#Big data analytics consulting

[capitalism-and-analytics]

For anyone currently in school or recently in school

I am doing a few guest lectures at some of the universities in my state and working on my presentation. Curious if anyone has any recommendations of topics they really enjoyed from a past guest speaker that isn't major/field-specific?

[collabsoftech]

Data Analytics Services to Unlock Business Insights | Collab Softech

Make smarter decisions with advanced Data Analytics solutions from Collab Softech. We help businesses harness the power of data through real-time dashboards, custom reporting, predictive analytics, and business intelligence tools. Our data experts turn raw data into actionable insights that improve performance, optimize strategy, and drive growth. Partner with us today to transform your data into a powerful business asset.

[nexit365]

Big Data Consulting & Analytics Services in Dubai | Premier Globe Equipment Trading LLC

Premier Globe Equipment Trading LLC offers expert Big Data consulting and analytics services in Dubai, helping businesses turn complex data into valuable insights. Our team provides end-to-end services, from data strategy and implementation to advanced analytics and reporting, ensuring your business can make informed, data-driven decisions. We specialize in delivering tailored solutions that optimize operations and improve business performance. Ready to unlock the potential of your data? Visit our official website today and discover how our Big Data consulting services can elevate your business in Dubai!

[jcmarchi]

DJ Fang, Co-Founder & Chief Operating Officer at Pure Global – Interview Series

New Post has been published on https://thedigitalinsider.com/dj-fang-co-founder-chief-operating-officer-at-pure-global-interview-series/

DJ Fang, Co-Founder & Chief Operating Officer at Pure Global – Interview Series

DJ Fang is a technology executive and entrepreneur with over 15 years of experience driving digital transformation and innovation across industries, including finance, energy, and healthcare. He has led initiatives for Fortune 500 companies and government agencies, combining business expertise with technical skills in AI, cybersecurity, and cloud infrastructure.

As a serial entrepreneur, Fang has successfully built and scaled businesses, excelling in product development, market strategy, and operational execution.

Pure Global combines real-world experience, AI, and data to create smart and efficient medical device regulatory consulting solutions for more than 30 markets.

Could you share your journey from working with top consulting firms like Deloitte and PwC to becoming the co-founder of Pure Global? What inspired this transition?

My journey to co-founding Pure Global was shaped by two pivotal moments. First, the COVID-19 pandemic threw the world into chaos, forcing individuals, businesses, and governments to re-evaluate how they operated. As a volunteer helping hospitals and schools source PPE, I gained firsthand insight into the challenges people faced adapting to sudden changes in regulations and market access. That experience really opened my eyes to a critical need.

Second, my entrepreneurial drive came into play. I’ve always been drawn to identifying challenges and creating effective solutions, embracing the process of refining and adapting ideas to address changing needs.

Before Pure Global, I had my own big data and cybersecurity consulting firm, and prior to that, I worked at Big Four firms like Deloitte and PwC. I was constantly pushing the boundaries of technology, creating custom solutions for clients facing unique challenges. It was exciting work, always dynamic and demanding.

At Pure Global, I’m tackling similar challenges but with a healthcare focus. We’re helping MedTech companies bring quality products to market faster and more efficiently. It’s incredibly rewarding to apply my skills and experience to make a real difference in this critical industry.

Pure Global was founded during a critical moment in the pandemic. What were the key challenges and opportunities you identified at that time that led to its creation?

During the pandemic, we began by volunteering to help hospitals and schools source PPE. As we worked with global suppliers, we gained insight into the complexities of international trade and regulations. While assisting manufacturers with changing pandemic rules, we also improved our internal processes for efficiency.

Initially, we only supported a few organizations. However, as requests from manufacturers seeking assistance across various countries grew, we identified a clear need – and a market opportunity – for technology to modernize traditional, often inefficient workflows. We saw an opportunity to make a significant impact by developing solutions to address these challenges

Your Resource Center leverages AI to provide real-time regulatory updates and compliance insights. Can you walk us through how the AI algorithms identify and prioritize regulatory changes across 30+ global markets? What challenges did you face in training these models?

Our Global Markets Resource Center serves as a centralized hub for the latest regulatory updates and insights across all major global medical device markets. We’ve built a robust system to gather regulatory data from diverse sources, such as official agency websites, legal databases, and public announcements. This includes web scraping with intelligent parsing to extract data from unstructured formats like PDFs and HTML, as well as using APIs where available.

