Tag Archives: Enterprise Data Warehousing

What is Change Data Capture? Something Business and IT Both Agree on for Mainframe Data Integration

A few days ago, I got a text message from a friend telling me that my favorite company’s stock price was suddenly tanking and that I should dump my holding.  So I went to the news portal to get a stock quote and see where the stock price happens to be. I found that the stock didn’t move much at all.  Thinking that it might’ve been a prank text message, I ignored it.  To my dismay, the stock quote I saw was delayed by 20 minutes and the decline wasn’t yet reflected in the news portal. (more…)

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What Role Does Data Integration Play In Data Warehousing?

In my previous entry, I mentioned how our customers are democratizing innovation in data warehousing and data integration. One thing is clear: there is renewed energy around using data to become competitive in the global market. We also have many options in data warehousing –a centralized enterprise data warehouse (EDW), departmental data warehouses and data marts, including appliance options and cloud computing for data warehousing. And yes, we do have an ongoing argument of EDW versus data marts. What’s different at this time is that, it’s the business that’s fueling this debate. A customer may outlaw a data mart because the maintenance costs and risks managing marts outweigh the potential benefits and thus do not meet the operating requirements. Another may opt for a cyclical data mart to allow for faster time to market and analytic flexibility for departmental business needs with a shorter turnaround.

One of our customers in the entertainment industry recently went live with their real-time data warehousing and master data management project. (more…)

Posted in Data Integration, Data Integration Platform, Data Quality, Data Warehousing, Enterprise Data Management, Master Data Management, Real-Time | Tagged , , , , | Leave a comment

Dr. Kimball, Pervasive BI and Real-time Demo

This year, I have the pleasure of hosting a yearlong Web Seminar series featuring Dr. Ralph Kimball. On April 23, we will discuss how we build an enterprise data warehouse to garner the benefits of Pervasive BI. This is exciting because it will be the first time that Dr. Kimball will describe Pervasive BI from the data warehousing perspective in depth.  What’s more, we will provide a live demonstration of Informatica PowerCenter Real-time Edition. It will be a potent combination of Dr. Kimball, Pervasive BI and Real-time Demo. Hope you will join us.

PS. We are also kicking off an Operational BI Road Show featuring David Loshin with our friends from Teradata and MicroStrategy. We’re sure to have a location near you.

Posted in Data Integration, Data Warehousing, Enterprise Data Management | Tagged , | 7 Comments

After 2009, Enterprise Data Warehousing Will Never be the Same

For years, the data warehousing space had been fairly steady and predictable. Data warehouses grew by terabytes over terabytes, addressing a critical need to collect and analyze data to discover patterns in customer behavior and other business trends. However, data warehouses have also been notoriously expensive and complex to implement in their early stages, requiring major corporate budget initiatives.

Now, revolutionary forces are aligning and reshaping the world of enterprise data warehousing as we know it. (more…)

Posted in Business Impact / Benefits, Cloud Computing, Data Integration, Data Warehousing, Enterprise Data Management, Master Data Management | Tagged , | Leave a comment

Turbocharging Data Warehousing Performance with ELT

Flipping around traditional ETL (Extract-Transform-Load) on its head is not a new practice.  ELT (Extract-Load-Transform), where processing is handled in the database, instead of the ETL server, has been proven to enhance performance in many types of data warehousing deployments.

For example, Oi, a leading telecom provider in Brazil, implemented an enterprise data warehouse (EDW) consolidating information on 36 million customers, speeding response time to customer requests.  The right-time EDW also enabled Oi to rapidly launch a successful new service offering, which made it easier for customers to recharge their pre-paid accounts for telecom service.

By implementing ELT with Informatica’s pushdown optimization capabilities for this Teradata data warehouse, Oi accelerated its data warehousing loading process two-fold.  This has led to even more timely updates of Oi’s customer information, while lowering costs.

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Viva la Data Warehouse

Okay, so the band Coldplay will never release a song by that title (and I probably wouldn’t want to hear it if they did.)  But it would be timely, because despite certain rumors to the contrary, data warehousing is thriving.

We weren’t supposed to need data warehousing in an era of SOA/data services, data federation and other new-fangled technologies.  Data warehousing was old-fashioned and tired and a bit boring.  But the need for data warehousing solutions just continues to grow– companies aren’t getting less data, and their environments aren’t getting simpler.  The discipline of integrating data from multiple systems and conforming it to a common structure so that is can be analyzed and used for business intelligence and reporting is still invaluable.  This is not to say that the new technologies don’t play a role– they can greatly enhance data warehousing by providing more real-time data and new ways of delivering data where it’s needed. (more…)

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It’s about time for Enterprise Data Warehousing (EDW)

As Don noted in his post “Why the “E” in EDW (Enterprise Data Warehousing)?” many companies have successfully implemented Enterprise Data Warehousing, producing great business ROI. Don talked about how the industry has evolved to better appreciate EDW.

While consulting to companies on data warehousing solutions I’ve noticed that companies not effectively deploying EDW fall into two camps:

  • No real data warehousing effort. Instead they rely on their business applications to provide reporting and analysis capabilities.
  • A central data warehouse has been created. But they conduct most analysis using databases (maybe called data marts) or data shadow systems created separately from the central DW.

If you are in either camp it may finally be time for you to pursue enterprise data warehousing.

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