Tag Archives: Architecture

Data Integration Career Architecture

Those who understand data integration and the supporting technology are in high demand. Why? The need to create data synergy within enterprises, among both traditional and cloud computing-based data and applications, is inflecting. This is due to a more clearly understood business benefit around the value of data integration.

The ability to have information arrive on-time and when needed has been a fundamental need of IT since I wrote the EAI book over a decade ago. However, in the last few years, systems became more complex, including the complexity of the data that exists within them. In response, data integration grew more complex, the technology more sophisticated, and thus the increase in the demand for data integration talent.  (more…)

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Why is the New SOA Data Integration Architecture Group on a Roll?

Because there is real need! Period! Even after investing heavily in agile architecture approaches such as SOA, IT organizations are finding it extremely challenging to solve complex data integration issues.

If you are involved in defining or re-defining a data architecture to enable composite applications and portals to effectively leverage data in an SOA, here is where the discussions are happening.

If you are looking to enhance your existing data architecture to ensure that business intelligence reports can quickly leverage data that is not in your data warehouse, you will find your answers here.


Posted in Data Integration, Data Services, Data Warehousing, Enterprise Data Management, Integration Competency Centers, Real-Time, SOA | Tagged , , , | 1 Comment

Do The Math: Platform Approach Adds Up As The Superior Alternative To Multidomain MDM

A couple of weeks back I posted on the shortcomings of the application approach to multidomain MDM, so this week let’s take a look at the many reasons why the platform approach is the superior alternative for effective multidomain MDM. The primary technological difference between the two approaches is that MDM “applications” typically employ a predefined data model, business logic, and a dedicated graphical user interface (GUI) tied to solving a single business problem, whereas platform-based MDM allow users to create and use flexible data models, configure it to suite any business logic, and provide visibility across any number of business processes via a single user interface. (more…)

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Rethinking Data Virtualization

I’m looking forward to doing a Webinar on data virtualization this Thursday, April 22nd.  Why?  Because this is the single most beneficial concept of architecture, including SOA, and it’s often overlooked by the rank-and-file developers and architects out there.  I’m constantly evangelizing the benefits of data virtualization, including integrating data from many and different data sources in real-time, and enabling query-based applications to get data from multiple systems.

The idea is pretty simple, really.  Considering that there are many physical database schemas within most enterprises, and typically no common view of the data, data virtualization allows you to map many physical schemas to virtual schemas that are a better representation of the business.  For example, a single view of customer data, sales data, and other data that has the same logical meaning, but may be scattered amongst many different physical database systems, using any number of implementation models. (more…)

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The Achilles Heel Of Cloud Computing – Data Integration

Loraine Lawson did a great job covering the topic of the integration challenges around the cloud and virtualization. She reports that “…a recent Internet Evolution column [by David Vellante] looks more broadly at the cloud integration question and concludes that insufficient integration is holding up both cloud computing and virtualization.”

In fact, what currently limits the number of cloud deployments is the lack of a clear understanding of data integration in the context of cloud computing. This is a rather easy problem to solve, but it’s often an afterthought.

The core issue is that cloud computing providers, other than Salesforce.com, don’t consider integration. Perhaps they are thinking, “If you use our cloud, then there is no reason to sync your data back to your enterprise. After all, we’re the final destination for your enterprise data, right?” Wrong. (more…)

Posted in Cloud Computing, Customers, Data Integration, Data Warehousing, Master Data Management | Tagged , , , , , , | 12 Comments

What’s The Importance Of Informatica 9 To The CIO?

Informatica 9As a CIO, I am a strong proponent of Enterprise Architecture (EA) and the components of EA articulated by Steven Spewak. Eight years ago, I would sit with the Informatica R&D Chief Architect and describe what I needed to realize our IT architectural vision, as well as the problems I wanted to overcome.

So, what were the problems I wanted addressed?

First, I am a believer of a best of breed strategy. I fundamentally believe the “megavendors” are dictating IT strategy, yet they cannot innovate fast enough – thereby harming IT. To build a best of breed approach, I wanted to build a loosely coupled architecture. In essence, I wanted to abstract the data away from the applications we ran, thereby enabling me to switch vendors if necessary. This would enable me to provide the best solutions to our business as well as maintain negotiating leverage with my vendors. The challenge is that no technology existed to do this cost effectively. (more…)

Posted in Business/IT Collaboration, CIO, Data Integration, Data Integration Platform, Data Quality, Master Data Management, News & Announcements | Tagged , , , | 1 Comment

Slowing Down, and Other Counter-Intuitive Steps to Agile BI

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. (more…)

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New Competitive Weapon: Pervasive BI and the Culture of ‘Now’

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. (more…)

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Get Ready for Informatica World 2008 – Las Vegas

I’m already making my flight arrangements for the 10th Annual Informatica World Conference in Las Vegas this year. (more…)

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Real-time Integration Competency Centers – What are they?

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.” (more…)

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