DataHub Workflows for Data Platform & Governance Leads

Data powers crucial decision-making and insight generation at a wide variety of organizations and businesses. It’s frequently up to data platform leads and governance leads to ensure that your data ecosystem stays reliable and legally compliant. DataHub is a powerful tool to help them do their jobs and maintain your data systems. Let’s dive into some of the use cases where DataHub can vastly improve workflows for these types of team leads.

Data Platform Lead

Data Platform leads are tasked with designing and tending to an organization’s data platform and its users. DataHub allows data platform leads to easily maintain different parts of your data platform. On top of that, it makes it easy for other users in your organization to generate insights on their own, freeing up bandwidth for data platform leads. Here’s how DataHub can help data platform leads answer some of the pressing questions they might face day-to-day.

Are my most important datasets and dashboards dependable?

DataHub’s metadata tests feature lets you define tests around what defines good quality metadata. You can easily view how many of your datasets have descriptions, owners, and other salient properties attached to them. This helps you quickly determine whether your entities are dependable. In the near future, we’ll allow you to view metadata test breakdowns by top used datasets, which helps you prioritize your focus when doing this kind of quality control.

How can I support a growing number of producers and consumers of data?

The modern paradigm for conducting business means that data platform leads will be tending to even more producers and consumers of data than before. DataHub lets your organization’s data producers and consumers work with each other without requiring direct involvement from a data platform lead. Producers can easily annotate the data you own by writing descriptions and categorizing data with tags and glossary terms.

DataHub exposes easy and powerful annotation tools in the right sidebar

Data consumers can also leverage DataHub’s search functionality and lineage features on their own to find relevant assets and gain understanding about them.

DataHub Search

DataHub Lineage

DataHub enables producers and consumers to self serve a variety of use cases, which keeps your data platform leads from being the bottleneck of your team’s productivity.

Governance Lead

Regulatory requirements and compliance policies are typically the responsibility of your organization’s governance lead. Since private information is at risk, it’s important for your team to reliably ensure that governance guidelines are followed. DataHub’s features for categorization and organization let you take care of this simply and reduce the chance for human error.

Can I standardize business and compliance types?

DataHub’s business glossary provides your team a one-stop shop to standardize your business and compliance types and provide the ground truth for your whole organization. Compliance types can be standardized into different levels, such as sensitive, confidential, and more.

Clicking into a glossary term lets you easily view a list of entities that fall under that term.

The glossary also allows you to define business terms and associate datasets and dashboards with a term. This allows all of your team members know what a certain term precisely means.

How can I categorize my data and scale coverage?

Categorizing your data is one of the simplest and most powerful ways to organize it and make it easy for your organization to manage. In DataHub, you can apply glossary terms to specific columns in dataset, which allows you to categorize data as well as assign it a compliance type.

You can set an inheritance structure for glossary terms such that specific categories automatically get categorized with other glossary terms. In the example below, we’ve set all data labeled as ‘Breed’ to also fall under the ‘Sensitive’ glossary term, so it automatically carries that compliance type throughout DataHub.

DataHub also has logic that allows you to automatically propagate glossary terms between entities, which automates the task of categorizing data. This allows your team to scale coverage easily.

How do I organize my data assets into domains?

Many organizations consist of multiple divisions and departments. While using DataHub, team members can easily filter and view only the data relevant to their own department by browsing under their department’s domain.

Having this subview into the data ecosystem streamlines work for team members who only work within certain domains of your organization’s data. This is especially useful for organizations that have different departments or divisions that generally work independently from each other. At the same time, your central management still has a unified view of all the data and business that happens in your organization through DataHub. This would give visibility into insights like “domain A’s data is properly annotated, but domain B’s data is poorly annotated and disorganized”. Data can be organized into domains through the UI for each dataset, or using a transformation during data ingestion.

Takeaways

We find that DataHub creates value for Data Platform Leads and Governance Leads by enabling efficient workflows for organizing your data. It also exposes useful self-serve functionality for other users in your organization, which frees up bandwidth for your team leads. Acryl Data and the DataHub community are adding even more features over time to magnify the positive impact that your data can have. So, we’d love you to be part of the DataHub community! Want to get involved? Come say hello in our Slack, check out our Github and attend our latest Town hall to learn about the latest in DataHub.