Has data ever been more important than it is right now? As the world continues to grapple with the scale and impact of COVID-19, we look to data—and more importantly, the analysis of that data—to provide us with some level of understanding. There are data sources from independent labs, healthcare systems, different countries, and all... more
You betcha! In fact I heard it’s gonna be so big, that AWS had to rent a whole additional Vegas hotel to keep it all in! OK so I am only half kidding… For anybody following this space, the explosive growth of this conference, has been one of the biggest indicators of how massive AWS... more
A big thank you to everyone who voted for the Datanami 2017 Data Management Cataloging and Prep Reader’s choice awards. We are honored to receive first place recognition in both– the “Big Data Product or Technology: Data Management(Cataloging)” and “Data Management(Prep)” categories. Many of our customers use Informatica’s AI-Powered Data Catalog for a variety of... more
Every data lake is dynamic and never exactly alike which makes managing a data lake a daunting task. As we discussed in prior blogs, we know what’s in the lake and introduced a variety of fish to the lake, we need to manage a lake efficiently, making sure the water quality is good, weeds are... more
You’ve built a data catalog of fish (I’m using fish here as an analogy for data), identifying three categories: Near-shore, bottom-shore and off-shore fish and tagging fish according to various categories. Your catalog also goes one level deep by identifying different levels of plankton! What about introducing new varieties of fishes to the data lake?... more
“Different types of fish live in a community and when you understand their relationship to each other, you have a better chance of catching what you want.” thompsonadvertisinginc.com You navigated your way to the lake and read up on the fundamentals of fish management and introduced the data lake management principles. As you drove up to... more
It’s tough to fish for insights in a poorly designed Data Lake. When you decide to build a data lake, you first need three things: A strong foundation A design blue print A vision for the final product which end users will consume If done correctly, you end up with a delicious platter of fish. ... more
Fraud has been a big challenge for Communications Service Providers (CSPs) and probably always will be. According to the Communications Fraud Control Association (CFCA) fraud costs CSPs billions of dollars a year and in their 2015 survey estimated that cost at over $38bn a year. I was talking with a former colleague recently and he... more
I learned at an early age when fishing with my buddies that it doesn’t matter how good of a fisherman you are—you’re not going to catch anything if you’re not where the fish are. This same bit of advice extends to data lakes. Not even the best data scientists in the world would find insights... more