In a study performed ahead of last week’s Gartner Data and Analytics Conference, researchers found that data governance is a top initiative that business leaders and data officers plan to focus on in 2023 and into 2024. We’re glad to see companies choosing this as a top priority. Data governance is only increasing in urgency and demand, yet we’ve seen many organizations falling behind in establishing a proper data governance practice.  

Data Governance Definition

At its center, data governance is, “the process of overseeing the integrity, security, usability, and availability of data within an enterprise so that business goals and regulatory requirements can be met.”

According to the Gartner Glossary, data governance is, “the specification of decision rights and accountability framework to ensure the appropriate behavior in the valuation, creation, consumption, and control of data and analytics.” A well-run data governance practice can improve your data quality by setting the standard for how data is received, stored, and processed within your database.

A successful data governance strategy will guarantee that your data is dependable and that data users are being held accountable for their access levels. Data governance is a critical business component for all industries and will only continue to increase in traction as a standard business practice as more rules and regulations are set in motion surrounding data governance.  

Building a Successful Data Governance Strategy

Building a data governance strategy ahead of implementing a data governance solution is the best way to ensure your data plan is set up in such a way that will offer success for the data you store. Your data governance strategy serves as the base for the decisions that your organization makes. Once you have that strategy in place you can better identify which data governance solution best fits your needs. A solid data governance strategy will guarantee that you are building a solid foundation for your data.

Our partner, Alation, says that a successful data governance strategy must decide four things: data availability, data consistency, data accuracy, and data security. ‍

Data Availability: A good data governance strategy allows the correct data to be available to the correct people at the appropriate times. Your data governance solution should be structured in such a way that the people who the data is made available to can easily find and access the data. When strategizing, your team should determine what data availability you will need within a data governance solution.

Data Consistency: One key point your organization should consider when discussing your data governance strategy is the standardization of data points across your database. Determining these key data points from the beginning will help streamline the decision-making process down the road and will ensure consistent decisions are being made across your organization regarding your data.

Data Accuracy: Determining how data comes into your database, what you do with it once it’s there, and how data will exit your database will establish ground rules for the future of how your data is managed. It’s important to determine ahead of time the values, tags, and lifecycle that will be associated with data points to ensure consistency and accuracy, and guarantee that your dataset is error-free.

Data Security: Companies are responsible for protecting the sensitive data entrusted to them. Should your organization need to pass regulatory audits for any reason, a good data governance strategy and solution will ensure your data is safe, and that you have the audit logs available confirm regulatory compliance.

6 Must-Haves to Master Data Governance

A quick Google search of “Data Governance Solutions” will prove there isn’t a one size fits all approach to data governance tools. By taking the time to pre-determine your data governance strategy, you are better positioned to find a data governance solution that is flexible and scalable to fit your needs.

ALTR’s data governance solution delivers both scalability and flexibility, and we’ve seen data governance success in organizations from a multinational retailer governing PII to a regional credit union protecting PCI to a unique healthcare organization safeguarding PHI.

Our data governance features matrix outlines 18 key points that we think are critical when evaluating whether a data governance solution will suit your needs. We’ve broken down key differences that ALTR brings to the table in each of these categories:

1) Flexible Pricing‍

Starting price and scalable pricing are points to consider when choosing a data governance solution. While some data governance solutions charge six figures to start, ALTR is proud to offer a free solution for one database within Snowflake and scalable pricing when you decide to upgrade to ourEnterprise or Enterprise Plus plans.

2) Access Monitoring

See what data is used, by whom, when, and how frequently with ALTR’s industry-first interactive Data Usage Heatmaps and drill-down Analytics Dashboards. Access monitoring is helpful for understanding normal data usage, identifying abnormalities, and preparing your organization for an audit request.

3) Data Masking

Within ALTR, you can quickly and seamlessly apply flexible, dynamic data masking over PII like social security numbers oremail addresses to keep sensitive data private.

4) Rate Limiting

ALTR’s patented, rate-limiting data access threshold technology can send real-time alerts, and slow or stop data access on out-of-normal requests. The control is then in your hands to stop individual access when it exceeds normal limits. This is helpful for mitigating the risks associated with credentialed access and data breaches.

5) Tokenization ‍

Tokenization is the process of replacing actual sensitive data elements with random and non-sensitive data elements (tokens) that have no exploitable value, allowing for a heightened level of data security during the data migration process.  ALTR’s tokenization allows you access to secure-yet-operable data protection with our patented data tokenization-as-a-service. 

6) Open-Source Ecosystem Connectors

As we worked to integrate our solution with data discovery, catalog, and ETL tools, we found opportunities for very simple data governance integrations to be created. We found open source to be an ideal distribution method as it allows companies more flexibility in building their integrated and secure data stacks.  

What’s Next for Data Governance

The need for data governance is guaranteed to only increase in the coming years. IDC predicts that the global datasphere will double in size from 2022 to 2026. We predict that in the near future, companies that don’t have a data governance strategy in place now, will soon need to.

From legacy on-premises providers to new cloud-based start-ups to lateral players in the data ecosystem, it seems almost everyone offers a “data governance” solution these days. But, there’s no actual data governance without data control and protection, and DIY and manual approaches can only take you so far. To ensure they don’t fall behind, companies should be evaluating data governance solutions now to find those that meet the requirements of their data governance strategy and deliver those six “must-haves” for mastering data governance.