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
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Importance of Scope In Data Quality Efforts
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Exclusive > The Importance of Scope In Data Quality Efforts
Exclusive

The Importance of Scope In Data Quality Efforts

JillDyche
JillDyche
4 Min Read
SHARE

When it comes to data quality, I fervently believe that it is destined for widespread adoption. As a concept data quality has been around for a while, but until now it’s only truly been appreciated by a group of aficionados.  But just like taco trucks, the HBO show “In Treatment,” video on demand, and Adam Lambert, data quality’s best days are actually ahead of it. 

Part of the reason data quality hasn’t yet its stride is because it remains a difficult sell. Those of us in the business intelligence and data integration communities understand that accurate and meaningful data is a business issue. And well-intentioned though they may be, IT people have gone about making the pitch the wrong way.

We—vendors,  consultants, and practitioners in the IT community…

More Read

importance of data loss prevention
Why Is Data Loss Prevention is Crucial for Business?
What Are OLAP (Online Analytical Processing) Tools?
Big Data Leads to the Possibility of a Cashless Society
Administering Data Fabric to Overcome Data Management Challenges.
5 Ways Where Data-Driven Analytics Reshaped The Software Industry



 

When it comes to data quality, I fervently believe that it
is destined for widespread adoption. As a concept data quality has been around
for a while, but until now it’s only truly been appreciated by a group of aficionados.  But just like taco trucks, the HBO show “In
Treatment,” video on demand, and Adam Lambert, data quality’s best days are actually
ahead of it. 

Part of the reason data quality hasn’t yet its stride is
because it remains a difficult sell. Those of us in the business intelligence
and data integration communities understand that accurate and meaningful data
is a business issue. And well-intentioned though they may be, IT people have
gone about making the pitch the wrong way.

We—vendors,  consultants,
and practitioners in the IT community—blather on about data quality being a business
issue and requiring a business case and a repeatable set of processes but at
the end of the day automation remains the center of most data quality discussions.
As we try to explain the ROI of name and address correction, deterministic matching,
multi-source data profiling, and the pros and cons of the cloud, business
executives are thinking two things:

1: “Jeezus I’m
bored.”

2. “I wonder
how we would we start something like this? Where would we begin?”

In fact the topic of scope is a huge gaping hole in the data
quality conversation. As I work with clients on setting up data governance, we
often use the bad reputation of corporate data as its pretext. We always,
always talk about the boundaries of the initial data quality effort. Unless you
can circumscribe the scope of data quality, you can’t quantify its value.

In our experience, there are 5 levels of data quality
delivery that can quickly establish not only the scope of an initial data
quality effort, but also the actual duties and resources involved in the
initial project:

 


By specifying the initial scope of the data to be corrected we’re
establishing the boundaries of the effort itself. We’re also more likely to be
solving a real-life problem. Thus we make the initial win much more impactful,
thus securing stakeholder participation. Moreover where we start our data
quality effort is not necessarily where we’ll finish, so we can ensure an
incremental approach to setting up the program and its roles.

Business executives and users can consume a well-scoped
problem, especially if it makes their jobs easy or propels progress. And if we
solve it in a way that benefits the business—eliminating risk, ensuring economies
of scale, and driving revenues—we might even get budget for a data quality
tool!

TAGGED:business intelligencedata governancedata integrationdata quality
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

The Next Generation BI Professional – Things Will Be Very Different

6 Min Read

NIEMNTE – Vivek Kundra, US CIO on Data Sharing and Quality Issues

4 Min Read

New Generation of Location Analytics

5 Min Read

Tufte Shares Wisdom for Data Presenters

4 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 and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?