The Fundamentals of Data Lineage in the Cloud

Why is data lineage a critical capability for organizations aspiring to be more data-driven? And why should this capability be deployed in the cloud?

If you’re interested in gaining the answers to these questions and more, then hopefully you’ve registered for our Data Lineage in the Cloud webinar series. In our first episode, The Fundamentals of Data Lineage, we covered the basics and provided answers to some of the most essential questions related to data lineage. Keep reading for more highlights of what we learned.

What Is Data Lineage and Why Is It Important?

Data lineage is a visual representation of data flow that helps track data from its origin to its destination. It enables you to understand how data changes during its journey, throughout its entire lifecycle. Lineage helps to clarify information regarding the availability, ownership, security and quality of the data as it flows across the organization.

As organizations work towards being more data-driven, it becomes increasingly critical to understand where data originates, its transformations and how it’s being used. Data lineage provides the transparency needed for users to be confident in and trust the data they’re using, which is fundamental for fueling data-driven initiatives.

Why Is Data Lineage in the Cloud Essential?

Deploying data lineage as a cloud-native capability, as with other solutions in the cloud, provides many advantages. One of the largest benefits is the acceleration of time to value: for many projects, simply provisioning the necessary infrastructure is extremely time-consuming. Because you do not have to deploy or manage complex infrastructure with a cloud-native offering, it significantly reduces the amount of time between when you procure the solution to when your users can extract value.

Other benefits include the flexibility to scale resources as needed and freeing up personnel who would otherwise be managing servers, patches and upgrades, allowing them to focus on tasks that are higher value and more rewarding. You’re also able to access new features automatically and immediately as they are released.

What Are the Different Types of Data Lineage?

A wide variety of stakeholders can utilize and benefit from data lineage. And the presentation of lineage can vary based on persona, as different audiences have different needs.

Business lineage offers a summarized view of data sources and transformations. Business stakeholders creating financial reports or generating marketing dashboards, for example, want to know that they can trust and use the underlying data.

Technical lineage displays the granular details that technical stakeholders desire, as they commonly utilize lineage for initiatives such as migrating data to the cloud. Technical teams appreciate a large amount of detail, as they need it to comprehensively understand the impact of rolling out new systems, for example.

What Are Some Typical Use Cases for Data Lineage?

While there is a diverse collection of use cases for data lineage, some of the more common questions answered by data lineage include:

• Regulatory compliance: “What data in my enterprise needs to be brought into compliance with regulations such as the General Data Protection Regulation (GDPR)?”
• Cloud modernization: “What data should we migrate to a cloud data warehouse — and which users will be impacted by the move?”
• Analytics: “Where should our data scientists look for trusted data they can use in advanced analytics projects?”
• Customer experience: “Which data sources should we use for developing new customer experience initiatives?”
• Change management and impact analysis: “What reports will be impacted if I modify this data source?”
• AI governance: “What data was used to train and validate the AI model? Which downstream applications are using this model for decision-making?”
  

For more information regarding each of these use cases and more, read our eBook, AI-Powered Data Lineage: The New Business Imperative.

What Are the Must-have Capabilities for a Data Lineage Tool?

A robust data lineage solution must be able to support automatic data lineage stitching from multiple sources. Automated scanning is the first, and perhaps most critical, step of capturing data lineage. Manually defining lineage would not only be highly resource-intensive, but error-prone as well. Additionally, the output most likely would be outdated soon after being documented (and overwhelming to maintain) due to frequently changing environments.

To meet today’s demands, a complete solution must be able to derive end-to-end lineage automatically from a large amount of diverse, fragmented data sources — both cloud-based and on-premises. Ideally, the solution also should automate the capture of detailed data transformation details from sources including SQL scripts, stored procedures, business intelligence reports, and ETL jobs.

To hear about other must-have capabilities, watch Episode 1 of the Data Lineage in the Cloud webinar series on-demand.

What Are the Benefits of Data Lineage?

As mentioned earlier, a key benefit of data lineage is understanding your data and increasing confidence in the data fueling your analytics and AI. Data lineage provides the transparency needed to support self-service analytics and AI initiatives. It can also help with managing regulatory compliance and mitigating risks as well as gaining end-to-end visibility and insights to drive effective change management.

Ultimately, data lineage, within an intelligent data catalog solution, provides the information necessary to improve overall data intelligence. Organizations can leverage this comprehensive data intelligence to help make predictive recommendations that help:

• Accelerate and automate data governance to deliver trusted data
  
• Enable data sharing programs that empower data consumers to engage with data
• Drive analytics, AI and business outcomes with trusted data

Register for the Data Lineage in the Cloud Webinar Series

Be sure to join us for the next episode of our Data Lineage in the Cloud series, where we’ll discuss using data lineage to drive business value and will also dive into some specific industry use cases. Select your episode(s) of interest or join us for all the remaining episodes in this five-part series. Register today!