• NoSQL vs SQL: Key Differences

    In this contributed article, Alex Williams, Writer/Researcher at Hosting Data UK, indicates that NoSQL and SQL databases greatly differ on many points. One is not better than the other, but just like any technology, eventually, developers will have their preferences. Luckily, there are numerous options for database selection for both SQL and NoSQL databases.

Featured Stories

  • 5 Tips for Making Data Work for Your Business

    In this contributed article, Scott Ziemke, Director of Data Science, Vertafore, discusses how in order to overcome barriers to data & analytics success, companies must implement clear and relevant strategies that focus on real business cases. Too often data scientists get excited about data and its nuances, but the organization doesn’t know how to operationalize the insights and turn them into action that drives business results. Here’s how to overcome that problem, along with other tips that can help ensure you get the maximum ROI out of your data & analytics investment.

  • 2021 Trends in Blockchain: Mainstream Adoption at Last

    In this contributed article, editorial consultant Jelani Harper believes that mainstream adoption of blockchain is surely coming, both at the consumer and enterprise levels. In all likelihood, momentum in one of these domains will spur that in the other. At this point, cryptocurrencies are still the forerunners of this technology, particularly with the foregoing methods to redress measures for data privacy and oversight.

  • Using AI for Contract Management

    In this special guest feature, Sunu Engineer, Principal Architect at Icertis, discusses using AI for Contract Lifecycle Management. Done right, AI for contract management has the potential to empower organizations to stay out front by turning repositories of contracts into indispensable strategic advantages.

Featured Resource

Why CRM and Data Warehouses Fail with Customer 360

This whitepaper from our friends over at Profisee explains why achieving a complete view of the customer is so difficult and how customer relationship management (CRM) systems and data warehouses, especially in the  insurance industry, do not manage customer-related data well. The core elements of this type  of data fall into a discipline called Master Data Management (MDM).

All Recent News

Industry Perspectives

  • We All Know about AI in Medicine By Now. Here’s Why It Really Matters.

    In this special guest feature, Eran Atlas, Co-Founder & CEO of DreaMed Diabetes, discusses how the rapid incorporation of artificial intelligence in medicine is no longer a novel trend, with more fields than ever developing improved solutions and protocols. Yet the intricacies of AI have often made it a difficult success story to explain to the average Joe. While AI’s huge leap forward has provided much needed clarity and assistance to medical decision-makers, its positive effects have not been as crystal clear for the general public, meaning patients and prospective patients, have no clue how it helps. This article details [READ MORE…]

  • MLOps Brings Best Practices to Developing Machine Learning

    In this special guest feature, Henrik Skogström, Head of Growth at Valohai, discusses how MLOps (machine learning operations) is becoming increasingly relevant as it is the next step in scaling and accelerating the development of machine learning capabilities. The definition of MLOps is not yet crystal clear, but the practice aims to systematize and automate how machine learning models are trained, deployed, and monitored.

RSS Featured from insideHPC

  • Argonne’s Rick Stevens named ACM Fellow
    Rick Stevens has been named a Fellow of the Association of Computer Machinery (ACM). Stevens is associate laboratory director of the Computing, Environment and Life Sciences directorate at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and a professor of computer science at the University of Chicago. Stevens was honored “for outstanding contributions in […]

Editor’s Choice

  • The insideBIGDATA IMPACT 50 List for Q1 2021

    The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting [READ MORE…]

  • Big Data Industry Predictions for 2021

    2020 has been year for the ages, with so many domestic and global challenges. But the big data industry has significant inertia moving into 2021. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming.

  • Hats Over Hearts

    It is with great sadness that we announce the death of Rich Brueckner. His passing is an unexpected and enormous blow to both his family and the HPC Community. Rich was an institution in the HPC community. You couldn’t go to an event without seeing his red hat bobbing in the crowd, usually trailed by a fast-moving video crew. He’d be darting into booths, conducting interviews, and then speeding away to his next appointment.

  • What is the Difference Between Business Intelligence, Data Warehousing and Data Analytics

    In this contributed article, Christopher Rafter, President and COO at Inzata,, writes that in the age of Big Data, you’ll hear a lot of terms tossed around. Three of the most commonly used are “business intelligence,” “data warehousing” and “data analytics.” You may wonder, however, what distinguishes these three concepts from each other so let’s take a look.

  • The Difference Between Data Science and Data Analytics

    In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business.

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