Top 10 Best Practices in Data Governance for 2021 and Beyond

Top 10 Best Practices in Data Governance for 2021 and Beyond

For over two decades, organizations have been accumulating data and building systems to store, manage, and analyze it. Along the way, they’ve created several governance frameworks competent enough to facilitate some level of control over the data in their possession. However, as the data’s sophistication soars, its governance enters a vicious cycle of insufficient utilization and subsequent uninformed decisions.

Forrester’s analysis confirms that above 60% of data at the disposal of an organization, on average, goes unutilized. That more or less complements the stat that a handful (only 3%) of enterprises ever live up to the basic data quality standards.

Add the combination of different types of data found in a typical enterprise (e.g., financial reports, HR records, customer information, vendor details, etc.) and dynamic business environment (e.g., the rise of social media and the mobile workforce) to the mix and the need to understand how effectively these information assets are being managed becomes more than imperative. 

The problem is, most organizations don’t have a clue as to whether their existing governance practices are working or not. There is simply too much data and too many systems to be managed. It makes it incredibly difficult for those charged with oversight to know whether their efforts are even having any effect.

At a minimum, the need some metrics to know how their data assets are being used, at what level, how frequently, and with what success. To that end, the following is the list of best data governance practices that could help enterprises leverage data more effectively.

1.     Gather all the information assets

Gathering information assets typically incorporate aggregating both structured and unstructured data, much of which will still be locked in legacy systems. Suppose the company is able to draw a complete picture of how the information is being organized (in terms of location, type, etc.) and what exactly it comprises. In that case, they’ll be well on their way to understanding and better managing it.

2.     Gain control of data

Taking control of the data means organizing it within a database to allow for better management and organized reporting. The more comprehensive this central repository is, the easier it will be to generate the reports for various stakeholders and target specific data aspects. This commences with setting up an Enterprise Data Warehouse (EDW), which is essentially one enormous database with all of the information assets housed in one convenient location.

3.     Understand the data environment

Before one attempts to understand the data within their organization, it is essential that one fully interprets the environment in which the data is active. This helps determine how large the EDW needs to be and whether there are any tools or processes that can be leveraged to make it more efficient.

4.     Promote data governance objectives

For organizations to be more effective with their data, they must have clear objectives regarding what they want to achieve through their efforts. A data governance committee should be formed that could help define these objectives and then determine how best to achieve them. Report generation and analytics through tools seem plausible in this case, for they provide a good indication of where, where not, and why not the efforts are bearing fruits.

5.     Employ strategic data governance tools

A host of software programs work in favor of facilitating analytics and generating reports to allow for better comprehension of data. The key is always to choose between the services that best suit the organizational needs and are explicitly designed to cater to the type of data that can drive informed decisions.

This can be useful not only in terms of analyzing the data but also in helping the enterprise determine what forms of analysis are most appropriate. For example, some data may be better suited for operations-specific algorithms, while other data groups may require the use of predictive analytics. In either case, it is crucial to be aware of what the data at disposal can and cannot do and then take steps accordingly.

6.     Develop a data strategy

Gartner reports that around 27% of data employed by organizations (Fortune 1000) worldwide, tends to be flawed. Imagine the repercussions on ROI. As a result, the company’s data strategy should be at least as necessary as the overall business strategy, and rightly so. As part of this strategy, data collection, data storage, and data leveraging need to be precisely calculated and monitored. After all, the more specific this information is, the better prepared the enterprise will be for dealing with large amounts of data.

7.     Promote data security

The easiest way for a company to waste time and money is to open all its databases to everyone else in the organization, which is why promoting security needs to be an essential consideration when conducting data governance.

In addition to encrypting the data, organizations may also want to consider hiring a security manager who would spend part of their time ensuring that all of the right safeguards are in place, including appropriate access controls. With the rise of data breaches and reputational damage – both from a legal and financial perspective – it is critical to have an IT security manager making sure that everything is being managed properly.

8.     Conduct data awareness training

Every member of the organization should be aware of how the data is being used so that they can take steps to understand what is and isn’t working. Nevertheless, they shouldn’t just be aware of the data, in general, but the results they are trying to achieve through its use. This will allow them to manage their own information assets better and ensure that others in their organization are doing so as well.

9.     Form a data governance committee

Without the proper management team in place, enterprises will be unable to achieve the data governance objectives they have set for themselves. So, it is essential that they form a group of representatives from every department in their organization who could make sure the data fulfills its purpose.

10.   Create standards and processes

If the organizations want to have adequate controls in place, they need to have some processes and standards that can be followed. These standards and processes can be data modeling standards, data quality standards, or perhaps, data architectural standards. Compliance with these affirms that the organization can pave its path successfully for the accomplishment of objectives. 

Takeaways

So, there you have it – 10 ways to ensure that your data is being managed appropriately. Implementing these strategies will help make sure that your data is performing the way it needs to be, which in turn will help improve the performance of your business as a whole.