Unleashing Exploration on Enterprise Data

This post was originally published here

Enterprise customers have huge investments in transactional data systems, yet they struggle to provide their users with flexible and timely exploratory access to this data. One solution to this problem is to empower these users with the ability to use Jupyter Notebooks and Apache Spark running natively on z/OS to federate analytics across business critical data as well as external […]

Author information

Dan Gisolfi

Dan Gisolfi

Client-facing, strategy and development engineer responsible for architecting, implementing and running next-generation cloud applications on Bluemix, SoftLayer and private clouds.

The post Unleashing Exploration on Enterprise Data appeared first on IBM Emerging Technologies Blog.

Related Posts

Forecasting Time-Series data with Prophet – Part 2 In Forecasting Time-Series data with Prophet – Part 1, I introduced Facebook’s Prophet library for time-series forecasting.   In...
Visualizing data – overlaying charts in python Visualizing data is vital to analyzing data.  If you can’t see your data – and see it in multiple ways – you’ll have a ha...
Forecasting Time-Series data with Prophet – Part 1 This is part 1 of a series where I look at using Prophet for Time-Series forecasting in Python A lot of what I do in my data analytics work is underst...
Getting Started with Kaggle: House Prices Competition Founded in 2010, Kaggle is a Data Science platform where users can share, collaborate, and compete. One key feature of Kaggle is “Competitions&r...

Leave a Reply

Be the First to Comment!

Notify of