Published on 15-Mar-2012
Validated on 07 Oct 2013
Business Analytics, Data Warehouse, Smarter Computing
In this video, Andreas Happel, the Director of BI Services for MACH International, discusses how they are taking their Business Intelligence to the next level with their Netezza Data Warehouse appliance.
In 2010, MACH International began to look into DWHs as there was a growing customer need for transaction level detail information. Hence also the need to now increase the data volume and level of granularity in system.
The new analytics that are enabled by IBM Netezza 1000 as of today are really going down to make calculations or analysis based on location and other areas structured around the single subscriber, allowing MACH to drill-down to a very granular level.
- Can analyze their subscribers' behavior - Unique product offerings, like single transaction analysis - Disk scanning time reduce from hours to 5 minutes
With more than 750 different mobile operators WW, MACH International discusses how they are using the IBM Netezza data warehouse appliance to run transaction level analytics. The ability to report and analyze the massive amounts of data, has made it possible to drill-down to a very granular level and better understand their customers.
The IBM Netezza data warehouse appliance transformed the data warehouse and analytics landscape with a platform built to deliver extreme, industry-leading price-performance with appliance simplicity.
Director, BI Services
MACH, Multinational Automated Clearing House
For us, business intelligence is a window into what our customers are processing and having as data flowing through our systems. It allows them to, first of all, analyze what’s happening from an operational perspective as well as taking a closer look at the more analytical part in regards to strategic decisions – what’s going on with their customers, when are they using services, what’s happening, and how the traffic as well as the kind of service growth is evolving over a period of time.
By definition our business is pretty much residing on large scale data volumes. We’re processing call transactions throughout the network of about 750 different mobile operators worldwide. Hence it’s a massive amount of records which is flowing through our system.
The whole business on the roaming side which used to be a fairly granted business, where everyone was looking into a given revenue stream, is now a very competitive business and people are really looking into addressing also the kind of different subscribers, the different profiles of users, specifically with marketing campaigns, with new services, and therefore also need to have a means of analyzing that detail of data in a BI solution.
That was the point where we were looking into other technologies which would enable us to process these large volumes of data – as we would be looking at about a 10x increase in data volumes.
The new analytics which are enabled by Netezza as of today is really going down to making calculations like the average revenue per user in the system, making calculations or analysis like how many distinct users have been using a certain service in certain area, and allowing us to really go down to very granular level meaning going into location based analysis and other areas which are really structured around the single subscriber.
There’s no typical DBA work to be done on our side right now, like table spaces, looking into physics of the database, which they do on the Oracle side.
Netezza helps us position in marketplace in a kind of unique way, as the analysis of single transaction has been kind of a holy grail in this industry for a long time. It was not really possible offered by us and also by our competition at that point in time. It really allows us as a unique selling factor to bring in something which we have as MACH and allows our customers to do…which is needed from their side more and more in today’s competitive market.
Products and services used
IBM products and services that were used in this case study.
IBM Netezza 1000