HANDS-ON WITH BIG DATA VIA LUMIRA - PART 3

In my previous post, we have covered on how to setup & analyse in big date in Hadoop environment via Hortonworks Apache Ambari portal: Big Data Sample Setup & Visualization in Ambari.

The data is already in Hortonworks hadoop big date environment. Let’s try to incorporate the data into SAP environment. Choosing SAP Lumira in this case. Why choosing SAP Lumira out of other SAP BI Portfolios?

“SAP Lumira Server is a native SAP HANA application that is deployed directly on the appliance and therefore has a natural ability to work on complex or large data and leverage the full power of SAP HANA.” By Product Manager of SAP Lumira Server 

Useful blog to understand : future roadmap of SAP Lumira.

1) Choose the Apache connection driver

2) Key in Ambari login credentials and port details

3) From the above screen, click “Advance” button to specify driver properties.

4) Connect to Hortonworks hadoop Hive tables. All the available table setup in my previous post now reflecting in SAP Lumira.

Analyse Big Data in SAP Lumira

Data from .ORC(HIVE) now available in SAP Lumira via Hadoop connection. Remember the Truck data we have loaded in HIVE? Going to use that data to create a LUMIRA story Board.

1) Choose all the data from “truck_mileage” table

2) Choose the relevant dimension and measures for visualization

3) Create Visualization

4) SAP Lumira storyboard, showing “Top 10 Trucks with Best MPG” & “Top 10 Trucks with Worst MPG”. Which purely derived from big data source. *Mileage per gallon(MPG). With such information, the transportation company know which are the truck needs more attention for service & maintenance. Which can reduce cost of operation & improve income per truck in long run. And the information is readily available for business users in an intuitive display, SAP LUMIRA.

Disclaimer: My original post in 2017, reposted here again to centralise my digital profile in one single location, in dataChief. And to share the knowledge with any members starting with big data.