Practical SQL queries are central to data analysis, including selecting films, finding special features, listing active customers, and more. Homework assignments reinforce learning through ...

These qualities of SQL and other factors pushed data analysts to write code that’s difficult to share or repurpose. Thinking back on those agile principles, data analytics wasn’t doing so great.

Key Takeaways Data Analytics courses help professionals develop core skills to boost their careers in the competitive job ...

With growth in unstructured big data, RDBMS is inadequate for big data analytics. Know how to use SQL and MapReduce for big data analytics, instead.

Data analytics involves analyzing raw data to see if patterns, trends, or insights can help inform you of your data set. Data analytics involves collecting, cleaning, then compiling the data in ...

“ I wouldn’t have gotten the internship offers and ultimately the full-time job I have now without the data analytics credentials I gained at BC. Human resources, like all fields, is becoming ...

Prophecy has announced the release of Prophecy 3.0, to provide first-of-its-kind, low-code SQL capabilities for business data users.

Queries against SnappyData can be written as conventional SQL or as Spark abstractions, so existing work done in both paradigms can be reused, alone or together, on the same data.

In SQL Server 2016, high-performance parallelized R services, built right into the database, can interact with T-SQL constructs, essentially bringing the analysis to the data instead of bringing ...