When clients register their devices in our Pure Certification module, we leverage AI to suggest the most relevant changes and prioritize them for review. AI text embeddings and similarity calculations rank these updates. For example, if you have a ‘portable dialysis machine’ and three related news articles:

Article #1: New guidelines for the disposal PPEs (cosine similarity to product: 0.2)

Article #2: FDA approves a new portable dialysis machine with improved safety features (cosine similarity: 0.8)

Article #3: Cybersecurity vulnerabilities discovered in connected medical devices (cosine similarity: 0.5)

Text embeddings convert all text into numerical representations in a multi-dimensional vector space. Cosine similarity then calculates the distance between these vectors. The higher the cosine similarity, the greater the relevance of the article to the product.

The Translation Manager uses AI to convert technical documents into over 20 languages. How does the system ensure accuracy and cultural relevance in translations for highly regulated markets, and how does it compare to traditional translation methods in terms of speed and compliance reliability?

AI is truly breaking barriers in this regard. From our internal testing with localized regulatory experts, the accuracy of these AI translations exceeds 80%. Combined with our proprietary MedTech-specific multilingual glossaries, we can push this to over 90%, significantly reducing the time required compared to traditional translation methods.

With AI-driven tools like the Translation Manager and Certification Manager, what kind of feedback have you received from clients about their efficiency gains?

Clients have reported significant efficiency gains through the use of our AI-driven tools. Many have experienced reduced translation costs, particularly for high-volume content, thanks to the automation of previously manual tasks. This has not only cut costs but also accelerated workflows.

Additionally, the consistency and flow of translations have improved. Our multilingual translation terminology management ensures consistent language use across all translated materials, which is critical for maintaining brand identity and clarity in technical documentation. Previously, depending on who performed the translation, the flow could differ slightly. With AI-driven translation, however, the consistency and flow are seamless.

In your opinion, how is big data reshaping the MedTech industry, especially in regulatory compliance and market access?

Some exciting developments in the context of big data are as follows:

Data-Driven Decision Making (Market Intelligence): Big data tools provide comprehensive analytics, enabling companies to make informed decisions about market opportunities, patient behavior, product development, market access, and commercial success.

Post-Market Surveillance: Real-world data monitoring can identify safety issues or areas for improvement, leading to faster, more effective post-market surveillance.

Real-World Evidence (RWE): Analyzing large datasets of real-world data (patient records, clinical trials, device usage) can provide evidence of product safety and effectiveness, supporting regulatory submissions and post-market surveillance. However, much of this information still resides within large hospital systems and research institutions, and accessing it remains a challenge.

Cybersecurity:  With the surge in connected medical devices, wearables, and healthcare IoT devices generating vast amounts of data, the attack surface for cybercriminals continues to expand. Sensitive patient information stored in large datasets becomes a prime target for hackers, potentially leading to data breaches that compromise privacy and safety. Then, many healthcare organizations still rely on outdated systems with insufficient cybersecurity measures, increasing the risk.

How do you envision the intersection of AI, cybersecurity, and MedTech evolving in the future?

There will be more personalized options as AI enables the development of medical devices and treatment plans tailored to individual patient needs. By analyzing patient data, including genomics, lifestyle factors, and medical history, AI can optimize device design and functionality. Additionally, AI can accelerate the design and prototyping of medical devices by generating design options, simulating performance, and optimizing for specific requirements, allowing companies to iterate quickly and bring new products to market faster.

Cybersecurity is becoming increasingly emphasized in the MedTech space. This shift comes as regulators recognize its growing importance and transition from a reactive approach—mainly responding to incidents—to a more proactive approach focused on risk management and prevention. As submission requirements for cybersecurity continue to increase in rigor, companies will need to prioritize cybersecurity throughout the entire product development lifecycle, from design to deployment, to ensure the safety and reliability of their devices.

What do you see as the biggest challenges for medical device manufacturers in the next five years, and how does Pure Global aim to address them?

The biggest challenge is that regulatory agencies worldwide are raising the bar for safety, efficacy, and cybersecurity, making it increasingly difficult to keep up with evolving requirements across multiple markets

How Pure Global can help:

AI-Powered Regulatory Intelligence: Pure Global’s AI platform monitors regulatory changes across 30+ markets, offering real-time updates and personalized alerts for compliance.

Streamlined Submission Workflows: AI helps reduce time and costs for regulatory submissions, making the clearance and approval process more efficient.

Market Intelligence: With a comprehensive database covering regulations, product registrations, and clinical trials across 30+ markets, manufacturers can analyze trends, identify opportunities, and assess competition.

What advice would you give to startups and scaleups in the MedTech space looking to navigate complex regulatory landscapes?

