6 Dos and Don'ts of Data Governance - Part 2

In my last post, I gave you the first six Do's and Don'ts of Data Governance and promised to bring together an additional six to consider when making a data governance plan for your organization.

Here are six more dos and don'ts when building your data governance framework.

Do: Consider the Cloud on Your Route to Trust

Gartner predicts that "by 2023, 75% of all databases will be on a cloud platform, increasing complexity for data governance and integration." The move to the cloud is accelerating as organizations are collecting more data, including new datasets that are created beyond their firewalls. The need to deliver data in real-time to a wider audience, and seeking for more agility and on-demand processing capabilities is also driving this shift.

Because your data can be off-premises, the cloud might mandate stronger data governance principles. Take the example of data privacy, where regulations mandate that:

• You establish controls for cross border exchange of data.
• You manage policies for notification of data breaches, that you establish key privacy principles such as data portability, retention policies, or the right to be forgotten.
• You establish more rigorous practices for managing the relationships with vendors who process your personal data.

The cloud brings new challenges for your data governance practices, but it brings many opportunities as well. At Talend, we see that a majority of our customers are now selecting the cloud to establish their single source of trusted data. DRG is a great example of this.

Depending on your context, there is a good chance that the cloud is the perfect place to capture the footprints of all your data into a data landscape. Further empowering all the stakeholders in your data-driven process with ready to use applications to take control and consume data.

Do: Be Prepared to Explain "Data"

Employees often lack digital literacy. That's one part of the problem. As data is becoming more predominant in organizations, you will also consider they often require data literacy.

You'll likely find some employees being reluctant to learn how to use sophisticated tools. To combat this, use a data catalog to make your data more meaningful, connected to their business context, and easy to find. Leverage cloud-based apps such as Talend Data Prep or Data Stewardship so that they can access data in a few clicks without specific training before they can start.

Do: Prove the Data Value

As you move along with your data governance project, it's highly likely that you will come across skeptical users. They will challenge you on your ability to control and solve their problems.

You would need to prove to them that they will save resources and money by delivering trusted data. Start by taking a simple data sample like a Salesforce or Marketo dataset. Use data preparation tools to explain how easy it is to remove duplicates and identify data quality issues. Show the recipe function that allows to effortless reproduce the prep work to other data sets. It's data quality at first. Another quick hint will be to show them how easy it is to mask data with Talend Data Preparation.

Don't: Expect Executive Sponsorship to Be Secured

Once you prove business value with small proofs of concepts (POC) and gain some support from the business, ask for a meeting with your executives. Then, present your plan to make data better for the entire organization.

Be clear and concise so that anybody can understand the value of your data governance project. Explain that they will gain visibility by endorsing you and hence, improve the entire organization's efficiency. You will gain the confidence you need to have your project supported, and your work will get easier.

Do: Be Hands-On

As you begin to meet with different people in the organization, to listen to their challenges and offer your assistance. Make sure all your actions are indeed efficient. As the old saying goes, "You have to plan the work and work the plan." Follow up and outline the next milestones of the project. You will confront some obstacles, realignment priorities as your organization readapts to changing business conditions. Don't give up and adapt your planning if needed. However, keep convincing people and (re) explain how your project would overcome the company's challenges.

Also, ensure your data governance is really connected with your data. Too many data governance programs have established policies, workflows, and procedures, but are failing to connect with the actual data. For example, a Talend Survey has shown that among the 98% of the companies surveyed that are claiming for GDPR compliance in their legal mention, only 30% could deliver on their promises to fulfill the data access requests when their customers are asking to respect their rights for data accessibility. This means that most companies have established strong governance principles, but are failing in operationalizing them.

Do: Practice Your Data Challenges

Work your data governance framework through some practice scenarios. Let's say you want to practice as if you had experienced an internal data breach or a data leak to see if your framework is working in a worst-case scenario. Consider running a team drill. Make up a breaking news scenario and see how well your plan works then use those lessons learned to improve it. As you go through and practice this scenario around your framework, ask yourself:

• "Is all sensitive data properly masked?"
• "Can I to track and trace all of my data?"
• "Do the data owners feel accountable about the data they're responsible for?"

Get in the shoes of your customer you want to consider his right for data access or right to be forgotten.

It's always better to be proactive rather than just experiencing a privacy incident for real with all its consequences that this entails. And this will make data governance more concrete, turning it in operational challenges rather than high-level principles.

To know more about how to deliver data you can trust, don't hesitate to download our definitive guide to data governance.