Data is the main part of every machine learning model. Your model is only as good as the data it’s built with, and you can’t build a model at all without data. So, it makes sense to train your models only with accurate and authentic data.
In the course of running their operations, many organizations arrive at a point where they need to improve data tracking and transferring systems. This improvement might lead to:
- finding errors in the data,
- implementing effective changes to reduce risk.
- creating better data mapping systems.
Some writers say that data is the new oil. And just like oil becomes fuel for powering your car, data also has to go through a process from raw data to a model component or even a simple visualization.
Data scientists, data engineers, and Machine Learning engineers rely on data to build correct models and applications. It can help to understand the necessary journey of the data before it can be used to build accurate models.
This concept of a data journey actually has a real name — Data Lineage. In this article, we’re going to explore what data lineage means in machine learning, and see several paid and open-source data lineage tools.