From the course: Complete Guide to Data Lakes and Lakehouses

Introduction to data management and governance

From the course: Complete Guide to Data Lakes and Lakehouses

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Introduction to data management and governance

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- Data governance and management are core elements of a well-structured data lake. They make sure the data not only serves its purpose today, but is also secure and optimized for future use. Let's have a quick overview of some of the important concepts around governance and management. Data governance and data management are related and often confused. So what does each of them really mean? Data governance refers to establishing processes, rules, standards, and metrics that ensure the effective and efficient use of information stored in a data lake. Data management on the other hand, refers to the implementation of processes like ingestion, validation, storage, processing, and protecting data to ensure the accessibility, reliability, and timeliness of such data for its users. In simple terms, data governance establishes policies and procedures while data management enacts them. So why should you consider implementing a data governance strategy in your data lake? There are a few important reasons. Implementing a governance strategy increases trust and guarantees compliance. It makes sure data is managed according to the requirements and policies, helping you avoid legal and regulatory penalties and build trust with the stakeholders. Honestly, there's no point in building the robust data lake if stakeholders cannot trust the data in it. It can also increase data quality and consistency, which as we saw before, is so important for accurate analytics and decision making. Basically, it prevents us from creating data swamps and last, but certainly not least, it enhances security and privacy. By protecting sensitive data and making sure that privacy standards are met, you can avoid data breaches and unauthorized access. Now let's see some of the key components of a data governance and management strategy. The first is developing clear policies and procedures that govern the data ingestion, storage, distribution, and archiving. Then building and maintaining robust infrastructure that supports data governance, including tools for data cataloging, quality and security. It is also important to implement metrics and indicators that allow you to verify the effectiveness of your initiatives. This was a quick introduction into data governance and management. Hopefully it nicely sets the context for the upcoming more specific topics we will discuss.

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