Tag Archives: Architecture

From RASP to Agile

If you have been following publications in the Potential at Work Community or any number of Linkedin discussions such this one on the DrJJ group (a think-tank for information management best practices), you will have noticed the Agile methodology topic come up time and time again. For instance, check out the article Architect Your Way From Sluggish to Speed or the video Focus on Agility Adaptability.  It hasn’t always been this way. For many years the architectural focus was on RASP.

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Posted in Data Integration, Enterprise Data Management, Integration Competency Centers | Tagged , , , , , | Leave a comment

Ten Facets of Data Governance

In this video, Rob Karel, vice president of product strategy, Informatica, outlines the Informatica Data Governance Framework, highlighting the 10 facets that organizations need to focus on for an effective data governance initiative:

  • Vision and Business Case to deliver business value
  • People
  • Tools and Architecture to support architectural scope of data governance
  • Policies that make up data governance function (security, archiving, etc.)
  • Measurement: measuring the level of influence of a data governance initiative and measuring its effectiveness (business value metrics, ROI metrics, such as increasing revenue, improving operational efficiency, reducing risk, reducing cost or improving customer satisfaction)
  • Change Management: incentives to workforce, partners and customers to get better quality data in and potential repercussions if data is not of good quality
  • Organizational Alignment: how the organization will work together across silos
  • Dependent Processes: identifying data lifecycles (capturing, reporting, purchasing and updating data into your environment), all processes consuming the data and processes to store and manage the data
  • Program Management: effective program management skills to build out communication strategy, measurement strategy and a focal point to escalate issues to senior management when necessary
  • Define Processes that make up the data governance function (discovery, definition, application and measuring and monitoring).

For more information from Rob Karel on the Informatica Data Governance Framework, visit his Perspectives blogs.

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Posted in Data Governance | Tagged , , , , , , , , , , , , , | Leave a comment

Reasons You Need a Data Integration Strategy When Deploying on Cloud-Based Systems

Those moving to cloud computing have their work cut out of for them.  They need to pick a parcel of data, applications, or both to migrate to a cloud-based service.  Or, perhaps build a system from the ground up on a cloud platform.

In any event, you need a few things to insure success, including a good architecture, a deployment plan, and a sound data integration strategy.  (more…)

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Posted in Cloud Computing, Data Integration | Tagged , | Leave a comment

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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Posted in Data Integration, Informatica University | Tagged , , , | 1 Comment

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.

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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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Posted in Data Governance, Enterprise Data Management, Master Data Management | Tagged , , , , , | Leave a comment

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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Posted in Data Integration, SOA | Tagged , , , , , , , | 4 Comments

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…)

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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…)

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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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Posted in Data Integration, Data Warehousing, Enterprise Data Management, Integration Competency Centers | Tagged , , , , , , , , , | Leave a comment