Informatica Perspectives

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]

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]

This blog post is part two of an ongoing series highlighting the importance of data in a Service-Oriented Architecture (SOA). I look forward to hearing your thoughts and input on the subject.

I'm back. It's been a little longer than normal, longer than I would have liked. Perhaps that’s because 'addressing SOA's data-centric pitfalls' isn’t easy. (Really it’s because I’ve been working on other things. But let’s get back to the topic at hand.)

One of the benefits of the SOA approach is the ability to think top-down about problems. The usual approach is to work tightly with the business to define your processes from a business perspective, leading to clearly defined services that the business understands and you can implement together.

This is wonderful and has a clarifying symmetry that Software Engineering has been trying to achieve since the days of CASE. But now, here we are in 2008 with the SOA standards defined and the tools available to potentially achieve this vision. Ah, finally, the integration hairball will be contained and life will improve immeasurably for all!

But as I talked about last time, one of the reasons that things aren’t that simple is the data-centric pitfalls. And addressing this problem is not easy if you want to take a long-term, enterprise-oriented approach.

In talking with folks who have walked down this path, struggled with data problems, and are trying to think holistically about a workable longer-term solution, three themes come up again and again: [Read more]

If banks and financial institutions had invested in more data integration and business intelligence tools to spot issues arising within their portfolios, could they have avoided the recent credit mess?

Perhaps, to a degree. But it is human beings that are ultimately making the risk judgments, and oftentimes, bad decisions may have looked good at the time they were made.

Still, technology has improved to the point where troubles could have been more effectively flagged. [Read more]

Years, ago, I came across this question in an article in Boardroom Reports:  "What do you call a hamburger that’s 99% meat and 1% garbage?"

The answer was a "garbageburger." In other words, even if a small fraction of the burger is tainted, the whole meal is tainted. The original analogy was being used to illustrate the challenges of time management, but it's an apt analogy for data environments as well. That is, if a portion of the information is bad or unreliable, trust in all the data eventually breaks down. In essence, many implementations of service-oriented architecture (SOA) taking place across companies may be garbageburgers because they are serving up unreliable information – an element that has been out of the control of SOA designers.

Sorry if I ruined anyone’s lunch, but the point had to be made. [Read more]

Just as they say success is 10% inspiration and 90% perspiration, it can also be said that the success of a data integration project is 10% technology and 90% chemistry. And when I say chemistry, I'm not talking about hydrocarbons and nitrates, but the chemistry of people.

The success of any complex data integration depends on how the people that make things happen - the teams of administrators, analysts, managers, end-users, and business partners - can collaborate in establishing the business case, setting requirements, selecting technology, and putting all the pieces together.

However, two of the key players in data integration - analysts and administrators - don't necessarily see eye to eye, and this is costing enterprises in terms of staff resources and quality. [Read more]

"Despite certain rumors to the contrary, data warehousing is thriving."

I couldn't agree more with Judy Ko in her recent post, in which she points out that predictions that data warehousing was going to be abstracted away — by service-oriented architecture (SOA) and other new approaches — didn't quite pan out. Instead, if anything, the need for data warehousing solutions only continues to grow. Data volumes are growing, and businesses are demanding ever-more sophisticated business intelligence and analytics to run against that data.

If anything, approaches such as SOA promise to greatly enhance - not replace - data warehousing, [Read more]

In one of my earlier posts I discussed the need for a sophisticated data services-driven technology serving as the foundation for SOA and BPM.

When I was poking around the web recently, I ran into a powerful statement by Michael Blechar from Gartner, covered in the DAMA keynote, titled Survival of the Data Management Fittest:

"Data and processes are intertwined. It will fundamentally change the way organizations think about your roles, and your roles are going to need to evolve".

At this year’s Data Management Association (DAMA) International Symposium,
Michael is quoted saying that:

"In this world there's a very loosely coupled user interface from the assembled services that in turn share access to data. SOA exposes data issues to more people, places and processes, and what I tell companies is that without a focus on information management and meta data management they're going to fail."

It is in speaking to numerous customers, prospects and technologists that I had gathered that without accurate, consistent and timely information, SOA and BPM deployments will face serious information-centric hurdles, affecting the cost-effectiveness and success of the project. As we move towards more agile architectures, I believe that we need to grow typical process-centric approaches to include information centricity as well.

As Michael states:

"Where we are going is beyond the first generation of BPM and SOA [that is process-centric]," he said, "to the next generation of SOA that is information-centric."

Observe that the key word here is "information-centric." Reading such statements from Michael and many others definitely validates the strategy I have been defining for building out an effective IT infrastructure that can benefit from the flexibility of a services and process-driven approach, in the data integration layer. Simply wrapping data access with a web service does not qualify as a sophisticated data service and hence, stringing together such simple services with a BPM tool also does not guarantee agility.

As discussed in Services to Orient your Enterprise Data Layer, Joe McKendrick is of the opinion that neither SOA nor enterprise-application integration alone can effectively handle the enterprise data layer. However, data services delivered within an SOA framework can create a data-abstraction layer to address the complexities seen across enterprise data environments.

I have always said that without serving up good quality, consistent and timely information as a data service or a comprehensive data service built using a sophisticated data integration platform, SOA and BPM deployments will not be able to deliver on their promise of agility.

What are your experiences? What kind of information-centric issues have you run into in your service-oriented deployments? Is inaccurate, stale and inconsistent information passing through your IT infrastructure holding you back?

Governance is a tricky and ill-defined area. For example, in the emerging SOA space, listen to the drumbeat of messages from consultants, analysts, and vendors, and the message is clear: Service oriented architecture won’t work without governance.

However, establishing effective governance has been a vexing challenge, with a lot of disagreement and debate amongst governance proponents. [Read more]

There is a lot of worry on Wall Street and Main Street these days. Are we in a mild or severe recession? Is it the next Great Depression? How long will it last? No one knows the answers to these lofty questions, but Forrester Research has been busy recalibrating on the impact the economy is having on IT spending.

First, the good news, IT spending was better in the first half of this year than expected. The bad news, IT spending is being hit adversely now and probably into 2009. According to Forrester Research:

“The economy's affect on IT spending is evident in some specific data points contained in the report: Forty-three percent of firms have already cut their overall IT budgets in 2008 in reaction to the slow down in the global economy, while 24 percent of firms have put discretionary spending on hold. Twenty-eight percent of respondents said the economy has had no impact on their IT budgets.”

“Forrester: Impact Of Economic Downturn On Tech Spending Varies By Region And Sector”, Forrester Research, September 9, 2008

Even under the best circumstances it’s important to maximize the value from your BI/DW projects.  But with these conditions it becomes even more of an imperative.

No one can afford to be sloppy or wasteful in their business intelligence and data integration strategies. Cost cutting and getting by with what you have is the norm.

But mistakes are expensive. Businesses, now more than ever, need to understand who their current and potential customers are as well as how much revenue and profit each product or service line generates. This demands current, consistent, clean and comprehensive data. [Read more]