Featured Stories

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

  • COVID and Compliance Shape 2021’s Data Workflow and Forensics Trends

    In this special guest feature, Bobby Balachandran, CEO, President and Founder of Exterro, discusses how upholding data integrity – the qualities of consistency, accuracy and reliability of digital information – has always been a priority for organizations. It’s not just a job for IT. Maintaining data integrity is an overarching obligation, although each department’s priorities will be nuanced by their specific roles and responsibilities.

  • How Harnessing Data Can Lead to Better Financial Outcomes

    In this special guest feature, Greg Wright, Executive Vice President and Chief Product Officer for the Experian Consumer Information Services (CIS) business in North America, discusses how the financial services industry must continue to utilize the most accurate and comprehensive data solutions to enrich credit decisions, while also educating consumers about the options available to them. Educating consumers about the information included in their credit report and ways they can improve their credit histories is an important step in getting the economy as a whole humming again and helping those most in need.

RSS Featured from insideHPC

  • 2 Seconds of Hair Growth: IBM Claims 1st 2 Nanometer Chip Technology
    IBM today unveiled what it said is the first chip with 2 nanometer (nm) nanosheet technology. Though still more than two years from commercial availability, the company said the 2nm chip will be used to power devices ranging from cell phones to HPC-class data center servers and will deliver nearly 50 percent higher performance, or […]

Editor’s Choice

  • The insideBIGDATA IMPACT 50 List for Q2 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.

Sign up for our newsletter and get the latest big data news and analysis.