Sentence examples similar to implement data analytics from inspiring English sources

A similar gap now exists between those companies who have thought about implementing data analytics to examine their business operations and those who are actually doing it.

Nonetheless, the company has huge ambitions for its future, aiming to be a comprehensive business intelligence platform, implementing data analytics, social publishing and even smart paid-for promotion of social media posts using the various platforms' advertising APIs.

By implementing data analytics into their everyday marketing endeavors, Pizza Hut has created 6,000+ customer behavioral groups, empowering the brand to predict future purchases and execute campaigns at preferred times via customers' preferred engagement channels (direct mail, email, text message and more).

Until recently, however, businesses have been less quick to implement big data analytics in supply chain management than in other areas of operation such as marketing or manufacturing.

In the next two years, 6,400 organizations with 100 employees or more plan to implement big data analytics, providing ample opportunities for a new crop of startups that collect, refine and interpret data to populate the HR analytics landscape.

In the next two years, 6,400 organizations with 100 employees or more plan to implement big data analytics, providing ample opportunities for a new crop of startups that collect, refine and interpret data to populate the HR analytics landscape.

Robinson recounted his experience with the Vice President of Supply Chain of a Fortune 100 company who had implemented data-driven analytics in 80 factories for two years.

This chapter presents innovative systems existing on clouds for designing and implementing scalable data analytics applications.

Therefore, new data analytics stacks have emerged as environments that provide the necessary underlying infrastructure for giving access to data collections and implementing data processing workflows to transform them and execute data analytics operations (statistics, data mining, knowledge discovery, computational science processes) on top of them.

We are also implementing big data analytic tools to empower the processing part through Hadoop and Spark.

We describe our experience using Overlog and Java to implement a "Big Data" analytics stack that is API-compatible with Hadoop and HDFS, with equivalent performance.