Tuesday, August 25, 2015

Mo’ Data, Mo’ Problems: Managing data in a dynamic environment

Today’s guest blog comes from David Luhan, a director at the Governor’s Office of Information Technology (OIT). David's views below are based on his years of IT experience; they do not necessarily represent OIT policy.

Data management is a business imperative. Success hinges on the ability to make informed and effective decisions, and although organizations have been collecting and storing information for years, they continue to wrestle with quality, availability, and retention of data -- day in and day out.

With the uptick of e-commerce, social networks, and mobile devices, data is collected and stored in an overwhelming number of formats. Data management requires constant attention to ensure adequate storage, enforce security, and ease of use. Data management is essential; end of story.

But there are many obstacles, and they are not easy to overcome. Businesses and IT leaders are consistently faced with the following:

  • Rampant data growth from capturing unstructured data and a “keep everything” attitude.
  • Intensification of data velocity where there is an influx of rapidly-changing data that is decreasing in value over time.
  • Data that was once confined to a single data store is being replicated and repurposed across multiple departments and beyond.
  • The increasing propagation of data imported into new applications and repositories.
  • New applications creating content from sources that come with varying requirements for access, security, and retention.

That’s a lot. So, how should we handle data in a dynamic business environment? Here’s what I suggest:

  1. Establish Controls
    Review the data and the process by which data it is collected and managed. Establish rules on access and modification rights based upon job function. Identify the opportunity for database consolidation to establish a single point of data truth that feeds reporting and applications.
  2. Develop a Data Map
    One key to effective data management is determining what data you are going to collect and why. A data map shows the “flow” of data from intake to output, how various systems integrate, and define the use for each database field. The data mapping process will support the controls that have been established and will ensure better data consistency.
  3. Segment Your Data
    Segmentation is the on-going process of building several ‘profiles’ in the database depending on the product or service offered. Using characteristics of your customer, target audience profiles can be developed. Segmentation allows you to effectively gain attention with targeted key messages, leading to better engagement.
  4. Establish a Regular Data Archive Process
    Implementing a data archive process is an essential consideration for every department. Determine how frequently you will need to access the information and timeframe for records retention.
Adopting a data management strategy like this will help to alleviate the pain around reporting, compliance, and space provisioning. And, if you do it right, your IT leaders will foster a collaborative environment to enable a comprehensive and secure data repository that becomes a valuable -- and permanent -- resource. And that’s certainly a happy ending for today’s data management challenge.

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