Informatica Enterprise Data Management

To paraphrase the Paul Simon song, there must be 50 ways to integrate your enterprise data. In recent years, companies have made all kinds of attempts to integrate both their applications and data - employing techniques from sophisticated enterprise application integration projects all the way down to manual hand coding. However, while most of these approaches work at least some of the time, few, if any, are delivering real agility for their businesses.

Recently, I had the opportunity to moderate a Webcast - sponsored by Informatica and hosted by ebizQ - which explored in detail an emerging approach, called data services, which ties into service oriented architecture (SOA) and creates a data abstraction layer that addresses the complexities seen across enterprise data environments.

Leading the Webcast were Ash Parikh, principal product marketing manager for Informatica and a highly regarded industry speaker and author, and David Ramos, director of business intelligence and analytics for LinkShare Corporation.

In his presentation, Ash urged closer collaboration between the enterprise data management and emerging service oriented architecture (SOA) worlds. (John Schmidt recently provided a nice overview of SOA here at the EDM blogsite.)

Ash observed that current approaches to enterprise data management have worked well from an application point of view, but have been ineffective for enterprise data. [Read more]

It seems in recent years pundits and vendors alike have been applying the 2.0 label to everything and anything emerging across the technology plain. In some cases, the new label has stuck - witness the widespread adoption of the terms 'Web 2.0' and its business sibling, 'Enterprise 2.0.'

In some cases, it’s a case of marketecture, but yet, the 2.0 identifier does convey a certain sense of maturity – that a technology is moving to a new stage of sophistication, of engagement with the business and its end users.

There have been moves afoot to identify the next generation of data warehousing as "Data Warehouse 2.0." However, there are differences of opinion as to what exactly will constitute DW 2.0, and thus no clear standard sense of direction in the market. [Read more]

Are BI managers and professionals sometimes too eager to please the business? Are centralized BI efforts slowing down progress? Should BI teams address requirements before the business even asks for them? These questions may seem counter-intuitive, but Wayne Eckerson, director of research for TDWI, says that the best intentions for BI efforts in many organizations may actually result in sluggish projects, duplication of effort, and misaligned priorities between BI teams and the business. [Read more]

There’s no question that integrating analytical and transaction data to deliver “Pervasive Business Intelligence” can be a significant project for many enterprises. However, the good news is that it’s a capability that’s within the reach of many enterprises today. That’s the gist of a Q&A with three industry thought leaders, published in the latest edition of Intelligent Enterprise. [Read more]

I’ll admit it, as an older brother, I didn’t want my younger sister borrowing or bugging me for my prized possessions. I still hoard things at work, old computer equipment, mice, cables, all in the name of finding a use for them at some point. I just like to know they are there when you need them as you can see here.

Is data treated the same way within corporations? Do application owners like sharing their data with others? In my experience, no, they don’t. Ask any mainframe or ERP program manager about utilizing their production data for other purposes and I’m sure you’ll receive a litany of questions around impact to production systems, utilization costs, and complexity of access. And IT’s business request list for access to these precious resources is only growing. For many organizations, data access is a cultural problem.
[Read more]

Since launching the EDM blog in early 2007, we have focused on a wide variety of data management, Informatica usage and technology topics. In 2008, I will also be discussing my experiences and research in Enterprise Data Warehousing, an area that our customers have used our software and solutions to great success.

Enterprise Data Warehousing is a term that has been around for a long time. In the mid-90’s, Bill Inmon preached an enterprise approach to data warehousing that was based on a central repository of corporate data. With the technology at the time, success was only attainable by a few elite organizations at extreme levels of funding. Informatica pioneered an incremental data mart approach that led to years of prosperity in the Data Warehousing market for Informatica and customers using our technology for their data warehousing related projects.
[Read more]

The recent Informatica Release 8.5 launch highlighted Real-time Integration Competency Centers (ICCs) as the optimal model for successful data integration. I’d like to review the concept of the Real-time ICC and why Release 8.5 supports this advanced operational, organizational and technology model.

As data integration moves beyond the realm of data warehousing into operational integration, real-time and data services use cases have exploded in importance to the business and necessitated stronger, unified infrastructure for IT to meet the challenge. Philip Russom, Senior Manager, TDWI Research captures this trend specifically in his quote on Release 8.5.

"The movement toward real-time data access and delivery has been the most influential trend in data integration this decade. The trend has enabled user organizations to initiate a variety of valuable real-time practices, including operational BI, real-time data warehousing, on-demand computing, performance monitoring, just-in-time inventory, and so on. And the trend has led vendors to extend their data integration products, so that many functions operate in real-time, not just batch. Informatica 8.5 is a great example of this trend, because it’s re-architected to support more real-time and on-demand functions for data integration, changed data capture, and data quality." [Read more]

We’ve been discussing the three pillars of an ICC, organization, process and technology, for a while now. In this segment, I’ll focus on a range of technology requirements facing ICC implementations teams, whether they are starting from scratch or morphing a set of disparate solutions into a common infrastructure. It goes without saying, to meet the demand of a broader set of enterprise needs rather than those of a single line of business, the infrastructure powering an ICC needs to evolve and mature.

High Availability
One of the first aspects related to infrastructure is the need for high availability. This pertains to the overall integration infrastructure environment. “Shared Infrastructure” by its very nature increases the need for reliability. An outage of a single point solution is acceptable and explainable but when several organizations are relying on solutions delivered by an ICC, outages can significantly impact revenue and productivity.

[Read more]

When I teach data integration concepts in my classes at various corporations or to my students at Northeastern University, one of the topics I address is the differences between engine-based and database-based data integration tools.

You may be more familiar with their other names:

• ETL (extract, transform and load) or engine-based
• ELT (extract, load and transform) or database-based tools

Inevitably, someone asks me which one is best. I have answer on two levels. The first answer is that neither is the best under all circumstances but depends entirely on the data integration scenario that is being addressed. Evolving industry trends are causing enterprises to often need both alternatives in order to best meet their full range of data integration needs.

The second part of the answer is that up until recently you could not compare ETL versus ETL purely on their own merits because the data integration tools that typically performed either approach tended to operate on two ends of the spectrum.
[Read more]

One of the best ways an organization can accelerate integration projects and recoup investment in infrastructure, people and implementation costs is through reuse of assets produced in previous integration projects. In my experience, “Re-Use” is often touted by vendors in the data integration marketplace but very little information is truly published in this area. Why is that the case?

For one reason it is an “after the fact” measurement attainable only where technology is used over time to deliver on multiple projects. It also means different things to different people. “Re-Use” in one technology context may be simplistic copying of objects within a design interface, saving time and effort but only a micro-scale. “Re-Use” in another technology context may mean “complete project section” reuse where surrounding environmental ties of a project implementation are removed and large blocks of implementation are repurposed across efforts. The latter is a more powerful concept, truly leveraging large amounts of previous work and making change faster, and more accurate. SOA is certainly driving more examination of this topic as well, some positive, some negative. [Read more]