Kylo: Cost Efficient Data Lakes Built in 9 Weeks

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Over the past several years, forward-thinking companies have been creating custom engineered data lakes in order to store large volumes and different varieties of enterprise data in an efficient way. To get the job done, many companies have tried to use complex, custom-engineered and Hadoop-enabled open source solutions in-house. However, while the software may be free, the engineering expertise this approach requires means that most companies are looking at multi-million dollar investments right from the start.

So what’s the answer to the data lake conundrum? Having spent nearly eight years solving data lake issues for companies across all verticals while also building data lakes from the ground up for various tier 1 and 2 organizations, we have recently introduced Kylo – the open source data lake management platform that delivers data lakes on Hadoop and Spark. Based on our experience on over 150 projects, Kylo brings a lot to the table, but the first benefit all customers report is immediate cost savings on a number of levels.

A production Ready Data Lake – in Only 9 Weeks

One of the top complaints many companies have told us – is that data lakes simply take too long to build, and in the average 6-12 month build cycle, users find that use cases become out of date and meaningless to the business. Companies are literally pouring millions of dollars into data lake builds which consume vast amounts of engineering expertise – that is if they have that expertise in the first place.

Upfront, Kylo is delivering cost savings because Think Big’s engineering and data science teams can deliver your data lake in as little as nine weeks. Kylo is based on open source Apache Hadoop tools, but the difference is that our team have the specific experience, capability and skills to use this set of tools to deliver effective data lakes by applying proven templates and best practices every time. This means that companies can focus on driving innovation and results through their big data programs in just over two months.

A Built-in Self-Service Capability: Priceless

Because Kylo features an intuitive user interface for self-service data ingest and wrangling, no coding is required.

Simply put, other open source tools do not feature a facility to build a self-service capability. Building this type of full self-service facility from scratch is extremely costly and difficult because of the amount of engineering required to create a user-friendly interface.

With Kylo, your data lake engineering team is free to access data quickly and without any help, driving business innovation at vastly reduced costs.

What’s The Cost of a Major Data Breach?

Major data breaches can compromise trust and reputation, and at the end of the day, are also tremendously expensive ordeals. We’ve witnessed major breaches in data lakes built in-house at global banks where data has not been properly secured and where data is simply not governed properly.

Because Kylo has been developed on years of engineering expertise dedicated to implementing granular layers of security and permissions-based access, Kylo customers can rest easy in knowing that the data quality is consistent as well as secure and governed according to owned, documented processes. This means that the likelihood of any data breach is minimized, guarding against unnecessary data recovery spend and reputational damage.

If you have any questions surrounding Kylo, click here to get in touch today.

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