Prioritize Regulatory Strategy Early On:

Integrate from the start: Incorporate regulatory considerations into your product development from day one, rather than treating them as an afterthought.

Proactive planning: Establish a clear regulatory strategy early, outlining target markets, device classification, and necessary approvals.

Expert advice: Consult regulatory experts or experienced consultants to understand the specific requirements for your device and target markets.

Stay Agile and Adaptable:

Expect changes: Regulatory landscapes are constantly evolving, so be ready to adapt your strategy as needed.

Flexibility: Keep flexibility in your product development plans to accommodate potential regulatory changes or market requirements.

Thank you for the great interview, readers who wish to learn more should visit Pure Global.

[nnctales]

AI Consulting Business in Construction: Transforming the Industry

The construction industry is experiencing a profound transformation due to the integration of artificial intelligence (AI). The AI consulting business is at the forefront of this change, guiding construction firms in optimizing operations, enhancing safety, and improving project outcomes. This article explores various applications of AI in construction, supported by examples and statistics that…

[artisticdivasworld]

Getting to Know FRC Part 3: Full Service Catalogue

Renee Williams, President, Freight Revenue Consultants, LLC (FRC) At Freight Revenue Consultants (FRC), we’re all about making your trucking operations run smoother and more profitably. With our deep knowledge of the transportation industry and advanced data analytics skills, we tackle everything. What sets us apart is our extensive experience and strong network of contacts and vendors, which…

[informative1-blogs]

Unlocking Business Success Through Analytics

Unlocking Business Success Through Analytics

In the era of big data, business analytics has become a vital asset for organizations striving to gain a competitive edge. With the vast amounts of data generated through various business activities, companies now have the potential to derive valuable insights that can drive strategic decisions and operational improvements. This blog explores the numerous benefits of business analytics in organizations, with a particular focus on its role in business consulting.

 Understanding Business Analytics

Business analytics refers to the systematic, iterative exploration of an organization's data, primarily through statistical analysis, to inform decision-making. It involves using various tools and techniques to analyze data, identify patterns, and draw meaningful insights that can guide business strategies and operations. Business analytics encompasses several domains, including descriptive, predictive, and prescriptive analytics, each serving distinct purposes.

 Key Components of Business Analytics

1. Descriptive Analytics: This involves analyzing historical data to understand what has happened in the past. Descriptive analytics uses data aggregation and data mining techniques to provide insights into past performance and trends, helping organizations to assess their historical performance.

2. Predictive Analytics: This uses statistical models and machine learning algorithms to predict future outcomes based on historical data. Predictive analytics helps organizations anticipate future trends, customer behavior, and potential risks, enabling proactive decision-making.

3. Prescriptive Analytics: This provides recommendations on actions to take to achieve desired outcomes. It combines data, mathematical models, and optimization techniques to suggest the best course of action, helping organizations to implement strategies that can enhance performance and efficiency.

 Benefits of Business Analytics

 1. Enhanced Decision-Making

One of the primary benefits of business analytics is the ability to make data-driven decisions. Traditional decision-making often relies on intuition and experience, which can be subjective and prone to error. Business analytics, however, provides objective insights based on data, allowing organizations to make more informed and strategic decisions. For instance, analytics can help identify market trends, predict future outcomes, and assess the potential impact of different strategies.

 2. Improved Operational Efficiency

By analyzing operational data, organizations can identify inefficiencies and areas for improvement. This can lead to streamlined processes, reduced waste, and lower costs. For example, a manufacturing company can use analytics to optimize its production schedule, reducing downtime and increasing output. Similarly, a retail business can analyze sales data to optimize inventory levels, ensuring that products are available when customers want them without overstocking.

 3. Enhanced Customer Insights

Understanding customer behavior is crucial for any business. Business analytics provides deep insights into customer preferences, buying patterns, and feedback. This information can be used to personalize marketing efforts, improve customer service, and develop products that better meet customer needs. For instance, an e-commerce company can analyze browsing and purchase data to recommend products that a customer is likely to buy, thereby increasing sales and customer satisfaction.

 4. Increased Revenue

By leveraging business analytics, organizations can identify new revenue opportunities and optimize pricing strategies. For example, analytics can help determine the most profitable customer segments, products, and sales channels. By focusing on these areas, businesses can maximize their revenue. Additionally, predictive analytics can forecast future sales trends, allowing companies to plan and allocate resources more effectively.

 5. Risk Management

Risk is an inherent part of any business, but business analytics can help mitigate it. By analyzing historical data, organizations can identify patterns that may indicate potential risks. This could include anything from financial risks, such as credit defaults, to operational risks, like supply chain disruptions. With this information, businesses can develop strategies to mitigate these risks, ensuring greater stability and resilience.

