What is data lineage and why it is important. Data lineage is nothing but its origins and transformation that data goes through with time. Data lineage can also be expressed as the life cycle and end to end flow the data. This lifecycle includes the origin of the data, how it moves from source to destination (or one point to another) and where the data currently resides. Using the data lineage organizations can get a better understanding of what is happening with the data, as it flows through different pipelines (DataLake, ETL, reports etc.), and provides more visibility for the analysis purpose, which can play the vital role in making important business decisions. In general, data lineage shows the pictorial representation of the flow of the data from the origin to the destination.
Data lineage enables the companies to trace sources of specific business data, which enables them to track errors, implementing the changes in process, and implement the system migration to save the significant amount of the time.
Family Tree vs Data Lineage
The best way to understand the concept of data lineage is to think about a family tree. Having a family tree means that you know family relationships. You need to know where you come from and who your ancestors are really. A person’s family lineage can prove to be a source of valuable information for you. How? Not only does it provide you with more knowledge about your origin, it contributes to genealogy, helps you discover the death and birth rates in the family and can also be useful in identifying your medical history. While the latter is a secondary benefit of knowing your family lineage, it can have huge benefits.
Data Lineage & Debugging Challenges
Since data lineage enables the tracing from origin to source, it helps & enables data analytics and business team to replay a specific portion of data flow for step wise debugging and to regerate lost output. Traditional database systems & data warehouse ETL tools uses such information using a concept called “Data Provenance” to addreass similar validation/debugging process as part of ETL process. Lineage is simple type of why provenance.
Is Data Lineage Complicated & How visual representation helps?
It is difficult task to trace data sources. Large enterprises are created with large and small applications and system and in their desire to keep up with technology, they rapidly continued to acquire new data sources. The variety and varicity data sources have interacted with each other and the systems are now bound together. The problem is that it is difficult to understand the complicated data maze and get a simple visual flow. This is where data lineage has to be tracked and it can play a vital role in a business’s operation.
What data lineage brings into the table?
The first area where data lineage has its impact is the existence of the business itself. For instance, the planning & forecasting team considers the demographics and customer behavior for setting sales forecasts and the senior management also makes decisions based on the growth and performance statistics of a business. If there is no data, all these functions are rendered irrelevant. Therefore, it makes sense for a business to have a clear understanding of where the data is coming from, who is using it and how it is transformed.
Data lineage is also important because specific sources of data can have prominent implications. For instance, when IT teams are starting a new software development process, they will need to understand the requirements. This means they have to know about the data sources they will have access to. Locating data sources can be immensely difficult without data lineage. Therefore, a lot of businesses often use a data lineage tool for extracting data. If they don’t, they have to create new data, which doesn’t just need extra time but also leads to added expense.
For many enterprise and large organizations changes on a yearly basis. One way that it can change is that you have begun to accumulate different types of data, either in the form of product or customer data that hasn’t been collected previously or in the form of data you have bought from other sources. It is also possible that your internal data analysts have come up with ways of deriving new insights from the data you already have. This innovation could be helpful for management in making decisions or for generating a new revenue stream.
Thus, when a business gets insight into data lineage, it is able to stay updated with the changing data environment that has a lot of impact on its operations and can practice data governance.