Archive for October, 2008

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Go green with CDI

Tuesday, October 28th, 2008
Green Globe

How much paper was used to deliver three copies of your glossy brochure in the same household? Every tried to estimate the impact on our environment of all the undeliverable direct mailers? How much fuel consumption can be reduced when orders  delivery can effectely be grouped together by geographic location?

Being more environmentally friendly is going to be a huge topic in the next few years. Effective data quality and customer data integration can go a long way into making a difference. A totally business to how we look at investing in these areas at this moment.

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Data Quality and SOA – how do they interact

Monday, October 27th, 2008

Service Oriented Architecture (SOA) has gained much popularity in the past years as the model for application development that uses groups of services that are orchestrated around business processes. SOA involves more than just the manner in which applications are deployed and interact with each other – it also involves how they interact with data. 

SOA

SOA

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Cloud Computing Entering Period of Accelerating Adoption

Thursday, October 23rd, 2008

Last week I made a post on a Gartner Survey that showed increasing SaaS momentum in the economic down-turn. Well, the industry analyst seem to be tumbling all over each other to report on the accellerating pace of SaaS adoption, especially in relation to the current situation.

A couple of days ago IDC published a press release on cloud computing and how it is reshaping the IT marketplace. 

Some major points I think are very interesting:

  • Cloud computing is “crossing the chasm” and entering a period of widespread adoption
  • IDC expects the cloud adoption trend to be amplified by the current financial crisis
  • IT cloud services to grow almost threefold, reaching $42 billion by 2012
  • More importantly, cloud computing will account for 1/3 of IT growth in 5 years

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Citizen Data Integration failed…

Thursday, October 23rd, 2008

Just before the upcoming elections in the United States on November 4th many voters have fallen victim to incorrect voters registration. It might well involve over hundred thousands of voters.

The Help America Vote Act was passed in 2002 in order to prevent voter registration and voting counting problems which happened with the presidential elections in 2000. One of the measures was to create centralized databases, which allow voters to check their registrations. In rolling up and centralizing local databases to state databases many mishaps have occured. Resulting in thousands of voters who are now not eligible to vote. These people have to reestablish their eligibility to vote in the coming weeks.

Click here for the full article in the Washington Post.

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Seven tips for success in implementing CDI

Wednesday, October 22nd, 2008

Jill Dyché, an expert on Customer Data Integration, was asked about the most common mistakes and obstacles when organizations want to implement CDI. For the complete article please follow this link. She came up with 7 very usefull tips:

1) Anticipate the saboteurs. With CDI there will be people in your organization claiming that “we already do that with our data warehouse/ODS/CRM system/toothpicks-and-glue.” Anticipate their arguments and educate them, offering deliberate examples of why they’re full of it. Nicely, of course.

2) Articulate more than one business problem that CDI can solve. You want to position your CDI effort as an ongoing program that can enable different business needs. If you position CDI as a one-trick pony (for instance, it can handle identity resolution), you’ll only be able to ride that horse for so long…

3) Know your functional requirements. It never ceases to amaze me how quickly companies want to enlist vendors. “We’ve gotten everyone in a room and we know what we need,” they explain as they cherry-pick brochures off of vendor websites and schedule proofs of concept (POC). Not so fast! At best, this is a well-intentioned attempt to fill in the blanks by talking to smart vendors. At worst, it’s tire-kicking in a vacuum. Unlike with business intelligence (BI), master data management (MDM) requires a huge and measured focus on functional requirements. Until you have your list in hand, you won’t be able to give the vendors what they need to deliver the goods.

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SaaS momentum in economic down times

Friday, October 17th, 2008
Man

Jeff Kelly from SearchDataManagerment.com writes about the momentum of SaaS based data quality and integration tools. With quotes from a survey done by research firm Gartner he writes about how “the on demand model is beginning to gain foothold in the industry”.

A few remarkable facts from the Gartner survey:

  • 28% of companies have deployed SaaS-based data integration tools
  • 24% have SaaS-based data quality tools
  • Most companies use a mix of on-premise, outsourced and SaaS-based technology
  • SaaS-based software, at this point, often trails its on-premise counterparts
  • Gartner advice: “Plan SaaS deployment enterprise-wide….to guard against siloed investments”

(more…)

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My next book I’ll read

Thursday, October 16th, 2008

Planet Google (Book)

A new book by Randall Stross is out (6th October 2008); it’s called “Planet Google” and covers Google’s beginnings but also their latest actions and troubles. Some quotes from the book triggered me. I hope Google Health will be addressed also.

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What your data tells you about your processes

Thursday, October 16th, 2008
Do you know exactly what the data processes in your company look like? Many people have a general overview of the processes. Others have a detailed view of some of these processes.  Few people know all data processes in detail.

 

HI Survey Results

HI Survey Results

Looking at the data can give you deeper insight in your data processes. Not only the processes in theory, but in practice too. How? By focusing on the exceptions! (more…)

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Data quality processes: The wrong guy

Thursday, October 16th, 2008

As a recent Human Inference survey shows, data quality processes appear to be the biggest challenge for organizations.  Although this may seem an obvious survey result for many, the real question here of is: What are data quality processes?

Many of you will probably start thinking along the lines of data ownership, database access and hierarchy. But data quality processes are far more essential.  First of all, you have to know who you are dealing with.The following video is self-explaining:

The wrong Guy

 

 

 

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Budget for Data Quality seems no problem

Thursday, October 16th, 2008

A survey of Human Inference in 2008 indicates that processes are the biggest experienced challenge in relation to Data Quality. However the subject that seems to be no problem is the budget. Human inference differentiates itself by interpretation of knowledge. So from this perspective I wonder how the respondents interpreted the word “processes”. Do they mean the processes within the value chain of their companies or do they actually mean the process of obtaining a budget for Data Quality? The latter would actually explain a lot.

HI Survey Results

HI Survey Results

 

 

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