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Data Lakes Challenges that CDOs should be Aware of

By Nikhil Sonawane - November 29, 2022 4 Mins Read

Many modern enterprises are finding it difficult to gather, store, and process in data lakes and get valuable business insights.

Business leaders need to have real-time information on their business performance and ROI. With the advent of industry 4.0, businesses are generating a large amount of data through various channels, and to process this vast amount of data, many CDOs have embraced data lakes in their tech stack. Integrating data lakes into the enterprise tech stack has benefited the DataOps team in multiple ways, but these data lakes usually lack to deliver the theoretical promises because of the following challenges:

Higher operating costs

Designing, developing, and deploying a data lake can be an expensive process with high maintenance costs. There are a few cloud data platforms that offer enterprises with open source platforms to develop a tool and manage by themselves. However, it can be a tedious task for organizations to manage and maintain these assets and will require expertise. Enterprises can also leverage managed cloud data platforms which are easier to deploy. However, this usually will have higher costs and will be difficult to manage.

Also Read: Busting Three Key Fallacies About Multi-Cloud Computing

Tedious Management

It is a daunting task for even skilled DevOps teams to design and manage data lakes. Even if organizations leverage an open-source cloud data platform or a managed service

CDOs find it challenging to develop a data lake that is scalable and deals with redundant data without compromising on security.

Challenges with gathering data

Gathering data from all the available channels and making sense of it can be a difficult task for many enterprises. Bygone are the days when organizations had copies of crucial data from their transaction systems consolidated into a data warehouse. It is a time-consuming task to structure data and cleans it with a lack of resources which creates a lag in the information flows, and users will not have real-time updated information to make strategic decisions.

Managing the large data volumes

One of the most significant challenges with managing data lake houses is to manage through the large amount of data generated. Moreover, data gathered through third-party channels might not be structured, which makes it even more difficult to interpret.

Longer time to generate ROI

Enterprises to generate a return on investment on their data lake expenditure will take longer than expected. Because once the organizations implement a data lake, it might take a while for the entire time to get acquainted with the systems and deliver value through it.

Inefficient data security and governance

The traditional cloud data system will not be highly efficient while securing data and enforcing stringent data governance policies. Enterprises, while embracing data lakes, need to consider data security and governance as a concern, which will reflect in higher operational and management tasks.

Also Read: Ways to Achieve Efficient Multi-Cloud Connectivity

Lack of Skills and resources

Another significant challenge while developing and implementing a data lake house which an enterprise has to be prepared for, is the lack of skills and resources.

There is a tremendous scarcity of data scientists and engineers that makes it challenging for enterprises to make the most of the data gathered and stored.

Other data lake challenges

CDOs need to resolve the data inconsistencies while merging various data sets. The challenges of a data lake resemble a lot of the pitfalls of data warehouses. Even though the underlying data storage layer might have evolved, but the concerns like data governance, security, metadata, data quality, and consistency are inherent challenges of the data lake that it exposes the business too.

These are a few challenges that CDOs need to consider before implementing data lakes into their IT infrastructure.

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AUTHOR

Nikhil Sonawane

Nikhil S is a Tech Journalist with OnDot Media. He is a media professional with eclectic experience in communications for various technology media brands. He brings his eye for editorial detail and keen sense of language skills to every article he writes.

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