SQL for Data Science: Using Analytical Function

Doing more by writing less Python code and instead use SQL Analytical Functions

Brendan Tierney

Analytics Data Databases

See in schedule

Most developers are familiar with SQL for accessing and retrieving data. Over the past few years the SQL language has developed significantly with many features available for analyzing data in a more efficient manner. This presentation will focus on some of the newer SQL analytical functions, what they do and what problems they can be used for. With efficient use of SQL analytical functions, means less data to process in our Python programmes, and with quicker results, means it is a win-win for us. Do More with Less by using SQL analytical functions.

Type: Talk (30 mins); Python level: Beginner; Domain level: Beginner

Brendan Tierney


Brendan Tierney, Oracle GroundBreaker Ambassador and Oracle ACE Director, is an independent consultant (Oralytics) and lectures on data science, databases, and Big Data at the Technological University Dublin. He has over 27 years experience working in the areas of data mining, data science, machine learning, big data, and data warehousing. Tierney has published four books, three with Oracle Press/McGraw-Hill (Predictive Analytics Using Oracle Data Miner, Oracle R Enterprise: Harnessing the Power of R in Oracle Database, and Real World SQL and PL/SQL: Advice from the Experts) and one with MIT Press (Essentials of Data Science). 
Web and blog: www.oralytics.com
Twitter: @brendantierney