically sourced and privacy-compliant data sets

Integration of AI and machine learning in data analysis

Growing influence of data transparency and user consent mechanisms

Rising adoption of cloud-based platforms for scalable data management

Strategic partnerships between data brokers and analytics firms

Emergence of blockchain for secure data exchange

Market Scope

A Dynamic Ecosystem Enabling Precision at Scale

Serving industries from retail to financial services and public policy

Supporting B2B and B2C segmentation strategies

Enabling hyper-targeted advertising and predictive modeling

Driving operational efficiency through real-time insights

Facilitating new revenue streams through data monetization

The scope of the data brokers market continues to broaden, with the digitization of services across sectors. As companies seek granular, behavior-based insights to differentiate themselves, data brokers are becoming indispensable enablers of competitive advantage. The market's reach now spans SMBs and large enterprises alike, democratizing access to strategic data assets.

Market Forecast

The future of the data brokers market is anchored in innovation, compliance, and integration. As enterprises increasingly demand contextual and predictive analytics, the market is expected to evolve through smarter algorithms, ethical data sourcing, and intelligent automation. Strategic investments in privacy-enhancing technologies and AI-driven platforms are set to elevate the quality and accuracy of brokered data. With digital transformation accelerating across regions, data brokers will become central to unlocking new growth avenues and driving customer-centric strategies.

Access Complete Report: https://www.snsinsider.com/reports/data-brokers-market-3873 

Conclusion

As data becomes the new oil, the data brokers market is refining the way businesses extract value from vast digital trails. The sector is not only a cornerstone of modern marketing and analytics but also a key player in shaping the future of privacy and personalization. Stakeholders who embrace innovation while respecting consumer rights will lead the next era of data intelligence. The market’s momentum signals more than growth—it’s a transformation in how insights power action.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[thabisonjoko]

Understanding the Four Types of Blockchains

Public, Private, Consortium & Hybrid — Which One Powers What?

Blockchain technology isn’t one-size-fits-all. As the technology evolves, we’re seeing different flavors of blockchain emerge — each tailored to specific use cases and governance models. In Episode 4 of Unpacking Blockchain Technology with Thabiso Njoko, we break down the four main types of blockchains and explain how each one functions in the real world.

If you’ve ever wondered why some blockchains are open and others are gated, this episode is your gateway to clarity.

The Four Main Types of Blockchains

Whether you're launching a cryptocurrency, managing a supply chain, or modernizing government services, choosing the right type of blockchain is critical. Here's how they compare:

1. Public Blockchains

These are fully decentralized and open to anyone. Anyone can read, write, or participate in the network. Popular examples include Bitcoin, Ethereum, and Solana.

Features:

Open-source

Transparent and secure

Powered by consensus mechanisms like Proof of Work (PoW) or Proof of Stake (PoS)

Use Cases:

Cryptocurrencies

NFTs

Decentralized Finance (DeFi)

Open-access Web3 applications

“Public blockchains are the backbone of the trustless Web3 world,” says Thabiso.

2. Private Blockchains

These are permissioned systems controlled by a single organization. Only selected participants can access the network or validate transactions.

Features:

High speed and scalability

Restricted access

Centralized authority and governance

Use Cases:

Internal business operations

Financial institutions

Healthcare data management

Think of private blockchains as enterprise-grade solutions for data security and control.

3. Consortium Blockchains

Also known as federated blockchains, these are governed by a group of organizations rather than a single entity. Each participant in the consortium has certain rights.

Features:

Semi-decentralized

Shared control among participants

Collaborative governance

Use Cases:

Supply chain tracking

Trade finance between banks

Joint ventures between corporations

 These are ideal for industries that rely on shared infrastructure but don’t want to go fully public.

4. Hybrid Blockchains

As the name suggests, hybrid blockchains combine features of both public and private systems. This offers flexibility—you can keep some data public while keeping sensitive data private.

Features:

Controlled access + transparency

Combines the best of both worlds

Complex but powerful

Use Cases:

Government records (public data + confidential citizen info)

Healthcare systems (open research + private patient data)

Real estate platforms

 Hybrid blockchains are perfect when trust, control, and openness need to co-exist.

How Do You Choose the Right One?

Thabiso emphasizes that context determines the blockchain. Ask:

Who needs access?

Who verifies the data?

How sensitive is the information?

What are the trust assumptions?

Each blockchain type serves a purpose. The key is understanding your goals before choosing the structure.

Real-World Examples

A public blockchain like Ethereum is widely used for DeFi and NFTs, while a private blockchain such as Hyperledger Fabric powers IBM's supply chain solutions. In the banking and finance sector, a consortium blockchain like R3 Corda is commonly used. Meanwhile, XinFin (XDC) serves as a hybrid blockchain, particularly effective in trade finance applications.

Final Thoughts from Thabiso

“Not every blockchain has to be open to the world. Some need privacy, speed, and control. But understanding why each model exists helps us build smarter systems.”

As blockchain adoption grows, knowing the differences between these models will shape how we design solutions, collaborate with others, and build trust across systems.