 6. Competitive Advantage

In a highly competitive market, staying ahead of the competition is crucial. Business analytics provides organizations with insights that can give them a competitive edge. By understanding market trends, customer preferences, and competitor actions, businesses can develop strategies that differentiate them from their competitors. This could include everything from new product development to targeted marketing campaigns.

 7. Strategic Planning

Business analytics plays a crucial role in strategic planning. By analyzing data on market trends, economic conditions, and internal performance, organizations can develop more accurate and effective strategic plans. This helps ensure that resources are allocated efficiently and that the company is well-positioned to achieve its long-term goals.

 The Role of Business Consulting in Business Analytics

Business consulting firms play a vital role in helping organizations harness the power of business analytics. These firms bring expertise, experience, and an outside perspective that can be invaluable in developing and implementing analytics strategies. Here are some ways business consulting can enhance the benefits of business analytics:

 1. Expertise and Knowledge

Business consultants bring a wealth of knowledge and expertise in analytics tools and techniques. They can help organizations select the right tools, develop effective analytics strategies, and ensure that these strategies are aligned with business goals. This expertise is particularly valuable for organizations that are new to business analytics or that lack in-house expertise.

 2. Objective Perspective

An outside perspective can be invaluable in identifying opportunities and challenges that internal teams might overlook. Business consultants can provide an objective assessment of an organization's data and analytics capabilities, helping to identify areas for improvement and potential opportunities for growth.

 3. Implementation Support

Implementing a business analytics strategy can be complex and resource-intensive. Business consultants can provide support throughout the implementation process, from developing a strategy to selecting tools, training staff, and monitoring progress. This ensures that the implementation is successful and that the organization can quickly start realizing the benefits of analytics.

 4. Customized Solutions

Every organization is unique, with its own goals, challenges, and data. Business consultants can develop customized analytics solutions that are tailored to the specific needs of the organization. This ensures that the analytics strategy is aligned with business goals and that it delivers the maximum possible value.

 5. Continuous Improvement

Business analytics is not a one-time effort but an ongoing process. Business consultants can help organizations develop a culture of continuous improvement, where data and analytics are constantly used to drive decision-making and improve performance. This ensures that the organization remains agile and responsive to changing market conditions and business needs.

 FAQs

 1. What is the difference between business analytics and business intelligence?

Business intelligence (BI) refers to the process of collecting, storing, and analyzing data from business operations. It focuses on historical data to provide insights into what has happened in the past. Business analytics (BA), on the other hand, involves using statistical and quantitative analysis to predict future trends and outcomes, providing insights into what could happen and what actions should be taken.

 2. How can small businesses benefit from business analytics?

Small businesses can benefit from business analytics in many of the same ways as larger organizations. By using data to make informed decisions, small businesses can improve efficiency, enhance customer satisfaction, and drive growth. Analytics can help small businesses understand customer behavior, optimize operations, and identify new revenue opportunities.

 3. What tools are commonly used in business analytics?

There are many tools available for business analytics, ranging from basic spreadsheet software to advanced analytics platforms. Some commonly used tools include Microsoft Excel, Tableau, Power BI, SAS, R, Python, and IBM Cognos. The choice of tool depends on the specific needs and capabilities of the organization.

In conclusion, business analytics offers a wealth of benefits for organizations, ranging from improved decision-making and operational efficiency to enhanced customer insights and increased revenue. By leveraging the expertise of business consulting firms, organizations can successfully implement and optimize their analytics strategies, ensuring they extract the maximum possible value from their data. The ability to make data-driven decisions will not only enhance current performance but also provide the agility needed to adapt to future market shifts, thereby ensuring long-term success and sustainability.

Reference : https://addonez.com/benefits-of-business-analytics-in-an-organization/

[hari-100]

Transform Your Business with Pixid.ai Data Engineering Services in Australia

Transform Your Business with Pixid.ai Data Engineering Services in Australia

Data engineering is essential for transforming raw data into actionable insights, and Pixid.ai stands out as a leading provider of these services in Australia. Here’s a comprehensive look at what they offer, incorporating key services and terms relevant to the industry

Data Collection and Storage

Pixid.ai excels in big data engineering services in Australia and New zealand  collecting data from various sources like databases, APIs, and IoT devices. They ensure secure storage on cloud platforms or on premises servers, offering flexible cloud data engineering services in Australia tailored to client needs.

