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Top 5 Aspects That Can Strengthen Your Data Governance Framework

Information is power, and your organization depends on it for making good business decisions every day. Unfortunately, the data generated by organizations is not being governed the way it should be.

Big data surveys show that a partnership between business and technology is key to ensuring the adoption of successful data-driven initiatives.

Businesses today are plagued by broken links, missing files, and duplicate data, which show just how mismanaged their data streams are. Furthermore, breaches in privacy laws and a lack of accountability continue to impede the possibility of a quick fix. Strict privacy laws like the

GDPR is incentivizing better governance. 71% of organizations believe that these laws help improve data governance, in this survey.

This is where the framework of data governance comes in; a governance solution that consistently monitors your data to give you the best insights owed. Given our passion in this field, we have shortlisted the top 5 aspects that can strengthen your data governance framework:

  1. Ensuring Data Privacy & Security

One of the first things to know about data governance is its ability to enforce data privacy. Data privacy means the securing and sharing of sensitive data on a strict ‘need-to-know’ basis only. This means that throughout the data’s lifecycle, only authorized personnel gets to access it at any given time.

These days, companies have access to a lot of Personally Identifiable Information (PII). This information is often sourced through multiple data sources like login pages, personal profiles, feedback details, surveys, etc. In addition to securing confidential business data, companies are also required to protect all sensitive third-party information that passes through them; this includes private information belonging to their customers/clients as well as their business partners.

Allowing sensitive PII to fall into the wrong hands would categorize the event as an ‘information leak’. This is a very dangerous thing to happen; both to the privacy of the owners and the reputation of the company that was responsible for securing the data.

It is, therefore, very important for businesses to have a strong data governance framework that can ensure data privacy and security. With good data governance tools, you can define the nature of the said data, monitor its storage, and also oversee its usage. It would also keep you compliant with the latest data privacy laws (eg. GDPR) and help you follow the right policies around data ownership.

  1. Consistently Maintaining Data Quality

There is a reason why the term ‘data dump’ is popular. The only job of a data source is to collect information and ‘dump’ it where you can access it. This is why businesses have to sift through petabytes of data just to find something meaningful to gain business insights from.

It is only after this data has been categorized into usable, helpful portions that it starts being realized as an asset. Data quality is, therefore, the simple act of converting raw data into a usable form and maintaining it as an asset.

Data governance helps you uncover new sources of information and draw better business value from your data. It can also identify broken/missing pieces of information and prevent duplicates from interfering with one another. Through data governance, outdated information can be flagged for attention, and critical data can be highlighted to the right teams within the organization.

Broken links, incomplete files, incorrect prioritization, etc. are all incidents that greatly affect data quality. Data governance practices help fix such occurrences and also maintain it. Good data quality must be achieved throughout the complete life cycle of the data.

Also, one of the best ways to achieve this is through the use of Artificial Intelligence.

  1. Artificial Intelligence (AI) & Machine Learning (ML)

Real-time data management can achieve any enterprises’ dream of consistently maintaining their data quality and security. Through machine learning (ML) and (AI), we can reach new heights in data governance that would not have been possible merely through human labor. Though implementing the AI concept might bring challenges yet its always worth the effort.

Data governance tools that employ (AI) can help with predictive analysis for foresight on important trends. These would be key when decisions that are time-sensitive cannot be delayed, and when timely information can mean the success/failure of important business deals.

(AI) brings with it the evolved ability to track patterns and discover hidden data that earlier would have been lost to you. Automation allows the data governance tools to continuously scan data reserves without the massive time factor that comes with doing it manually. The accuracy and reliability of machine intelligence further make this a must-have addition to the data governance solutions. A good (AI) grows with your governance needs while staying compliant with all the policies that govern it.

This ties in neatly with the benefits of guided analytics that can revolutionize the way you learn from your data.

  1. The Benefits of Guided Analytic Activities

There are many ways to derive insights from good quality data and businesses often depend on the developers or the analytics team to come up with them. However, a good data governance tool allows you to improve upon this style of analysis. By reading governance needs through user-defined dictionaries and patterns, guided analytics let you derive the best possible insights from your own data.

Automatic analytic activities can monitor repositories and display key findings that would have been missed in the traditional methods of data analysis. They can detect hidden relationships between data columns and highlight valuable insights that show you exactly where to start focusing.

Data governance allows the guided analytic capabilities of its tool to assist you with the maximization of your returns from your own data; this lets you use the system as a guide and make major improvements to the way your data is analyzed. A tool that can automatically read volumes of information can do a much better job at detecting better ways to analyze it when compared to a developer who may or may not be familiar with every byte of information.

Guided analytics are essential for good data governance; they can reveal statistical insights through methods that you may never have used before. With data, there is always more than what meets the eye; and you can finally start knowing what that is.

  1. Reducing Your Compliance Risk and Exposure

With great data, comes great responsibility.

Given the data volumes that businesses handle every day, it is easy to see how the slightest mismanagement can lead to severe security breaches. Since this data is essential to the service they provide to their clients, companies need a strong data governance framework that allows them to securely use this information.

The overlapping of several policies that govern data makes it tough for the organizations to decide on how best to use it. Staying compliant with multiple regulations like GDPR, Dodd-Frank, Basel III, CCAR, etc, can be confusing, which is why a tool that grants you visibility into these policies is fundamental to reducing exposure risks.

Data governance helps keep your company safe by automatically implementing the appropriate policies into the system. This keeps anyone who uses the data stay compliant with the right standards that govern it.

A strong data governance framework also tests your compliance risk factors while detecting sensitive information. Knowledge of the amount of sensitive data coursing through your company and knowing whether or not it is secure is critical to keeping your company on the legal side of things. Data governance helps you to stay legally compliant so that when you do more, you do it right.

In Closing

Businesses are most crippled when they are unable to manage their own data and use them for insights like they ought to. Allowing data mismanagement to continue unchecked would mean to actively reject the benefit of useful information. Without a proper data governance framework, your company would also be liable to violate several privacy laws.

By maintaining data privacy and quality throughout its lifecycle and making use of AI and guided analytics to derive valuable insights, you can strengthen your framework to govern your data like never before.

In a world where information is overflowing and insights are few, data governance is the tool that will determine its leaders.

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