Data Lakes Driven by Kylo: Unparalleled Speed to Market

Comments (0)

For many companies, working with data lakes has become a frustrating and unsuccessful experience: instead of being focused on building analytics and improving the quality of the data lake, engineering teams often spend most of their time dealing with requests to ingest new data sources or wrangle data. As a result, they have little time left to focus on data improvement and delivering value from big data analytics. Using Kylo, our open source data lake management platform, companies are able to generate valuable insight from their data lakes faster, bringing innovation via products and services to the market at unparalleled speed.

So Why is Kylo Faster than Traditional Data Lake Approaches?

Simply put, most data lakes are inaccessible to users without an engineering background because all interactions, including ingesting new data sources to querying data, must be initiated via complex queries that require coding knowledge. In these instances, engineering teams become a bottleneck for business users, who must submit approval processes to begin any new data transformation. In short, these builds and repeated processes may be simple, but they are also very time consuming.

Kylo is helping companies bypass this entire process by putting the power back into the hands of the business user. Using Kylo’s simple, self-service interface, enterprises are able to access data and rapidly build new use cases and analytics tools without entering a single line of code. By providing proven templates easy to use by non-tech resource, Kylo empowers the consistency of data quality, encryption and masking standards that many organizations are regulated by.

Lifting the capability up out of the programming realm makes building data sources for business users easier than ever before. Once data is ingested, Kylo features a visual SQL builder as well as a spreadsheet interface, exposing over 100 transformation features to help data analysts wrangle data before publishing and scheduling feeds. This means that all manner of big data driven products and services development can be accelerated.

Using Kylo, businesses are able to query data within hours rather than months. This means that their teams are able to deliver insight against big data faster than ever before, rather than being stuck in slow cycles and bottlenecks. With business users freely able to access the data lake, technical consultants are free to do more of what they really want to focus on: building complex transformations.

Kylo: Timely, Productionized Use Cases

In dealing with custom engineered data lakes, IT often allocate extensive budget building a huge team who spend months or years bringing a data source in without really consulting the business what the use cases are.

Ultimately, IT doesn’t get the buy-in because the business doesn’t understand how to get value from the data. Because it takes so long to ingest a new data source and productionize the new use cases while also managing data quality and governance, the business may get bored and go away to find other tools. What it means is that companies can end up with userless data lakes with no subscribers and no business stakeholders involved.

Kylo helps to move away from the userless data lake dilemma because it allows technical teams to quickly get to building the features that excite the business and solve real problems.

In the Kylo blog, we’ll take a closer look at how Kylo’s self-service graphic user interface is helping business users ingest, find and wrangle data.

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

Visit for more information and to speak with the community.

Leave a Reply

Your email address will not be published. Required fields are marked *