Data Processing

Their data processing includes cleaning and organizing raw data to ensure it’s accurate and reliable. This is crucial for effective ETL services in New zealand and Australia (Extract, Transform, Load), which convert raw data into a usable format for analysis.

Data Analysis and Visualization

Pixid.ai employs complex analytical algorithms to detect trends and patterns in data. Their big data analytics company in Australia and New Zealand provides intelligent research and generates visual representations like charts and dashboards to make difficult data easier to grasp. They also provide sentiment analysis services in New zealand and Australia, helping businesses gauge public opinion and customer satisfaction through data.

Business Intelligence and Predictive Analytics

Their robust data analytics consulting services in New zealand and Australia include business intelligence tools for real time performance tracking and predictive analytics to forecast future trends. These services help businesses stay proactive and make data-driven decisions.

Data Governance and Management

Pixid.ai ensures data quality and security through strong data governance frameworks. As data governance service providers in Australia and New zealand they implement policies to comply with regulations, maintain data integrity, and manage data throughout its lifecycle.

Developing a Data Strategy and Roadmap

They collaborate with businesses to develop a comprehensive data strategy aligned with overall business goals. This strategy includes creating a roadmap that outlines steps, timelines, and resources required for successful data initiatives.

Specialized Consulting Services

Pixid.ai offers specialized consulting services in various big data technologies:

Apache Spark consulting services in Australia: Leveraging Spark for fast and scalable data processing.

Data Bricks consulting services in Australia: Utilizing Databricks for unified analytics and AI solutions.

Big data consulting services in Australia: Providing expert guidance on big data solutions and technologies.

Why Choose Pixid.ai?

Pixid.ai’s expertise ensures businesses can leverage their data effectively, providing a competitive edge. Their services span from data collection to advanced analytics, making them a top choice for big data engineering services in Australia and new zealand They utilize technologies like Hadoop and cloud platforms to process data efficiently and derive accurate insights.

Partnering with Pixid.ai means accessing comprehensive data solutions, from cloud data engineering services in Australia to detailed data governance and management. Their specialized consulting services, including Apache Spark consulting services in Australia and Data Bricks consulting services in Australia and new zealand ensure that businesses have the expert guidance needed to maximize their data’s value.

Conclusion

In the competitive landscape of data driven business, Pixid.ai provides essential services to transform raw data into valuable insights. Whether it’s through big data consulting services in Australia and new zealand or data analytics consulting services in new Zealand and Australia, Pixid.ai helps businesses thrive. Their commitment to excellence in data engineering and governance makes them a trusted partner for any business looking to harness the power of their data.

For more information please contact.www.pixid.ai

[workforcesolution]

Discover the essential skills for a data scientist, including a relevant degree, knowledge of parallel fields, strong communication abilities, teamwork, and industry understanding. Learn why these skills are crucial for success in this dynamic field. https://www.rangtech.com/blog/data-science/skill-sets-required-to-be-a-data-scientist

[capitalism-and-analytics]

[collabsoftech]

Data Analytics Services to Unlock Business Insights | Collab Softech 

Make smarter decisions with advanced Data Analytics solutions from Collab Softech. We help businesses harness the power of data through real-time dashboards, custom reporting, predictive analytics, and business intelligence tools. Our data experts turn raw data into actionable insights that improve performance, optimize strategy, and drive growth. Partner with us today to transform your data into a powerful business asset.

[scholarnest]

Business Intelligence Solutions: Unleashing the Power of Managed Analytics

In today's dynamic business landscape, the effective utilization of data is pivotal for informed decision-making and sustained growth. Business Intelligence (BI) solutions have emerged as a cornerstone, offering organizations the ability to glean actionable insights from their data. This article explores the transformative impact of BI solutions and how managed analytics, coupled with outsourced IT management, is reshaping the way businesses harness the power of data.

1. Proactive IT Support and Managed IT Services:

BI solutions thrive in an environment supported by proactive IT services. Managed IT services, which include proactive support and maintenance, ensure the seamless operation of BI tools. This proactive approach not only enhances the reliability of analytics but also minimizes downtime, allowing businesses to make real-time decisions.

2. Advanced Analytics and Data Visualization Services:

Managed analytics encompass advanced analytics services that go beyond basic reporting. Data visualization services play a crucial role, translating complex data sets into visually appealing and understandable insights. This facilitates better communication and comprehension of data-driven findings across all levels of an organization.

3. Cloud Management Solutions and Migration Strategies:

The integration of cloud management solutions is a game-changer for BI. Cloud migration solutions offer scalability, flexibility, and cost-efficiency. Managed BI services leverage cloud optimization solutions, ensuring that businesses make the most of cloud resources while maintaining peak performance.

