3 Reasons Why Data Management and Data Governance Make the Perfect Couple

Data is the lifeblood of almost every business today, and the volumes they deal with is growing all the time. It's estimated that by 2025, some 463 exabytes of data will be created globally every day - the equivalent of more than 212 million DVDs.

How you manage and control your data can make or break the success of the company. Get it right and you'll have much better insight into your customers, your internal processes and the wider market. This allows you to make informed decisions and work proactively to get ahead of competitors.

On the other hand, poor data management can result in much lower efficiency and leave you without critical information exactly when you need it - not to mention the potential risks you may be exposing the company to should this data be compromised.

This means strong data management and data governance processes are essential. But what are these two vital components of a good data strategy, and how can they work together to give businesses the tools and processes it needs to handle its data successfully?

The difference between data management and data governance

The first step is to understand what's meant by data management and data governance and the different roles they play in your strategy. While some people may talk about the two terms as if they're interchangeable, they each have their own purpose.

Data management refers to the overarching strategy that encompasses every aspect of how you handle your data. This includes:

• Data preparation and cleansing
• Extract, load and transform (ETL) operations
• Data cataloguing and warehousing
• Architecturing to manage data flow
• Data security

This covers everything a business needs to do to complete the process, from the initial creation or gathering of data through to final analysis and decision making.

Whereas data governance is concerned with the handling of the data as it goes through this process, and how it relates to the needs and concerns of the wider business. It deals with key questions such as:

• Who owns the data?
• Who can access the data?
• How relevant and accurate is the data?
• Does the business have the legal and ethical right to use the data?
• What measures are in place to protect privacy?
• Are all new regulations being followed?

In short, data governance ensures that all the right policies and processes are being put in place for successful use of a firm's information, while data management handles the actual execution of the data strategy.

3 benefits of having a strong data strategy

A data management solution without a comprehensive data governance plan - or vice versa - means you won't have the right tools or safeguards in place to make the most of your data.

So how can data management and data governance work together to benefit the business? Here are a few key advantages of a well-integrated data strategy.

1.  Match your IT strategy to business needs

An effective system ensures that IT initiatives aren't taking place in a vacuum. By aligning governance processes throughout the project, this ensures companies are asking the right questions of their data and looking for outcomes that’ll address the key queries business units need answering.

Combining data management and data governance ensures there’s a strong bridge between the IT professionals working on the data on a day-to-day basis and business professionals who’ll use the results of analytics. This also helps everyone understand the roles each team plays in the business and how to best tailor the data strategy to assist with these.

2.  Improve the quality of your decision making

Data governance steps such as validating the accuracy and relevance of data ensure that any analytics activities are providing the best results. It can also help make certain that data management teams are focusing their efforts in the right areas and standardizing systems and policies.

This ensures that every part of the business is working to the same specifications and there’s no confusion between teams about the outcome of their data strategies.

3.  Protect the organization from liability

From a security and regulatory perspective, a good data strategy needs to be about much more than simply protecting the data from unauthorized access, such as hacking attacks. It's also about making sure you're up-to-date with ever-evolving privacy regulations and treating personal and private information with sensitivity.

For instance, if data can be anonymized before being processed, this is a must. And if personally identifiable information is necessary, the governance team should step in to ensure its use is minimized and handled carefully. This ensures the company isn't falling foul of strict regulations such as GDPR, as well as reassuring users and protecting its reputation.