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.
While the vision for data lakes has always been focused completely on making data more quickly available, few companies have managed to meet the challenge of satisfying the needs and of business end users as a central focus...
Maurizio Colleluori looks at the five major reasons behind data lake failure, pinpointing what businesses need to do to get back on the path to success. The reality is that data lakes are failing to support the time-to-market requirements new analytics-driven innovation requires, and it is safe to say that in many companies, data lakes are widely perceived to be expensive and ineffective. So why is it happening? In this article, we look at some of the common culprits turning data lakes into data swamps, and at the same time deliver advice based on experience to help companies from experiencing data lake disasters.
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.