Uses of SAP HANA for Utility companies

At the recent SAP for Utilities event in Huntington Beach, SAP’s Stefan Wolf gave a presentation about SAP’s HANA in-memory database. I caught up with Stefan afterwards and talked to him about some of the ways HANA can be used by utility companies.

Here’s a transcription of our conversation:

Tom Raftery: Hey everyone! We’re here at the SAP for Utilities event and I have with me Stefan Wolf from SAP. Stefan you gave a talk yesterday, where you were talking about the use of HANA for utilities. Can you give me a little synopsis of that talk?

Stefan Wolf: Absolutely!. Thank you Tom for giving me this opportunity. I think utilities these days are challenged by a lot of different requirements. There is lots of data coming through new channels like smart metering, smart grid, social networks. It’s pressure from the regulators, pressure from the public to get more information in real time, whether it’s a storm situation or just about my current bill, it’s mounting.

So they need the possibility to answer these in real time and manage the data and we have customers who are actually doing this today, with SAP tools. For example, one utility is using an SAP HANA solution to improve business process for energy settlement and they have achieved an improvement of a hundred times faster by moving certain steps of that process outside to a HANA box including the replication of the data.

So by just using HANA, they are now able to manage even when all their customers have smart meters and still running to a settlement process in the allowable timeframe. Other customers, for example have used HANA to optimize a collection process, by building a data mod in HANA to collect the information about the customers, the financial information, the surrounding information about the customers to now be much more, on time and on top of the information, and do the correction way more efficiently than before with manual error prone process.

Tom Raftery: Is there any customer facing technology using HANA?

Stefan Wolf: Yeah absolutely, so one example is a utility is using HANA to support their online portal, basically allow the customers to do bill simulations, and they draw their smart meter data from the back end system, from the legacy system into HANA and then run into HANA say, as a billing algorithm and within less than 4 seconds of overall process of getting the data and billing the data the customer sees a stimulated bill on the online portal. So it’s literally in real time.

Tom Raftery: Stefan I’ve heard that, there are data compression technologies in HANA as well, which reduce the size of the database how does this work?

Stefan Wolf: Absolutely, so we have one example, where a customer was using their business warehouse as a test case basically for moving into HANA and it had over 20 terabytes of data in their actual business warehouse and they moved it into HANA and it ended up with less than 700 GB. That was possible but not needing quite a bit of the data which business warehouse typically needs because of the time it takes to load the data from the source system, or they’ve staging areas and so forth. And you have the segregation areas in business warehouse because it takes times to build those cubes. All of that is not necessary in HANA.

So you start with much less data to begin with and then in addition you have the compression factor HANA allows was which is typically between 4.0 and 5.0 to 1, so that reduced it so significantly from over 20 TB down to 700 GB.

Tom Raftery: So of course that makes it even faster again to analyze the data.

Stefan Wolf: Exactly, so now we have less data to store which you can analyze faster and you have an in memory which again improved the time. So between our previous in memory technology, business warehouse accelerator, which was although based on in-memory, but specifically only for BW available. And now HANA, we see even there an improvement of over five times of the reporting time and we see even 50 — effect of 50 increase of the performance compared to conventional business warehouse means.

Tom Raftery: Well, impressive. Stephan, that’s been great. Thanks very much.

Uses of SAP HANA for Utility companies

AGL Energy and building Business Intelligence maturity through self service

At the SAP for Utilities event in Singapore I had a brief chat with Mr Cameron Vagg of AGL Energy about the talk he gave there.

Here’s a transcript of our conversation:

Tom Raftery: Hey everyone, welcome to GreenMonk TV! We are at the SAP for Utilities Event in Singapore, and with me I have Cameron Vagg, Cameron is with AGL Energy. Cameron, AGL Energy, who are they?

Cameron Vagg: We’re a large Australian Energy Company; we’re a retailer and a generator of electricity and gas, but not a distributor.

Tom Raftery: Okay! Now you’ve given us an interesting talk at the event, can you talk and just give a synopsis of that?

Cameron Vagg: Sure. I gave a talk about Building BI Maturity Through Self-Service

Tom Raftery: BI?

Cameron Vagg: Self-Service BI.

Tom Raftery: Sorry, BI is?

Cameron Vagg: Sorry, Business Intelligence Maturity for Self Service and Business Objects. Essentially, we’re trying to nail down that, we think that organizations can improve their business intelligence by conducting a simple self assessment that looks at their operating model the way that they are servicing the needs of their organization and their customers through business intelligence.

What their business intelligence culture is like, and what their business intelligence capabilities are like. And in conducting that self-assessment where you’ve made some changes and I go through those and talk about what we did and how we did, and the benefits that we are seeing in terms of terms of improved capacity, speed and breadth of business intelligence.

Tom Raftery: Okay! Can you just talk me through some of the potential use cases for that?

Cameron Vagg: Yes, particular interesting sort of area that we have in Australia right now is that we’re starting to see Smart Meter rollouts, so we have about 350,000 Smart Meter customers, with 48 meter reads a day. So that presents with a data challenge and a data opportunity for us to get inside into that data.

Tom Raftery: Okay, perfect! Cameron, that’s been great! Thanks again for talking to us.

Cameron Vagg: Great! Thanks Tom, bye!

AGL Energy and building Business Intelligence maturity through self service