4. Data Science Solutions and Hybrid Cloud Integration:

BI solutions often involve intricate data science methodologies. Managed analytics extend to data science solutions, enabling organizations to employ predictive analytics and machine learning for more accurate forecasting. Hybrid cloud solutions provide the necessary infrastructure for hosting and processing data across different environments securely.

5. IT Consultation Services and Strategic Managed Services:

Strategic IT consultation services are instrumental in aligning BI strategies with overall business objectives. Managed services, including serverless computing and big data consulting, are designed to optimize the performance of BI tools, ensuring they adapt to evolving business requirements.

6. Cloud Consulting Services and Holistic Cloud Management:

BI solutions benefit from specialized cloud consulting services. These services guide organizations in selecting the most suitable cloud platforms and architectures for their BI needs. Holistic cloud management services oversee the entire cloud ecosystem, ensuring optimal performance and security.

In conclusion, the convergence of BI solutions and managed analytics is reshaping the way businesses interpret and leverage their data. With the right blend of outsourced IT management, advanced analytics, and cloud solutions, organizations can unlock the full potential of their data, gaining a competitive edge in today's data-driven era.

[jcmarchi]

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series

New Post has been published on https://thedigitalinsider.com/dr-mike-flaxman-vp-or-product-management-at-heavy-ai-interview-series/

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series

Dr. Mike Flaxman is currently the VP of Product at HEAVY.AI, having previously served as Product Manager and led the Spatial Data Science practice in Professional Services. He has spent the last 20 years working in spatial environmental planning. Prior to HEAVY.AI, he founded Geodesign Technolgoies, Inc and cofounded GeoAdaptive LLC, two startups applying spatial analysis technologies to planning. Before startup life, he was a professor of planning at MIT and Industry Manager at ESRI.

HEAVY.AI is a hardware-accelerated platform for real-time, high-impact data analytics. It leverages both GPU and CPU processing to query massive datasets quickly, with support for SQL and geospatial data. The platform includes visual analytics tools for interactive dashboards, cross-filtering, and scalable data visualizations, enabling efficient big data analysis across various industries.

Can you tell us about your professional background and what led you to join HEAVY.AI?

Before joining HEAVY.AI, I spent years in academia, ultimately teaching spatial analytics at MIT. I also ran a small consulting firm, with a variety of public sector clients. I’ve been involved in GIS projects across 17 countries. My work has taken me from advising organizations like the Inter American Development Bank to managing GIS technology for architecture, engineering and construction at ESRI, the world’s largest GIS developer

I remember vividly my first encounter with what is now HEAVY.AI, which was when as a consultant I was responsible for scenario planning for the Florida Beaches Habitat Conservation Program.  My colleagues and I were struggling to model sea turtle habitat using 30m Landsat data and a friend pointed me to some brand new and very relevant data – 5cm LiDAR.   It was exactly what we needed scientifically, but something like 3600 times larger than what we’d planned to use.  Needless to say, no one was going to increase my budget by even a fraction of that amount. So that day I put down the tools I’d been using and teaching for several decades and went looking for something new.  HEAVY.AI sliced through and rendered that data so smoothly and effortlessly that I was instantly hooked.

Fast forward a few years, and I still think what HEAVY.AI does is pretty unique and its early bet on GPU-analytics was exactly where the industry still needs to go. HEAVY.AI is firmly focussed on democratizing access to big data. This has the data volume and processing speed component of course, essentially giving everyone their own supercomputer.  But an increasingly important aspect with the advent of large language models is in making spatial modeling accessible to many more people.  These days, rather than spending years learning a complex interface with thousands of tools, you can just start a conversation with HEAVY.AI in the human language of your choice.  The program not only generates the commands required, but also presents relevant visualizations.

Behind the scenes, delivering ease of use is of course very difficult.  Currently, as the VP of Product Management at HEAVY.AI, I’m heavily involved in determining which features and capabilities we prioritize for our products. My extensive background in GIS allows me to really understand the needs of our customers and guide our development roadmap accordingly.

How has your previous experience in spatial environmental planning and startups influenced your work at HEAVY.AI?

 Environmental planning is a particularly challenging domain in that you need to account for both different sets of human needs and the natural world. The general solution I learned early was to pair a method known as participatory planning, with the technologies of remote sensing and GIS.  Before settling on a plan of action, we’d make multiple scenarios and simulate their positive and negative impacts in the computer using visualizations. Using participatory processes let us combine various forms of expertise and solve very complex problems.

