Informatica Data Services

This blog post focues on the typical data-centric challenges that SOA and BPM deployments face. Without accurate, consistent and timely information, SOA and BPM cannot effectively deliver on their promise. I look forward to your take on this.

 As we know, SOA uses a simple Web services paradigm to address high-level application integration and business process orchestration, but it cannot address more granular data issues. Semantic inconsistencies, inaccuracies, diverse data formats and access mechanisms, varying requirements for data latencies and volume are some examples. Typical SOA and BPM deployments assume the availability of readily consumable information. This introduces the costly risk of data inconsistency and inaccuracy surfacing later and undermining the business and IT value of an SOA or a BPM initiative.

I think that in order to maximize the business and IT value of an application-centric integration strategy, organizations need to look closely at data integration challenges, requirements, and prospective solutions. Focusing on application-centric integration approaches like SOA, BPM, EAI, and ESB which promise agility, unless complemented by sophisticated data integration platform,  most likely will fail to deliver on that promise. The platform has to deliver holistic and accurate information as a service to consuming applications and business processes, exactly at the speed and latency needs of the business. Our Real-Time resource center looks at this in more detail.

What do you think about real-time or right-time data integration? Do you agree that without considering an organization’s flexible latency needs (from batch to real-time), business agility is at risk?

Ted Friedman, VP Distinguished Analyst, Gartner recently stated, "Most important for organizations to recognize is that their data integration will require a mix of latencies — while real-time activity is on the increase, there will always be a need for higher-latency data integration work, since not all data in the architecture changes frequently, and not all processes, teams and roles are capable of harnessing real-time data."

Do you agree? What’s been your experience?

This blog post features a link to an article that appears in the June 2008 issue of DMReview Magazine, written by David and myself. We look forward to hearing your thoughts and input on the subject.

This article introduces you to a data services platform as the most efficient approach for enabling business agility across the enterprise, through the delivery of right-time information, be it information delivered in batch, near real time or real time. As you will read in the article, with a data services platform you can enable scalable access, integration and right-time delivery of business-critical information to enterprise-wide composite applications. We have also tried to explain how a data services platform can maximize business value using right-time information for driving competitive advantage, lowered risk and cost-effective project implementations.

Read on…
Maximize Business Value through Right-Time Information Using Data Services - DMReview Magazine

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.

Last posting, I ranted about the fact that ‘data’ is finally a topic of discussion with respect to SOA initiatives. SOA provides business services that at their deepest level interact with data. What are the data-centric pitfalls that SOA can run into?

First off, data has meaning. While an enterprise ‘meaning’ can be presented by the services to outside consumers of those services, someone has to deal with the fact that the foundational business systems may have different meanings for the underlying data. The ‘transformation’ is frequently very important and complex.

Secondly, the meaning of data can change over time as the business changes. These changes will impact the services and the ‘transformations’ mentioned above. And sometimes these changes will affect the users of the services.

Thirdly, the quality of data is not perfect. How do you deal with these imperfections?

Fourthly, the systems of record for data are not usually neatly compartmentalized. At most complex enterprises, there isn’t just one Order Management system, or one HR system. The concepts of Customer, Policy, Employee, etc., can be spread across many heterogeneous systems, with overlapping responsibilities.

I’m sure there’s a fifth, a sixth, etc. But let’s just elaborate on these four. [Read more]