Empowering data analytics with our data lake management software platform
We help you prioritize and plan your implementation, while considering business impact, existing data, technology and skills.
Our technology best practices and pre-built framework components work with a variety of platforms and tools that accelerate time to value.
With open source tools at the core, we help organizations build big data infrastructures that can easily adapt and scale to meet your future needs.
Our Data Scientists excel at identifying opportunities and insights from unstructured and non-traditional data sources.
Our managed services support big data platforms and applications. Our experts use well-defined processes to deliver continuous improvements.
Our certified experts provide a variety of courses in Hadoop, Spark, NoSQL, Cassandra, Cascading and Big Data Concepts.
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.
Think Big's enterprise-ready, open source data lake management platform, Kylo, is built on Apache Spark, NiFi and Hadoop to help organizations get the most value out of their data. Using Kylo, Think Big has been able to help customers to integrate and simplify pipeline development and data management tasks, resulting in faster time to market and greater user adoption. From data lake build struggles, to building complex transformations in just 9 weeks instead of months or even years, Kylo enables organizations to significantly reduce costs across the board.