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 analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Standardizing Data Migration
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 Mining > Standardizing Data Migration
Data Mining

Standardizing Data Migration

EvanLevy
EvanLevy
4 Min Read
SHARE

In the motion picture industry, studios separate responsibilities for creating content from responsibilities for distributing content. The people who make the movies option the scripts, hire the talent, and film the scenes. The distributors of the films, on the other hand, figure out how to package and deploy the films. They need to know which theaters require 30 millimeter versus 70 millimeter formats, or even IMAX. They also deal with DVD packaging, including different international DVD formats. The industry understands the importance of having a supply chain that differentiates between the roles of content creation, content packaging, and distribution. In…

The Motion Picture Industry

In the motion picture industry, studios separate responsibilities for creating content from responsibilities for distributing content. The people who make the movies option the scripts, hire the talent, and film the scenes. The distributors of the films, on the other hand, figure out how to package and deploy the films. They need to know which theaters require 30 millimeter versus 70 millimeter formats, or even IMAX. They also deal with DVD packaging, including different international DVD formats. The industry understands the importance of having a supply chain that differentiates between the roles of content creation, content packaging, and distribution.

In IT we’re very quick to point to our operational systems as creators and owners of data. But maybe the solution is that IT establishes a functional team that’s responsible for data packaging and distribution, just like the movie industry.

More Read

Selling Data Mining to Management
Top 5 Reasons “Data Geek” Jobs are on the Rise
Text Mining Strategies and Limitations with Scalable Data Solutions
Customer Centricity Strategy #1 – Customer Analytics
Business Intelligence and The Heisenberg Principle

Traditionally data formats and standards have fallen into the realm of the architecture team. Unfortunately this is typically a paper-only activity without teeth. A data distribution team wouldn’t focus on paperwork. They would be focused on data logistics, receiving content from the various source systems and packaging the data for consumption by other systems. This isn’t about implementing a specific platform to store or move data. It’s about active management of corporate data content.

One of the biggest development challenges is the hunting expedition that developers go on to find and acquire the data they need. Most aren’t aware of all their choices, let alone the optimal systems of record.

Currently every application, data mart, data warehouse, reporting system that needs data from another system follows a specific set of procedures to obtain that data. Each system requests different data formats, different delivery schedules, and different content. Everything is custom, there are few if any standards, and there are no economies of scale.

This will also unburden the various application teams from building and maintaining the never ending volume of custom extract requests. The only way to stop the madness is to compartmentalize content creation from data packaging and distribution. This means establishing a data supply chain that separates data creators from data distribution from consumers. Who knew IT infrastructure was just like the movies?

Link to original post

TAGGED:data migrationdata quality
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai in business
Recurring Revenue Strategies for the AI Business Era
Artificial Intelligence Exclusive
ai for playground safety
Using Data to Plan Safer, More Efficient Public Playgrounds
Big Data Exclusive
AI for cybersecurity
How AI Supports Modern Penetration Testing
Artificial Intelligence Exclusive
ai kids and their parents
How Cities Use AI to Improve Playground Design
Exclusive News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Who should be accountable for data quality?

11 Min Read

Adventures in Data Profiling (Part 1)

6 Min Read

The General Theory of Data Quality

9 Min Read

There are no Magic Beans for Data Quality

7 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 in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data 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?