Evan Terry, Chief Analytics Officer at Velocity Mortgage Capital said that enterprise analytics technology is increasingly sophisticated, due to machine learning, artificial intelligence (AI), and streaming analytics, but you can’t benefit from these advancements without a solid foundation. “There’s a real interplay there between the foundational and the advanced.” Terry discussed these interplays during his […]
Fundamentals of the Data Lakehouse
During the last few years, a new concept in Data Architecture has emerged. It is called the “data lakehouse.” The data lakehouse offers a new paradigm that takes the best characteristics of data warehouses (large amounts of coordinated data) and data lakes (massive amounts of uncoordinated data), and merges them, providing improved controls and tools. […]
How to (Easily) Tap Historical Data for Business Growth
Click to learn more about author Joe Gaska. Imagine if you could remember every single thing that has happened in your life, and go back to any point in time to see how decisions, both big and small, altered your path. What might you learn that would help shape the decisions you make today and […]
Data Mesh in Practice: Learnings from a Customer Journey
Click to learn more about author Mathias Golombek. In my last blog post, I introduced the data mesh concept and explored the link between data democratization and data mesh. Since then I’ve had lots of interesting conversations on the topic with colleagues and customers. In particular, I interviewed one customer who has been on a very […]
AI Marches Forward: How the Latest Advances Could Impact Commercial Insurance
Over the past two years, the implementation of AI systems in the insurance industry has seen a sharp uptick, particularly when applied to claims operations.
Understanding the ETL vs. ELT Alphabet Soup and When to Use Each
There are advantages and disadvantages to both ETL and ELT. To understand which method is a better fit, it’s important to understand what it means when one letter comes before the other.
Why Graph Databases Are an Essential Choice for Master Data Management
Click to learn more about author Brian Platz. Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. It’s outdated, it’s clunky, and it was built for a different era. […]
Case Study: Cox Automotive Solves Data Drift and ETL Challenges
According to Pat Patterson, Community Champion at StreamSets, “data drift” is such a problem now that “only about one fifth of a data analyst’s time is actually spent analyzing the data.” The remainder is spent “wrangling it into shape and getting it from where it is to the actual analysis platform.” Speaking at the Enterprise […]
Where Is the Data Technology Industry Headed?
Click here to learn more about Heine Krog Iversen. We recently read reports about plans for Talend to be acquired by Thoma Bravo, a private equity investment firm. This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]
Is Lakehouse Architecture a Grand Unification in Data Analytics?
Click to learn more about author Arsalan Farooq. I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]