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
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
    data analytics for trademark registration
    Optimizing Trademark Registration with Data Analytics
    6 Min Read
    data analytics for finding zip codes
    Unlocking Zip Code Insights with Data Analytics
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Spinal Tap and The Art of Data Management
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Quality > Spinal Tap and The Art of Data Management
Data Quality

Spinal Tap and The Art of Data Management

MIKE20
MIKE20
3 Min Read
SHARE

Contents
ConsiderationsFeedback

Here’s a dirty little about data management: It’s about art as well as science. In this post, I discuss how many people often mistakenly focus on the “science” of things while minimizing the art piece.

More Read

Why Does Data Decay so Fast?
The Data Outhouse
Investigating the Potential of Data Preparation
Data Quality Chill Factor
There Are 2 Ways To Make Large Datasets Useful…

Here’s a dirty little about data management: It’s about art as well as science. In this post, I discuss how many people often mistakenly focus on the “science” of things while minimizing the art piece.

Considerations

Any good developer knows that there are many ways to skin a cat. For even something requiring high a degree of precision, there are often many options. Of course, some are better than others. When I develop data management tools, I often have a number of different alternatives with respect to moving and manipulating data, including the use of:

  • Temp tables
  • Queries
  • Batch processes
  • Export/import routines

While the MIKE2.0 framework provides for extensive best practices at a general level, there is a blizzard of individual decisions to make. Major development questions often include:

  • Should a data transfer process occur automatically or is there a need for someone to approve an action mid-stream?
  • What’s the right application for end users to enter and maintain data?
  • Are there any audit or regulatory concerns?
  • How technical are those being asked to maintain the data?
  • What type of safeguards exist so my clients won’t have to call me with minor questions?
  • How can I lock down the data–and the magic behind the scenes–so people can’t break things, dunintentionally or otherwise?

The answers to these questions drive my development efforts and basic philosophy for data management. For example, if I build an ETL tool for the IT department, it’s reasonable to assume that employees’ expertise will allow them to make some changes, especially if I document things well. I can probably automate many things and let SQL dance. However, if the same tool is built for gengerally less technical folks, there exists the very real danger that someone might break something. I typically err on the side of simplicity and more manual data management but it’s appropriate for that audience.

In the classic movie This is Spinal Tap, there’s an amazing line: There’s a fine line between clever and stupid. That quote need not be confined to the music industry. The same aphorism holds true for data management. Different folks in organizations have different levels of understanding and proficiency of all things data. I have seen repeatedly throughout my career the perils of overreaching; sometimes, really neat methods of data management are lost on end users, resulting in confusion, frustration, and dysfunction.

Feedback

What say you?

Read more at MIKE2.0: The Open Source Standard for Information Management

TAGGED:management
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

accountant using ai
AI Improves Integrity in Corporate Accounting
Exclusive
ai and law enforcement
Forensic AI Technology is Doing Wonders for Law Enforcement
Artificial Intelligence Exclusive
langgraph and genai
LangGraph Orchestrator Agents: Streamlining AI Workflow Automation
Artificial Intelligence Exclusive
ai fitness app
Will AI Replace Personal Trainers? A Data-Driven Look at the Future of Fitness Careers
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Innovation Management

13 Min Read

Bridging the Communications Gap Between Utilities and Consumers

6 Min Read

3 factors that lead to better employee performance

3 Min Read

Why Does Shaken Confidence Reinforce One’s Advocacy?

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.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
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.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?