A Quick Guide to Streamline Data Lineage Process and Process Transparency

Streamline Data Lineage Process

 If you want to understand the data governance framework and if you want to know how to implement and use this framework, then you must find out where the data has come from and how it passes through the system. This is where data lineage comes into the picture. 

With the help of data lineage, you can get complete transparency, and it can also help you build a foundation for informed changes. But if you want to use data lineage, you should first understand it in a detailed way. 

In this blog post, we will discuss all that you need to know about data lineage in a detailed manner.  

What is data lineage?

Data lineage defines or describes the characteristics, movements, and quality of data. If you are using any data, it becomes crucial to understand this data journey to maintain complete data transparency over the entire data. So, we can say that, with the help of data lineage, you can understand where the big data starts and how big data is transformed when presented in the outcome. 

So, data lineage help you with these three things;

  • Enhance the business intelligence as you can better keep tabs on data insights and process success

  • Find out data sources and make the process simple for all the technical teams.

  • Get better insights into the data processing activities as this helps ensure that the data is aligned with the regulatory needs. 

The challenges of data lineage 

Nowadays, the rules and regulations regarding the use of data have become strict. Therefore, the regulators want to know how the sensitive data is being handled throughout its lifecycle. It has never been so important to keep tabs on data lineage. 

But if a firm doesn’t have any data lineage tracking process, it can become challenging to understand where to begin. This becomes more challenging when you have thousands of data sources and integrations, isolated sets of data, and manual or outdated data management processes. 

Companies that never even plan to overcome the challenges mentioned above have to deal with a more significant issue. They also risk facing problems that cost the team more money, time, and effort. 

For achieving better data transparency, you should always work on planning a step-by-step data lineage tracking approach. Here are some of the steps that you can follow for better data transparency;

Defining the approach 

With the right type of planning, you can always overcome the data lineage challenges;

  • Pinpointing goals: It is crucial to define your goal to enhance the data lineage processes or if you want better transparency for easier compliance. By defining a goal, you can stay accountable to it, and thus you can recruit other teams for support. 

  • Anticipate scope: Analyzing how much data the firm currently processes and understanding which type of data you are now planning to track can also help you overcome the challenges of data lineage. 

  • Educating teams- All the teams working on data must be aligned. From assigning responsibilities to standardizing data vocabulary, everything should be done with precision. 

Streamlining data lineage process

It would help if you never planned to create the data lineage process manually. The effort required to assemble your data or discover your data can be overwhelming. Therefore, instead of relying on manual processes, you should start using robust tools that can help you find your data for you. These tools are going to save a lot of time for you. 

Another important thing that you can do is translate the rules into standardized data models. For turning everything automated, you should focus on turning the data into building blocks. There are many ways you can streamline the data lineage process, and by following these steps, you can consistently implement data lineage in a better way.

Get your data inline. 

An ideal data lineage tracking process will always help you align the integration and find valuable insights amongst all the noise. But with a large scale of integration used by your firm, it can become challenging to map out the workflow. 

You can overcome this issue by using a strategic approach, listing processes, assigning responsibilities, and determining goals. In addition to this, you can also use new approaches like data models for streamlining the entire process. 

If you are working with data, it becomes crucial to ensure that you are using the power of data in the best possible way and complying with the regulations. In such a situation, data lineage can help you in maintaining better transparency and can also aid in getting better insights as well. 

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