While we don’t typically do environmental planning at HEAVY.AI, this pattern still works very well in business settings.  So we help customers construct digital twins of key parts of their business, and we let them create and evaluate business scenarios quickly.

I suppose my teaching experience has given me deep empathy for software users, particularly of complex software systems.  Where one student stumbles in one spot is random, but where dozens or hundreds of people make similar errors, you know you’ve got a design issue. Perhaps my favorite part of software design is taking these learnings and applying them in designing new generations of systems.

Can you explain how HeavyIQ leverages natural language processing to facilitate data exploration and visualization?

These days it seems everyone and their brother is touting a new genAI model, most of them forgettable clones of each other.  We’ve taken a very different path.  We believe that accuracy, reproducibility and privacy are essential characteristics for any business analytics tools, including those generated with large language models (LLMs). So we have built those into our offering at a fundamental level.  For example, we constrain model inputs strictly to enterprise databases and to provide documents inside an enterprise security perimeter.  We also constrain outputs to the latest HeavySQL and Charts.  That means that whatever question you ask, we will try to answer with your data, and we will show you exactly how we derived that answer.

With those guarantees in place, it matters less to our customers exactly how we process the queries.  But behind the scenes, another important difference relative to consumer genAI is that we fine tune models extensively against the specific types of questions business users ask of business data, including spatial data.  So for example our model is excellent at performing spatial and time series joins, which aren’t in classical SQL benchmarks but our users use daily.

We package these core capabilities into a Notebook interface we call HeavyIQ. IQ is about making data exploration and visualization as intuitive as possible by using natural language processing (NLP). You ask a question in English—like, “What were the weather patterns in California last week?”—and HeavyIQ translates that into SQL queries that our GPU-accelerated database processes quickly. The results are presented not just as data but as visualizations—maps, charts, whatever’s most relevant. It’s about enabling fast, interactive querying, especially when dealing with large or fast-moving datasets. What’s key here is that it’s often not the first question you ask, but perhaps the third, that really gets to the core insight, and HeavyIQ is designed to facilitate that deeper exploration.

What are the primary benefits of using HeavyIQ over traditional BI tools for telcos, utilities, and government agencies?

HeavyIQ excels in environments where you’re dealing with large-scale, high-velocity data—exactly the kind of data telcos, utilities, and government agencies handle. Traditional business intelligence tools often struggle with the volume and speed of this data. For instance, in telecommunications, you might have billions of call records, but it’s the tiny fraction of dropped calls that you need to focus on. HeavyIQ allows you to sift through that data 10 to 100 times faster thanks to our GPU infrastructure. This speed, combined with the ability to interactively query and visualize data, makes it invaluable for risk analytics in utilities or real-time scenario planning for government agencies.

The other advantage already alluded to above, is that spatial and temporal SQL queries are extremely powerful analytically – but can be slow or difficult to write by hand.   When a system operates at what we call “the speed of curiosity” users can ask both more questions and more nuanced questions.  So for example a telco engineer might notice a temporal spike in equipment failures from a monitoring system, have the intuition that something is going wrong at a particular facility, and check this with a spatial query returning a map.

What measures are in place to prevent metadata leakage when using HeavyIQ?

As described above, we’ve built HeavyIQ with privacy and security at its core.  This includes not only data but also several kinds of metadata. We use column and table-level metadata extensively in determining which tables and columns contain the information needed to answer a query.  We also use internal company documents where provided to assist in what is known as retrieval-augmented generation (RAG). Lastly, the language models themselves generate further metadata.  All of these, but especially the latter two can be of high business sensitivity.

Unlike third-party models where your data is typically sent off to external servers, HeavyIQ runs locally on the same GPU infrastructure as the rest of our platform. This ensures that your data and metadata remain under your control, with no risk of leakage. For organizations that require the highest levels of security, HeavyIQ can even be deployed in a completely air-gapped environment, ensuring that sensitive information never leaves specific equipment.

How does HEAVY.AI achieve high performance and scalability with massive datasets using GPU infrastructure?

The secret sauce is essentially in avoiding the data movement prevalent in other systems.  At its core, this starts with a purpose-built database that’s designed from the ground up to run on NVIDIA GPUs. We’ve been working on this for over 10 years now, and we truly believe we have the best-in-class solution when it comes to GPU-accelerated analytics.

Even the best CPU-based systems run out of steam well before a middling GPU.  The strategy once this happens on CPU requires distributing data across multiple cores and then multiple systems (so-called ‘horizontal scaling’).  This works well in some contexts where things are less time-critical, but generally starts getting bottlenecked on network performance.

