Data lineage for Hive

What is Hive

Hive is an open source data warehouse system for querying and analyzing large datasets stored in Hadoop's HDFS and other compatible file systems. It provides an SQL-like language called HiveQL for querying and manipulating data. Hive also provides a mechanism for plugging in custom MapReduce scripts for more complex analysis. Hive is designed to enable easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems.

Benefits of setting up data lineage

Data lineage is the process of tracking the origin of data and how it moves through the various systems, processes, and tools within an organization. It is typically used by companies to maintain and analyze detailed information about all data assets registered within their system, such as their origin and transformation history. Data lineage information includes the steps a system follows to move data from source to destination, whooperates on the data and when, and the data relationships between different parts of the system. Data lineage can also be used to enable more efficient data governance, improve regulatory compliance and facilitate data analytics. It is an incredibly powerful tool for identifying and understanding data assets, as well as enhancing their security, trustworthiness and governability.

Why should you have Data lineage for Hive

Data lineage for Hive is immensely beneficial as it provides context and visibility into the data stored in it. It offers detailed information on data movement, transformation, and other data operations, which helps in understanding and ensuring data accuracy. It also helps organizations become more compliant with data privacy regulations by providing insight into who has access to what data and how it is being used. Finally, data lineage can be used to effectively track data gaps, quickly identify emerging issues, and streamline data-driven decision-making.

How to set up

Data lineage can be set up using Hive and secoda. Firstly, Hive should be used to extract the data from the source databases and structures it in a way that is easy to understand. Secondly, secoda can be used to map and analyze the data, creating a visual representation that depicts the data flow. Finally, secoda can be used to alert users to changes in the data lineage, ensuring accuracy of the data and improved data governance.

Get started with Secoda

Secoda is a modern data discovery tool that helps organizations quickly and easily explore and analyze their data. It provides a comprehensive view of the data stack, allowing users to quickly identify data sources, visualize relationships between data points, and uncover insights. Secoda also offers advanced analytics capabilities, allowing users to gain deeper insights into their data. Additionally, Secoda provides an intuitive user interface, making it easy for users to quickly explore and analyze data. With Secoda, organizations can quickly and easily uncover hidden insights in their data and make informed decisions.