Informatica Perspectives

Judy Ko recently discussed the difficulties business users have communicating with technical staff, and visa-versa. "How many of us have spent days or even weeks in tedious requirements gathering sessions, asking what the business wants, and getting very fuzzy answers back?" she asked, taking the technical side. Conversely, business people frequently complain that technical folks speak a different, strange language. This makes key enterprise projects such as data warehousing, SOA, or data integration that much more difficult, if not impossible, to implement. [Read more]

Last month I posted an article about cloud computing and cloud integration (see Keep your feet on the ground and your head in the clouds for the full article) and encouraged readers to come to the Architecture and Integration Summit to see Informatica, salesforce.com and Amazon.com tell the story and see a demo. Those that came were not disappointed – the keynote presentation by Sanjay Krishnamurthy, Jeff Barr and Peter Coffee was electrifying! [Read more]

Over the past several quarters, I’ve had the privilege of speaking with a number of companies involved in data governance. The interesting thing I found: firms who identified both drivers as critical, but only invest in one and not the other.

Case in point: a leading financial services firm implemented a data governance program to improve the comprehension and accuracy of the company’s existing board reports. I learned that one of their goals was to define their business terms and definitions (i.e. business metadata) to help non-technical users improve their understanding of the data used to run the business. What I found fascinating was that this was being done prior to addressing their data quality issues. In fact, when asked, “Do you have data quality challenges?” most business users said “yes”. Unfortunately, no one at this company knew to what extent. Instead, their focus was on defining their business metadata. This leads me to ask, “Can you trust your metadata without addressing your data quality issues as part of a data governance practice?”

If metadata is information about your data which your business users are relying on to drive decisions, but the source data is not clean, how will that affect your business? The answers seem self-explanatory. Of course you can’t trust your metadata if you have poor quality data.  For example, business metadata is defined from an approved list of valid values. Unfortunately, if the data used to define those values are incorrect, the downstream impact is you end up with inaccurate metadata.

Organizations implementing data governance programs need to consider the lifecycle of how data is captured, processed, and delivered to downstream systems— whether that is your data warehouse, master data management application, data hub or CRM system. Creating, defining, and publishing business metadata without addressing your data quality issues may not help companies looking to benefit from data governance.

Now that the $700 billion dollar Troubled Asset Rescue Program (TARP) has been approved by the government, firms on Wall Street are preparing themselves for even more oversight and scrutiny by lawmakers and taxpayers. Survivors from the market meltdown will be required to establish tighter controls, policies, standards, and processes for managing and delivering trusted information for decision making, auditing, and regulatory reporting than ever before. [Read more]

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.
[Read more]

In Chris Cingrani's recent post the question: "Data quality, does anyone care?" was posed. The answer is yes, of course people care about data quality – in fact, there are a lot of good reasons why a lot of people should care very deeply about data quality. Let’s look at the most recent example of where data quality makes a big difference, and that is in the federal election process. [Read more]

As a follow up to my Alliances momentum post, I wanted to call attention to a recent OEM partners press release highlighting recent wins with OEM ISV partners leveraging Informatica for their own applications, be they "in the cloud" or on-premise installation based. Much of my time in Worldwide Alliances is spent working with prospective ISVs explaining the benefits of taking a 'buy' approach versus ‘building’ a hand-coded solution for data integration.

I continue to see market evidence that also explains our momentum. If you read the interesting October 20^th InformationWeek cover article entitled, "SaaS Under Stress; Integration's the next big test for software as a service", you’ll understand why SaaS software providers are trying to fill this large gap in their offerings.

This makes perfect sense when you take a step back and think about the moving parts of a SaaS application, namely data that needs to [Read more]

In my last post Business Intelligence, Light and Fast (Part 1), I talked about how Web 2.0 technologies hold a lot promise for the spread of BI. But how are organizations putting this approach into everyday practice? [Read more]

Over the last few months, I have had a number of discussions with clients at various stages of planning a data quality initiative. Some clients are just starting to take the data quality plunge, while others are evaluating how to leverage the successes of past projects into building out a formal data governance initiative. When I start talking to clients about their goals around data quality, I often start with the same basic question, regardless of where they fall from a maturity process around data quality. The question is simply – does the business care?

[Read more]

In the post "SOA's Last Mile Part III: How to Address SOA's Hidden Data-Centric Pitfalls Effectively," David Lyle spoke about some high-level approaches to handling the data-centric pitfalls in an SOA.

I would like to introduce you to the solution…what I call data services, a flexible and cost-effective technology that can be the cornerstone of an SOA and EIM strategy by simplifying the complexity of both integrating diverse enterprise data that exists in individual silos as well as delivering a single, accurate and consistent view of all enterprise information, at the speed of business.
[Read more]