A key application of big data analytics involves understanding consumer behaviors from sources such as click streams, sensors, text, and other forms of non-traditional data. In this workshop we will discuss the use of NoSQL analytics to extract value from text data captured during customer interactions for the purpose of increasing subscriber retention. We demonstrate how the Not-Only-SQL approach leveraging a combination of SQL and MapReduce maximizes efficiency and productivity of data scientists within T-Mobile through detailed examination of a specific case study in semi-structured text analytics. We also show the importance of advanced data visualization techniques when performing big data analytics. The overall architecture for optimizing the use of Hadoop alongside traditional and non-traditional platforms is presented along with our future direction in big data analytics.
– Learn about combining SQL and MapReduce for semi-structured text analytics.
– Learn about optimizing a big data analytics ecosystem with a unified data architecture.
– Learn about matching skill sets and technologies to maximize productivity for data scientists within an enterprise analytics team.