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: Martha Stewart and Data-Centricity
Share
Notification Show More
Latest News
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
anti-spoofing tips
Anti-Spoofing is Crucial for Data-Driven Businesses
Security
ai in software development
3 AI-Based Strategies to Develop Software in Uncertain Times
Software
Aa
SmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Quality > Martha Stewart and Data-Centricity
Data QualityPolicy and Governance

Martha Stewart and Data-Centricity

GwenThomas
Last updated: 2011/06/03 at 11:38 AM
GwenThomas
5 Min Read
SHARE

One of the LinkedIn Groups I participate in has spent the past two months discussing the following question: “Respect for data – are we beginning to see a shift from application centric to data centric enterprises?

One of the LinkedIn Groups I participate in has spent the past two months discussing the following question: “Respect for data – are we beginning to see a shift from application centric to data centric enterprises? Has the revolution started or am I just imagining?”  

And finally – as such discussions often do – the topic veered toward the need for Data Governance. Person 1 suggested the need for a rule that would, in effect, force respect by requiring projects that impacted reference data to gain approval for their approach from a data-centric governance board. Person 2 concurred, adding  ”Without Data Governance you have no controls in place. Without controls you’ve lost.”  

This is such a common situation. Violent agreement for the need for governance, but not the meaning. Person 1 is looking at POLICIES, while Person 2 is embracing the need to enforce _policies_. Both are important, but any stakeholder who is just grasping the idea of making data-centric decisions rather than application-centric ones might be confused.

More Read

analyzing big data for its quality and value

Use this Strategic Approach to Maximize Your Data’s Value

Niche Data Tactics to Take Your Business to the Next Level
Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC
Encryption Importance in the Age of Data Breaches
What Tools Do You Need To Manage Unstructured Data?

At the Data Governance Institute, we’ve started using the term “Big G” Governance to describe the policies, mandates, rulings, and rules of engagement that come from on high (wherever that is). An example is the rule that Person 1 suggests: Any project with a linkage to reference data is reviewed by a Board for a determination of whether the project is introducing data-related risk. Another such “Big G” Governance ruling might be that controlled reference data sets can be duplicated ONLY IF certain criteria are addressed that would ensure that the data stays in sync.

Of course, nobody wants bureaucracy, and “Big G” Governance never exists for its own sake. I had to agree with Person 2 in the discussion that data-related controls are what we’re ultimately aiming for. Controls need to be embedded  in projects, processes, data flows, applications, and information management practices to ensure that the data and the people who touch it adhere to policies, standards, rulings, and rules of engagement. Here, down in the trenches, our objective is to institute a series of “little g” governance control points.

Of course, it can be tricky to translate policy to practice, so much of the work of Data Governance teams takes place in the all-important alignment layer between “Big G” and “little g” efforts. This is where stakeholders, subject matter experts, and experts get together to decide how to embed and enforce controls.

Application-centric or data-centric? The implementation of many “little g” governance efforts continue to be considered and managed from an application-centric point of view. That’s fine, as long as they’re the appropriate controls.

What I see changing, though, are awareness levels of mid-level and senior-level consumers of information.More and more of them seem to understand that:

  • Inadequate Reports/BI/Analytics can result from inadequate “little g” governance controls.
  • The people down in the trenches who work with those controls often get contradictory instructions, and that a key to aligned controls is aligned decision-making by managers and architects.
  • Alignment activities require enforceable rulings and a certain level of empowerment to interpret them, embed them, and enforce them. 

So these under-served stakeholders are calling out for data-centric “Big G” rules, rules of engagement, and councils to address gaps, overlaps, and conflicts.And – as Martha Stewart so famously says – “That’s a good thing.”

GwenThomas June 3, 2011
Share this Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

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
anti-spoofing tips
Anti-Spoofing is Crucial for Data-Driven Businesses
Security

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
niche data tactics for business success
Big Data

Niche Data Tactics to Take Your Business to the Next Level

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 encryption importance
Risk Management

Encryption Importance in the Age of Data Breaches

6 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 is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

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?