IT Explained: What Is a Data Lake?


The world is becoming double its size every year and turning into a digital universe. The size is been determined by the necessity of data. Every day, over 2.5 quintillion bytes of data is generated across the world and it is expected to grow 5.2 zettabytes by 2025. The pandemic also influences the rapid surge in 2020. To manage a large number of data requires a solution like a data lake.

Modern businesses are highly dependent on vast and diverse data, and data centers are the key to produce big data. More than 90% of the data is semi-structured or unstructured that has initiated a two-fold challenge. As such, 95% of business owners are looking for a way to manage unstructured data. All of them need an exclusive and organized solution to ensure the safety of the influential organizational data and information. This also requires upholding the capacity with a faster processing facility. Therefore, the data lake can be a perfect solution.

What is a data lake?

A data lake is a central storage repository that holds the big data from the sources in its original format until the businesses use it. The data can be structured, semi-structured, or unstructured with the flexibility to use in the future. This makes a data lake combined with various points and shapes of raw data providing useful insights for customization to meet the customers’ needs.

Data Lake
Image: Faraha Rahman Lamiya

Storing data in data lake associates with identifiers and metadata tags for a quick rescue. It includes hundreds of terabytes or petabytes to store simulated data from operational sources including databases and SaaS platforms. A data lake can also be used as a source platform that enables data storage and support tools to understand data through quick exploration for advanced analytics. It keeps track of the lineage, imposed security as well as centralized auditing maintaining its standard.

Who needs it?

Thomas H. Davenport, the President’s Distinguished Professor in IT and Management once said, “Every company has big data in its future and every company will eventually be in the data business.” This is how data storing is accustomed in data lake because it is constituted on an assembly of reasonable and ascendable service. Businesses are influenced by data lakes as it helps in creating a centralized place for managing infrastructure. Every organization can manage, store, analyze, and classify their data dumped in the lake. They can always use it for further need because it either exist on-premises or in the cloud.

If your organization adds value from the generated business data, then the possibilities are high to beat your peers. According to an Aberdeen survey, the organizations earned 9% revenue growth than the others for the implementation in a data lake outperforming. They became the leaders to enable new analytics like machine learning from newer sources stored in the data lake. It created certain opportunities for faster business growth by attracting and retaining customers, enhancing productivity, proactive device maintenance, and informed decision making.


The benefits of a data lake for businesses include:

  • Data remains available and ensures that the employees can have access whenever they need it.
  • The inexpensive accendibility to store vast of data adds financial value to the businesses even though it requires some formal orientation for processing and analyzing.
  • Data lake offers variations and the companies can hoard data in the future as it is saved in native format so it can be used and added multiple times without restrictions.
  • Adaptive to inherent changes according to the advancement in data technology makes it easier to recover the necessary data in the future.
  • The leverage of data lake enables real-time analytics by providing quality data and deep learning algorithms to emphasize the decision analytics of the business.
  • The flexibility to support SQL and other programming languages gear up the advanced requirements.
  • Resourcefulness is another benefit as data stored in the data lake can have diverse sources and multiple media, chat, social data, binary, or any other format.

Storage and computer possessions are dissociated to keep the rest of the data on budgeted object storage like Hadoop on-premise or Amazon S3. Various tools and services like Apache Presto, Elasticsearch, or Amazon Athena can be used for a data query.

The data lake has originated the approach of “store now, analyze later” with a little effort of ingesting data into the lake. It is often defined to be a big data structure to oblige multiple analytic services. But still gives a single pace to save and access valuable enterprise data and upsurge business threshold as well as benefits to its users.

YouTube: Explanation by Adam Kocoloski, IBM

Photo credits: The feature image has been taken by Becca Tapert. The infographic in the body of the article has been made by the author for TechAcute.
Sources: Jacquelyn Bulao (Techjury) / Data Ideology / Aberdeen

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Faraha Rahman Lamiya
Faraha Rahman Lamiya
Hi, this is Faraha, an enthusiastic tech journalist at TechAcute. Thanks for reading my article. Hope you liked it. I try to give you the latest updates regarding exciting technology innovations or something you would love to learn. If you wanna say Hi, knock me wherever you want.
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