Tune In Now

Catch Episode 4 of Unpacking Blockchain Technology with Thabiso Njoko to hear the full breakdown and use-case comparisons.

Join the Discussion

Which blockchain type best fits your project or organization? Share your thoughts or questions in the comments — let’s unpack it together.

[infograins]

How to Choose the Right Blockchain Platform: Ethereum vs. Solana vs. Hyperledger

 In today's rapidly evolving tech landscape, blockchain is no longer a buzzword. It's a powerful technology shaping the future of finance, supply chain, healthcare, gaming, and beyond. However, selecting the right blockchain platform is critical to your project's success. Ethereum, Solana, and Hyperledger are three widely used platforms, each offering unique strengths tailored to different business needs.

At Infograins, one of the leading blockchain development company in India, we guide businesses across industries in choosing and building on the ideal platform. This blog offers a deep dive into these platforms to help you decide which one best suits your use case.

1. Ethereum: The Smart Contract Pioneer

Overview: Ethereum is the most established public blockchain platform, known for introducing smart contracts and decentralized applications (dApps). It enables developers to create tokenized assets and applications that run on a decentralized network.

Key Features:

Decentralized and open-source

Supports ERC-20, ERC-721 (NFTs), and other token standards

Active developer community and strong documentation

Transitioned to Ethereum 2.0 for improved scalability (Proof of Stake)

Use Cases:

Decentralized Finance (DeFi)

Non-Fungible Tokens (NFTs)

dApps and DAOs

Blockchain-based gaming

Pros:

Highly secure and battle-tested

Rich ecosystem of tools and integrations

Extensive learning resources and community support

Cons:

Slower transaction speeds compared to newer platforms

High gas fees (mitigated with Layer 2 solutions like Polygon)

2. Solana: High-Speed & Scalable

Overview: Solana is known for its speed and low transaction fees. It's designed to support high-performance applications and is gaining popularity in gaming, NFTs, and DeFi spaces. Solana uses a combination of Proof of History (PoH) and Proof of Stake (PoS) to achieve its performance.

Key Features:

Handles up to 65,000 transactions per second

Sub-second block finality

Low gas fees

Developer-friendly SDKs and documentation

Use Cases:

Real-time DeFi platforms

NFT marketplaces

Scalable games and metaverse applications

Payment networks

Pros:

Fast and efficient

Ideal for high-throughput dApps

Rapidly growing ecosystem and developer interest

Cons:

Network outages have occurred in the past

Slightly more centralized compared to Ethereum

3. Hyperledger: Enterprise-Grade Blockchain

Overview: Hyperledger is an open-source collaborative project by The Linux Foundation that focuses on enterprise blockchain solutions. Unlike Ethereum and Solana, Hyperledger is permissioned, meaning only authorized participants can access the network.

Key Features:

Modular architecture (supports multiple frameworks like Fabric, Sawtooth)

Private and permissioned blockchain

High performance and scalability

Supports private transactions and data confidentiality

Use Cases:

Supply chain management

Healthcare data exchange

Financial services and interbank settlements

Identity management systems

Pros:

Tailored for enterprise-level requirements

Flexible and customizable for specific needs

Strong backing by industry leaders (IBM, Intel, etc.)

Cons:

Smaller developer ecosystem

Not suitable for public dApps or token launches

How to Choose the Right Platform

Choosing the right blockchain depends on several key factors:

Project Type:

For public applications like DeFi or NFT platforms, Ethereum or Solana is ideal.

For internal enterprise solutions, Hyperledger offers privacy and control.

Performance Needs:

Choose Solana for speed and real-time performance.

Ethereum is better for security-focused applications.

Ecosystem & Community:

Ethereum has the largest developer base.

Solana is growing fast with new tools.

Hyperledger offers strong enterprise-level support.

Cost & Scalability:

Solana provides low-cost operations.

Ethereum costs are higher but come with robust tools.

Data Privacy:

Hyperledger is the best option when data control and confidentiality are a priority.

Why Infograins?

As a trusted Blockchain Development Company in India, Infograins offers:

Deep expertise in Ethereum, Solana, Hyperledger, and more

Custom blockchain solutions tailored to your business

Smart contract development and audit

NFT, DeFi, and enterprise blockchain consulting

24/7 support and agile development methodology

We don’t just build blockchain apps—we build secure, scalable, and future-ready ecosystems.

Conclusion

There is no "one-size-fits-all" blockchain platform. The best choice depends on your business goals, scalability needs, privacy requirements, and user base. Whether you're a startup or an enterprise, choosing the right platform is the first step toward blockchain success.

Let Infograins help you make the right move in your blockchain journey.

[acomsoftware]

Advanced Payment Management Features for IBM i System i AS/400

ACOM Systems’ Payment Management for IBM i System i AS/400 allows you to optimize payment processing through a single platform for both electronic ACH and physical payments. Protect your financial transactions with advanced features like Positive Pay, multi-level approval security, and proactive fraud monitoring. 

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How AI Development is Revolutionizing Industries Across the Globe?