In addition to avoiding all of this data movement on queries, we also avoid it on many other common tasks.  The first is that we can render graphics without moving the data.  Then if you want ML inference modeling, we again do that without data movement.  And if you interrogate the data with a large language model, we yet again do this without data movement. Even if you are a data scientist and want to interrogate the data from Python, we again provide methods to do this on GPU without data movement.

What that means in practice is that we can perform not only queries but also rendering 10 to 100 times faster than traditional CPU-based databases and map servers. When you’re dealing with the massive, high-velocity datasets that our customers work with – things like weather models, telecom call records, or satellite imagery – that kind of performance boost is absolutely essential.

How does HEAVY.AI maintain its competitive edge in the fast-evolving landscape of big data analytics and AI?

That’s a great question, and it’s something we think about constantly. The landscape of big data analytics and AI is evolving at an incredibly rapid pace, with new breakthroughs and innovations happening all the time. It certainly doesn’t hurt that we have a 10 year headstart on GPU database technology. .

I think the key for us is to stay laser-focused on our core mission – democratizing access to big, geospatial data. That means continually pushing the boundaries of what’s possible with GPU-accelerated analytics, and ensuring our products deliver unparalleled performance and capabilities in this domain. A big part of that is our ongoing investment in developing custom, fine-tuned language models that truly understand the nuances of spatial SQL and geospatial analysis.

We’ve built up an extensive library of training data, going well beyond generic benchmarks, to ensure our conversational analytics tools can engage with users in a natural, intuitive way. But we also know that technology alone isn’t enough. We have to stay deeply connected to our customers and their evolving needs. At the end of the day, our competitive edge comes down to our relentless focus on delivering transformative value to our users. We’re not just keeping pace with the market – we’re pushing the boundaries of what’s possible with big data and AI. And we’ll continue to do so, no matter how quickly the landscape evolves.

How does HEAVY.AI support emergency response efforts through HeavyEco?

We built HeavyEco when we saw some of our largest utility customers having significant challenges simply ingesting today’s weather model outputs, as well as visualizing them for joint comparisons.  It was taking one customer up to four hours just to load data, and when you are up against fast-moving extreme weather conditions like fires…that’s just not good enough.

HeavyEco is designed to provide real-time insights in high-consequence situations, like during a wildfire or flood. In such scenarios, you need to make decisions quickly and based on the best possible data. So HeavyEco serves firstly as a professionally-managed data pipeline for authoritative models such as those from NOAA and USGS.  On top of those, HeavyEco allows you to run scenarios, model building-level impacts, and visualize data in real time.   This gives first responders the critical information they need when it matters most. It’s about turning complex, large-scale datasets into actionable intelligence that can guide immediate decision-making.

Ultimately, our goal is to give our users the ability to explore their data at the speed of thought. Whether they’re running complex spatial models, comparing weather forecasts, or trying to identify patterns in geospatial time series, we want them to be able to do it seamlessly, without any technical barriers getting in their way.

What distinguishes HEAVY.AI’s proprietary LLM from other third-party LLMs in terms of accuracy and performance?

Our proprietary LLM is specifically tuned for the types of analytics we focus on—like text-to-SQL and text-to-visualization. We initially tried traditional third-party models, but found they didn’t meet the high accuracy requirements of our users, who are often making critical decisions. So, we fine-tuned a range of open-source models and tested them against industry benchmarks.

Our LLM is much more accurate for the advanced SQL concepts our users need, particularly in geospatial and temporal data. Additionally, because it runs on our GPU infrastructure, it’s also more secure.

In addition to the built-in model capabilities, we also provide a full interactive user interface for administrators and users to add domain or business-relevant metadata.  For example, if the base model doesn’t perform as expected, you can import or tweak column-level metadata, or add guidance information and immediately get feedback.

How does HEAVY.AI envision the role of geospatial and temporal data analytics in shaping the future of various industries?

 We believe geospatial and temporal data analytics are going to be critical for the future of many industries. What we’re really focused on is helping our customers make better decisions, faster. Whether you’re in telecom, utilities, or government, or other – having the ability to analyze and visualize data in real-time can be a game-changer.

Our mission is to make this kind of powerful analytics accessible to everyone, not just the big players with massive resources. We want to ensure that our customers can take advantage of the data they have, to stay ahead and solve problems as they arise. As data continues to grow and become more complex, we see our role as making sure our tools evolve right alongside it, so our customers are always prepared for what’s next.

Thank you for the great interview, readers who wish to learn more should visit HEAVY.AI.

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