Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    business using business intelligence
    How to Use a Competitive Intelligence Dashboard to Turn Market Data Into Smarter Marketing Decisions 
    9 Min Read
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: DM Radio: EDW Mistakes to Avoid
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > DM Radio: EDW Mistakes to Avoid
Best PracticesData WarehousingExclusive

DM Radio: EDW Mistakes to Avoid

Rob Armstrong
Rob Armstrong
6 Min Read
SHARE

Last week I had the opportunity to participate in a DM Radio interview.  There was a panel of several of us industry types being asked question by the host Eric Kavanagh.  He was assisted this time by co-host Robin Bloor.  The topic was “Mistakes to avoid with an Enterprise Data Warehouse”.  If you missed interview you can follow this link to hear the recording (http://www.information-management.com/dmradio/-10019278-1.html).

Last week I had the opportunity to participate in a DM Radio interview.  There was a panel of several of us industry types being asked question by the host Eric Kavanagh.  He was assisted this time by co-host Robin Bloor.  The topic was “Mistakes to avoid with an Enterprise Data Warehouse”.  If you missed interview you can follow this link to hear the recording (http://www.information-management.com/dmradio/-10019278-1.html).

I bring this up as it was a lot of fun and it was very informative.  As the questions went into several directions I thought I would share with you the other points that I did not have time to get to during the show.  Just a few pointers on mistakes others have made and everyone can learn from rather than make them again.  I have expounded on some of these in earlier blogs but I repeat them  as having in one place is good and you can never hear this enough!

More Read

big data meets artificial intelligence
Big Data Is Already A Thing Of The Past: Welcome To Big Data AI
Data-Driven Custom Web Development is Invaluable to Many Businesses
Analytics: The widening divide. An IBM/MIT Sloan study
Focus, Simplicity and Service
TDWI Boston Chapter meeting on April 9, 2009

[Disclosure: I work for Teradata, which sponsors the Smart Data Collective.]

1) Mistaking Consolidated with Integrated

By this I mean that people try to make an EDW in name only.  They bring the data marts and consolidate them together on a single platform.  They do not do the hard work of actually integrating the data models and removing redundancy or inconsistency.  Yes, they may be able to get some new functionality and perhaps some marginally better analytics.  However, they are going to be more problems as users start to really be exposed to the data issues that then need more, and harder, efforts to resolve.

2) Mistaking “Phase 1 success” with “Foundational success”

This is what I describe as “short term gain but longer term pain”.  Many companies will have a very good plan to start the EDW but then when push comes to shove they will compromise the data model or eliminate data quality or IT checkpoints in order to get “Phase 1” complete.  Unfortunately they often end up not being able to leverage the phase 1 success into an on-going sustainable, evolutionary, information environment.

3) Mistaking Regulation for Governance

Regular readers will recognize this as it was my last blog: (http://smartdatacollective.com/rob-armstrong/37668/governance-if-it-isn-t-logical-it-s-political).  Just repeating the highlights; governance is when the executive groups, IT management and Business owners agree on how the environment will be prioritized, managed, managed, and utilized.  Regulation is when there is a rule for e very conceivable situation and each new issue generates yet another (sometimes conflicting!) rule.  This leads to an over cumbersome set of processes which then kills innovation and forward movement of the data warehouse.

4) Mistaking Report for Action

The goal of the data warehouse is to provide business users insight into situations so they can take action and either avoid a problem or very quickly identify and resolve a problem.  Too many people start using the system for reporting and then fail to move forward for several of the above reasons.  Reports simply tells what happened to far after the fact to actually impact the business in a serious way.  The data warehouse has to be able support analytics in the heat of the moment from a wide variety of viewpoints, after all that is what the E stands for in EDW.

5) Mistaking Projects with Programs

An enterprise data warehouse needs to be seen as a corporate wide program that deals with the integration, management, and usage of the data.  Unfortunately the EDW is initially treated as another IT project, at the benefit of one group, and it carries the funding and governance aligned to a project focus.  The downfall is that very few projects care about data integration across the enterprise.  As the EDW tries to evolve there are arguments as to which project will fund the integration?  Which project will fund the management and monitoring of enterprise service level agreements?  Which project will run the data roadmap and quality resolution?  Without a proper, longer sighted, program perspective the EDW is doomed from the start.

So, check out the interview to get some other insights from the other panelists.  Also, look around your organization and information implementation.  Are seeing some of the mistakes listed above?  If so, do you have plans to rectify them and get your efforts back on the right track?

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI driven big data company
How AI-Driven Workflows Are Changing the Way Companies Think About Data Risk
Artificial Intelligence Data Management Exclusive Risk Management
ai product development
Why Businesses Outsource AI Product Development Companies
Exclusive News
banking tools
The Fintech and Banking Tools Global Entrepreneurs Rely On
Fintech Infographic
business using business intelligence
How to Use a Competitive Intelligence Dashboard to Turn Market Data Into Smarter Marketing Decisions 
Analytics Big Data Exclusive Marketing

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

big data payroll
Big Data

3 Common Payroll Errors That Can Be Resolved with AI Solutions

6 Min Read
Analytics

5 Ways To Improve Your Business Skills with Data Analytics

11 Min Read
data analytics and local seo
Analytics

Search Engine Watch Suggests Data Analytics Key To Local SEO Success

8 Min Read
AI and data mining
Artificial IntelligenceBig DataExclusive

What the Rise of AI Web Scrapers Means for Data Teams

15 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?