How to Craft a Data Management Strategy and Why it is Important | 7wData

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Already routinely called the currency, the lifeblood, and the new oil of the modern business world, data promises organizations unbeatable competitive advantages. Lured by this promise, many companies have defaulted to hoarding every piece of data they can lay hands on. With storage budgets stretched, this data, however, remains unused. Some have taken a step further, toying with data analytics. But their initiatives have been held back by too much data, missing or inconsistent data, or a lack of advanced infrastructure.

According to a global survey sponsored by Splunk, 55% of data sitting in companies is dark, with organizations either not knowing how to use it or not even sure if they even have this data. Meanwhile, the strategic importance of data has been rising as technology advances are unlocking more and more success data stories. It is only natural that our data consultants at ITRex often hear from clients one question: How can we put our data to work? Our answer is always the same (and less breathtaking than might be expected): you first need to build a robust data management strategy.

Though not as sexy as predictive analytics and dashboard storytelling, data management is the key to making your data fit for successful data analytics and data science. Failure to manage data properly is similar to failure to manage financial or physical assets. It leads to waste and lost opportunity. In this article, we take a deep dive into what makes a good data management strategy and offer useful tips on how an organization can get started building it. Let’s go.

A data management strategy outlines a high-level course of action to enable data management. The Data Management Body of Knowledge (DAMA-DMBOK2), written by over 120 data management practitioners, defines data management as the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles.

In layman’s terms, data management is basically about:

Depending on the industry and business needs, data strategies can vary, but all of them cover 10 knowledge areas, with one area — data governance — at the center. Below is a table that provides a summary of each knowledge area and why it is critical.

As a rule, the data management strategy is owned by the Chief Data Officer (CDO) and implemented through a data governance team with support from a Data Governance Council. It is the CDO who drafts an initial data management strategy and gets executives’ buy-in for establishing data governance and data stewardship to monitor data practices. How an initial data management strategy can look like:

We’ve heard a few disappointing stories from our data clients who have sent their entire IT teams to months of data training. The people got back putting just one idea to the table: the company should hire an expert to build a data strategy.

Overall, only about 20% of companies are reporting success with managing their data, with less than a third saying it is “very easy” for users to access data and extract insights.