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
    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
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Top Ten Root Causes of Data Quality Problems: Part 2
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 > Culture/Leadership > Top Ten Root Causes of Data Quality Problems: Part 2
Culture/LeadershipData Quality

Top Ten Root Causes of Data Quality Problems: Part 2

SteveSarsfield
SteveSarsfield
5 Min Read
SHARE

Part 2 of 5: Renegades and Pirates

Part 2 of 5: Renegades and Pirates
In this continuing series, we’re looking at root causes of data quality problems and the business processes you can put in place to solve them.  In part two, we examine IT renegades and corporate pirates as two of the root causes for data quality problems.

Root Cause Number Three: Renegade IT and Spreadmarts
A renegade is a person who deserts and betrays an organizational set of principles. That’s exactly what some impatient business owners unknowingly do by moving data in and out of business solutions, databases and the like. Rather than wait for some professional help from IT, eager business units may decide to create their own set of local applications without the knowledge of IT. While the application may meet the immediate departmental need, it is unlikely to adhere to standards of data, data model or interfaces. The database might start by making a copy of a sanctioned database to a local application on team desktops. So-called “spreadmarts,” which are important pieces of data stored in Excel spreadsheets, are easily replicated to team desktops. In this scenario, you lose control of versions as well as standards. There are no backups, versioning or business rules.

Root Cause Attack Plan

More Read

Image
Quality vs Quantity in Customer Service Analytics
Bringing Big Data to a New Level: The Smart City of the Future [VIDEO]
Top Ten Root Causes of Data Quality Problems: Part Three
Data Design Principles
What does Whale Vomit have in Common with Big Data and Analytics?
  • Corporate Culture – There should be a consequence for renegade data, making it more difficult for the renegades to create local data applications.
  • Communication – Educate and train your employees on the negative impact of renegade data.
  • Sandbox – Having tools that can help business users and IT professionals experiment with the data in a safe environment is crucial. A sandbox, where users are experimenting on data subsets and copies of production data, has proven successful for many for limiting renegade IT.
  • Locking Down the Data – A culture where creating unsanctioned spreadmarts is shunned is the goal.  Some organizations have found success in locking down the data to make it more difficult to export.


Root Cause Number Four: Corporate Mergers

Corporate mergers increase the likelihood for data quality errors because they usually happen fast and are unforeseen by IT departments. Almost immediately, there is pressure to consolidate and take shortcuts on proper planning. The consolidation will likely include the need to share data among a varied set of disjointed applications. Many shortcuts are taken to “make it happen,” often involving known or unknown risks to the data quality.
On top of the quick schedule, merging IT departments may encounter culture clash and a different definition of truth.  Additionally, mergers can result in a loss of expertise when key people leave midway through the project to seek new ventures.

Root Cause Attack Plan

  • Corporate Awareness – Whenever possible civil division of labor should be mandated by management to avoid culture clashes and data grabs by the power hungry.
  • Document – Your IT initiative should survive even if the entire team leaves, disbands or gets hit by a bus when crossing the street.  You can do this with proper documentation of the infrastructure.
  • Third-party Consultants – Management should be aware that there is extra work to do and that conflicts can arise after a merger. Consultants can provide the continuity needed to get through the transition.
  • Agile Data Management – Choose solutions and strategies that will keep your organization agile, giving you the ability to divide and conquer the workload without expensive licensing of commercial applications.

This post is an excerpt from a white paper available here. More to come on this subject in the days ahead.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

fda14abd c869 4da5 943c c036ad8efc2e
How Data-Driven Journalists Are Using API News Apps to Improve Reporting
Big Data Exclusive News
0622cae5 f7d7 4f74 84b5 eabd1a823dca
How Data-Driven Grocery Recommendations Help Shoppers Eat Better With Less Effort
Big Data Exclusive
business recovering from data loss
How Data-Driven Businesses Protect MySQL Databases from Shutdown
Big Data Exclusive
ai driven task management
Reducing “Work About Work” with AI Task Managers
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Building an Analytical Portal to Support Analytical Culture

5 Min Read

Data Integration Processes: It’s Not the Tool, It’s How You Use It

4 Min Read
Smart Data
Best PracticesBig DataData ManagementData QualityDecision ManagementPredictive AnalyticsRisk ManagementSocial Data

Can Smart Data Ensure Cybersecurity and Data Protection?

6 Min Read

Risk and Five Sigma Events – Can They Happen to You?

5 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 and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

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?