Key Facts to Know about Data Lakes and their Significance

This is the era of Big Data. Every enterprise today is dealing with large volumes of data gathered from various sources. One of the biggest challenges faced by the enterprises today is, in fact, the analysis of this enormous volume of data. What every business needs today is a data strategy to manage and analyse the data in an effective manner so as to derive key insights hidden within the depths of the data. The insights from enterprise data can be instrumental in informed decision making.

Most enterprises today store and manage their data on the Cloud, because of the advantages it brings. Talking about data storage, one of the widely used terms that one comes across is data lakes. So, what is a data lake and why do enterprises need one?

What is a Data Lake

Every organisation has large volumes of data in various formats. The repository built to store, manage and process large volumes of enterprise data in its native format is referred to as a data lake. Furthermore, data lakes are ideal for structured, semi-structured as well as unstructured data and also have no restrictions when it comes to the size of the data.

Key Facts about Data Lakes

Now that we're aware of the concept of a data lake, let us look at some interesting facts about data lakes.

  • A data lake is different from a data warehouse. A data warehouse consists of data that is highly organised and so it is only meant for structured and optimised data. A data lake, on the other hand, is relevant for all forms of data, including unstructured and semi structured data. Both of these are essential for effective data management.
  • Even though a Data Lake contains data in its native form, this data can be effectively analysed for key insights. Moreover, the data in a data lake can also be used to operate applications and dashboards, through effective data management.
  • Machine learning is one of the key components of data lakes, which is a technology that helps in effective analysis of data to derive insights that are the most relevant to the business. Also, machine learning is useful to pull information from the large volumes of unstructured data that is stored in the data lakes.
  • One of the most significant advantages of a data lake is the fact that it allows the enterprises to analyse the data without the need to optimise it. This makes data lakes one of the most valuable assets for enterprises today.
  • Data lakes allow enterprises to break the barriers separating the different forms of enterprise data and bring all of the data together at one centralised repository.
  • Data lakes are highly scalable and can be used for multiple purposes. It allows enterprises to incorporate mining technologies like artificial Intelligence and machine learning for effective analysis of data. Also, the flexibility of having all of the enterprise data at one location, simplifies data management.

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Read: Top Big Data Trends to Look for in 2021
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