Artificial Intelligence (AI) has emerged as one of the most transformative forces across industries worldwide. As technology advances, AI is no longer confined to theoretical concepts or niche applications; it is now embedded in the core of everyday business operations. From automating tedious tasks to enhancing decision-making and improving customer experiences, AI development is reshaping industries at an unprecedented rate. Let’s explore how AI is revolutionizing sectors such as healthcare, finance, manufacturing, and more.

1. AI in Healthcare: Enhancing Patient Care and Efficiency

The healthcare industry has seen significant advancements due to AI, ranging from diagnosis to treatment and patient care. AI algorithms are increasingly being used to analyze medical images, identify potential health risks, and predict disease outbreaks. Tools powered by AI, like IBM Watson, can assist in diagnosing conditions such as cancer, aiding doctors in making faster, more accurate decisions.

Additionally, AI is playing a critical role in drug development and clinical trials. Machine learning models can analyze vast amounts of medical data to predict how patients will respond to specific treatments, helping to accelerate the development of new drugs. Personalized medicine is becoming more feasible, offering tailored treatment plans that enhance outcomes and reduce costs.

2. AI in Finance: Transforming Banking and Investment

In the financial sector, AI is helping businesses enhance customer service, improve security, and streamline operations. AI-driven chatbots and virtual assistants are handling customer queries, allowing financial institutions to provide 24/7 service and reduce human labor costs. These AI tools can also predict market trends, helping investors make informed decisions in real-time.

Moreover, AI is transforming risk management and fraud detection. With machine learning algorithms capable of detecting suspicious transactions, banks and financial institutions can safeguard their operations against fraud more effectively. AI-powered systems analyze historical data to spot anomalies and potential security threats before they escalate, ensuring greater protection for both businesses and their clients.

3. AI in Manufacturing: Boosting Productivity and Innovation

Manufacturers worldwide are adopting AI to increase operational efficiency, minimize downtime, and enhance product quality. AI-driven robotics and automation have revolutionized factory floors, reducing the need for manual labor and enabling faster production cycles. Machine learning models can predict equipment failures and recommend preventative maintenance, minimizing costly disruptions.

AI also plays a pivotal role in supply chain optimization. By analyzing data from suppliers, logistics, and customers, AI can predict demand, optimize routes, and ensure inventory levels are maintained, which helps reduce costs and improve service delivery.

4. AI in Retail: Enhancing Customer Experience and Personalization

Retailers are increasingly turning to AI to enhance customer experiences and optimize operations. AI algorithms can analyze consumer behavior, predict shopping preferences, and recommend products in real-time. Personalized shopping experiences, powered by AI, are no longer a luxury but an expectation for many consumers. AI helps retailers offer individualized recommendations, discounts, and marketing messages tailored to each shopper.

Additionally, AI-powered inventory management systems are helping retailers optimize stock levels and reduce waste. These systems can predict when products will be in demand and adjust stock accordingly, ensuring products are available when customers need them without overstocking.

5. AI in Education: Personalizing Learning Experiences

Education is another sector experiencing a massive transformation due to AI. AI-powered tools are being used to personalize learning experiences, providing students with tailored curricula that adjust in real-time based on their progress and areas of difficulty. Smart tutoring systems are helping students by offering additional support and feedback, enabling educators to focus on individual needs.

AI is also streamlining administrative tasks in educational institutions, automating grading systems and handling scheduling conflicts, freeing up time for teachers to focus on more impactful teaching.

6. AI in Transportation: Revolutionizing Mobility and Logistics

The transportation industry has been dramatically impacted by AI, particularly in the realm of autonomous vehicles and logistics. Self-driving cars, trucks, and drones are reshaping the way goods and people are transported, promising to reduce traffic congestion, lower emissions, and improve safety.

AI is also enhancing logistics and supply chain management. Predictive analytics allow companies to optimize delivery routes, reducing fuel consumption and improving delivery times. Real-time tracking and route optimization are helping logistics firms better manage inventory and reduce operational costs.

7. AI in Agriculture: Improving Crop Yields and Sustainability

AI is increasingly being used in agriculture to boost productivity and promote sustainable practices. Precision farming, driven by AI, allows farmers to optimize irrigation, monitor crop health, and predict harvest yields. By analyzing environmental data, AI helps farmers make informed decisions about when and how to plant, water, and harvest crops, leading to more efficient use of resources.

AI-driven technologies, like drones and sensors, are also used to monitor soil conditions and detect pests, enabling early interventions that reduce the need for pesticides and fertilizers, ultimately making agriculture more sustainable.

Conclusion: AI’s Global Impact

As AI continues to develop, its applications will only grow deeper and broader across industries. Its ability to automate tasks, analyze vast amounts of data, and make real-time decisions makes it an invaluable tool for businesses looking to stay competitive in an increasingly digital world. AI’s potential to innovate, streamline processes, and solve complex problems is transforming the global business landscape, leading to greater efficiency, personalization, and sustainability.

The future of AI holds limitless possibilities, and businesses that embrace this technology will undoubtedly be at the forefront of the next wave of industrial revolution. Whether in healthcare, finance, manufacturing, or beyond, AI is unlocking new opportunities, solving complex challenges, and creating a smarter, more efficient world.