By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics in sports industry
    Here’s How Data Analytics In Sports Is Changing The Game
    6 Min Read
    data analytics on nursing career
    Advances in Data Analytics Are Rapidly Transforming Nursing
    8 Min Read
    data analytics reveals the benefits of MBA
    Data Analytics Technology Proves Benefits of an MBA
    9 Min Read
    data-driven image seo
    Data Analytics Helps Marketers Substantially Boost Image SEO
    8 Min Read
    construction analytics
    5 Benefits of Analytics to Manage Commercial Construction
    5 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: Are You Afraid Of Your Data Quality Solution?
Share
Notification Show More
Latest News
big data mac performance
Data-Driven Tips to Optimize the Speed of Macs
News
3 Ways AI Has Helped Marketers and Creative Professionals Streamline Workflows
3 Ways AI Has Helped Marketers and Creative Professionals Streamline Workflows
Artificial Intelligence
data analytics in sports industry
Here’s How Data Analytics In Sports Is Changing The Game
Big Data
data analytics on nursing career
Advances in Data Analytics Are Rapidly Transforming Nursing
Analytics
data analytics reveals the benefits of MBA
Data Analytics Technology Proves Benefits of an MBA
Analytics
Aa
SmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Are You Afraid Of Your Data Quality Solution?
Uncategorized

Are You Afraid Of Your Data Quality Solution?

JimHarris
Last updated: 2009/04/15 at 8:15 PM
JimHarris
4 Min Read
SHARE

As a data quality consultant, when I begin an engagement with a new client, I ask many questions.  I seek an understanding of the current environment from both the business and technical perspectives.  Some of the common topics I cover are what data quality solutions have been attempted previously, how successful were they and are they still in use today.  To their credit, I find that many of my clients have successfully implemented data quality solutions that are still in use.

 

However, this revelation frequently leads to some form of the following dialogue:

OCDQ:  “Am I here to help with the enhancements for the next iteration of the project?”

More Read

analyzing big data for its quality and value

Use this Strategic Approach to Maximize Your Data’s Value

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing
Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC
Quality Control Tips for Data Collection with Drone Surveying
3 Huge Reasons that Data Integrity is Absolutely Essential

Client:  “No, we don’t want to enhance our existing solution, we want you to build us a brand new one.”

OCDQ:  “I thought you had successfully implemented a data quality solution.  Is that not true?”

Client:  “We believe the current solution is working as intended.  It appears to handle many of our data quality issues.”

OCDQ:  “How long have you been using the current solution?”

Client:  “Five years.”

OCDQ:  “You haven’t made any changes in five years?  Haven…

As a data quality consultant, when I begin an engagement with a new client, I ask many questions.  I seek an understanding of the current environment from both the business and technical perspectives.  Some of the common topics I cover are what data quality solutions have been attempted previously, how successful were they and are they still in use today.  To their credit, I find that many of my clients have successfully implemented data quality solutions that are still in use.

 

However, this revelation frequently leads to some form of the following dialogue:

OCDQ:  “Am I here to help with the enhancements for the next iteration of the project?”

Client:  “No, we don’t want to enhance our existing solution, we want you to build us a brand new one.”

OCDQ:  “I thought you had successfully implemented a data quality solution.  Is that not true?”

Client:  “We believe the current solution is working as intended.  It appears to handle many of our data quality issues.”

OCDQ:  “How long have you been using the current solution?”

Client:  “Five years.”

OCDQ:  “You haven’t made any changes in five years?  Haven’t there been requests for bug fixes and enhancements?”

Client:  “Yes, of course.  However, we didn’t want to make any modifications because we were afraid we would break it.”

OCDQ:  “Who created the current solution?  Didn’t they provide documentation, training and knowledge transfer?”

Client:  “A previous consultant created it.  He provided some documentation and training, but only on how to run it.”

 

A common data quality adage is:

“If you can’t measure it, then you can’t manage it.” 

A far more important data quality adage is:

“If you don’t know how to maintain it, then you shouldn’t implement it.”

 

There are many important considerations when planning a data quality initiative.  One of the most common mistakes is the unrealistic perspective that data quality problems can be permanently “fixed” by implementing a one-time “solution” that doesn’t require ongoing improvements.  This flawed perspective leads many organizations to invest in powerful software and expert consultants, believing that:

“If they build it, data quality will come.” 

However, data quality is not a field of dreams – and I know because I actually live in Iowa.

 

The reality is data quality initiatives can only be successful when they follow these very simple and time-tested instructions:

Measure, Improve, Repeat.

Link to original post

TAGGED: data quality
JimHarris April 15, 2009
Share this Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

big data mac performance
Data-Driven Tips to Optimize the Speed of Macs
News
3 Ways AI Has Helped Marketers and Creative Professionals Streamline Workflows
3 Ways AI Has Helped Marketers and Creative Professionals Streamline Workflows
Artificial Intelligence
data analytics in sports industry
Here’s How Data Analytics In Sports Is Changing The Game
Big Data
data analytics on nursing career
Advances in Data Analytics Are Rapidly Transforming Nursing
Analytics

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

analyzing big data for its quality and value
Big Data

Use this Strategic Approach to Maximize Your Data’s Value

6 Min Read
data lineage tool
Big Data

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing

6 Min Read
data quality and role of analytics
Data Quality

Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC

8 Min Read
data collection with drone use
Data Collection

Quality Control Tips for Data Collection with Drone Surveying

9 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 is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US

© 2008-23 SmartData Collective. All Rights Reserved.

Removed from reading list

Undo
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?