Building your Data Democracy

Building Your Data Democracy

In a “pure” data democracy every end user can access the value of all your organization’s data. They can use simple business terms to find and understand data and there are no doubts about data legitimacy or data lineage. Just pure value, unprecedented insight, and smarter decisions based on data truth.

Ah, to live in such a blissful data society. Alas, like any democracy, there are rules. Everyone shouldn’t be able to see everyone’s salary or personnel file and data is always subject to scrutiny. Democracy is difficult. More people want more capabilities and options, but great data can be contaminated. At the battlefront of data democratization are three familiar foes that must be defeated:

  1. The sheer quantity and variety of disorganized data in your organization makes it difficult to find the right data, ascertain its trustworthiness and derive value from it.
  2. Those who can benefit most from a data democracy (business users) have neither the time nor the technical know-how to take advantage of the data. The gap between technical metadata and business terms seems impassable.
  3. An increasingly stringent regulatory environment instills fear when considering how to use data that may contain sensitive information or be collected for a completely different purpose and, therefore, not be usable without an explicit user opt-in. If you don’t even know what that data is, how can you possibly know where it came from or why it was collected?
  4. Fear not. In the battle for data democracy, Waterline Data has a secret weapon.

How do you establish a culture of data democracy? Start with Waterline Data’s AI-driven data catalog as a foundation and then watch your data democracy turn your organization into a more perfect union.

Find the Value in All of Your Data

Finding data is close to impossible without a data catalog, and building a proper catalog requires automation. The manual tasks involved in building a catalog given your existing data variety and quantity are untenable. Waterline Data’s AI-driven automated tagging resuscitates lost data, associates it with appropriate business terms or tags and makes it findable across the enterprise to technical and business users alike.

There’s also a security-findability paradox in most companies where you cannot give everyone access to all the data in all the databases and data repositories. Usually users cannot get access to data until they request access. But without having access, they don’t even know that the data exists, so they don’t know to ask for access. It’s a perfect catch 22.

We have built Waterline Data’s AI-driven data catalog specifically to break this cycle by making metadata visible to users without compromising data access security, and by managing data access through native access control policies, so the catalog does not introduce any security holes and does create yet another authorization system to synchronize. Even though a user may not normally have access to a data set, that data set is still findable. As soon as they know the data set exists and can be of value to them, a user can request access. At that point, automated privacy and security checks-and-balances kick in to help the user gain access to the data in a governed way.

Data Democratization: Insight for Everyone

In its raw form, technical metadata identifies data sets, yet users responsible for decision-making think in business terms. Unless business terms can be mapped to data sets, there is no way for users to search for it (e.g., a field containing “Account ID” may be called “id,” “acctid,” “account_id,” “aid,” “anumber,” etc.). Even when a data specialist points a user to a potentially useful data set, the user may not be able to understand or interpret what different fields mean.

Waterline Data’s AI-driven data catalog automatically tags each field with business terms so data sets are findable and understandable. No matter where it came from, who gathered it, the type of data, or how its metadata was defined, users can find a data set through searches familiar to their roles.

Eliminate Data Compliance Fears

Users don’t set out to break regulations while seeking insight from data. However, if they do not know that a data set contains sensitive data, if they do not know where the data set came from, or if they reuse sensitive data, they may inadvertently expose the organization to regulatory risk. How can users confirm that data was collected for a purpose compatible with their usage as mandated by, for example, GDPR regulations?

By automating sensitive data discovery and providing a place to document acceptable business use for each data set, Waterline Data’s AI-driven data catalog removes organizational fear of non-compliance with government and internal regulations. In turn, this opens the door to wider, more creative use of data and, ultimately, competitive advantages.

Data Democracy Begins with a Data Catalog

Before users can access data, it has to be available in one place, accessible, and easy to use. As data becomes increasingly valuable to more people across the enterprise, a data catalog will be required to facilitate advanced users as well as data neophytes. Why limit insight to the data elite when your business users on the frontlines are making the daily decisions that propel your business forward?