A successful data-driven organization has to provide the right tools for its data analysts, developers, and business end users. Increasingly, this means leveraging open-source software. The R or Python programming languages, along with the Apache Spark and Hadoop data frameworks, are preferred open-source tools for many modern analysts and developers. But for all their benefits, popular open-source data programs also come with potentially time-consuming drawbacks.
Read this IBM Analytics paper to find out how to handle these drawbacks: