Introduction Every five to six years, there comes a technology wave, and if you are able to catch it, it will take you a long way. Throughout my career, I’ve ridden several of these waves. MPP data warehouses brought us incredible speed for analytics and a few headaches for data integration. We’re seeing in-memory analytics reducing disk latency. Hadoop based technologies are opening up new solutions every day for storage and compute workloads while our source systems are still generating varying degrees of velocity, volume, and variety. As a traditional ETL developer, I would usually try to figure out the
Over the last few years there has been a lot of industry buzz about the future of the enterprise data warehouse (EDW). Maybe we should change the classic EDW acronym for a new title: Extended Data Warehouse.
If you have any doubts about the data flood that is covering the globe, here are a few amazing stats. Around the world, in just one minute…
When I received the email notice from the TDWI Dallas Chapter about an upcoming Big Data event, I was interested. The meeting was at 8:00 a.m. on a Friday, the traffic wouldn’t be ideal, but it sounded like this might be a good opportunity.
Why would it be a good opportunity? Bill Inmon was in town!
Business Intelligence guru, analyst and author, Wayne Eckerson, and I had great times when we worked together at The Data Warehousing Institute (TDWI). Although we have both moved on to other ventures, we remain in touch and I still like reading his books and articles.
I particularly enjoyed the first chapter of his most recent book, Secrets of Analytical Leaders: Insights from Information Insiders, where he talks about the concept of “purple people.” But before I explain that, read this concept from Wayne in his book.
There have been several advancements within the Hadoop world that have positioned Hadoop closer to the data warehousing community than ever before. With a series of Hadoop 2.0 releases starting in October 2013, Hadoop is now much closer to being a platform for a data warehouse.
Every once in a while I brush aside all the stacks of paper on my desk and tell myself to spend a couple hours deep diving into some topic to see where it takes me. If browsers could heat up from over-use, there would be smoke coming out of my office for those two hours.
This time I focused on an IDC report that came out towards the end of 2013. I had seen this phrase a few times before, but for some reason it really caught my eye this time:
The Third Platform.
In both consumer and business technology discussions, we hear a lot about the cloud these days. So what does “cloud” mean within the context of things like Big Data, Business Intelligence and Data Warehousing?
When we talk about data strategies and cloud technology, there are some basic service categories and deployment models that need to be defined and understood. Here’s a quick look at those categories and models—plus an interesting look at the market itself and where it’s going as predicted by the experts.
How old is your data warehouse? It’s a simple question and probably one you don’t think about much. The majority of production data warehouses are now 15-20 years old and probably very transactional centric. Over the years, you’ve probably remodeled “the house” more than a few times—adding some “rooms” and “upgrades” here and there. It’s starting to feel its age as more Business Intelligence requirements have been added, including Mobile applications and specialized analytics. And more and more ideas seem to show up in your inbox every day, especially Big Data questions.
Have you ever wondered how it would feel to stand on the top step of an Olympic podium, lean over and have a gold medal placed around your neck? You not only have family, friends and coaches cheering you on, you have a whole nation behind you. It must be an overwhelming moment. While few ever have that opportunity, you can be the go-to champion in your organization. How can that happen?