Infinite Solutions currently covers the following business cases.
SAP BW & SAP BO Enablement to SAP HANA
This is a non-disruptive roadmap to upgrade your BW and BO environments in preparation of the implementation of your Real Time Data Platform. Yet, it represents more than just a technical upgrade. The first step consists in analysing the appropriate target architecture, what should be migrated (calculation routines, custom developments, customisation, triggers, and loading rules, info-cubes and meta-models…) and what should be defined as "hot", "warm" and "cold" data. Then data sources and cubes must be cleaned.
Regarding the migration itself, the most frequent option is the one that reduces the downtime to a minimum. The idea is to continue for a while on the existing production BW system while the migration is performed on a full copy. The copied system is first upgraded to version BW 7.3, SPS5 and then it can be easily migrated to SAP HANA.
Infinite Solutions currently covers the following business cases.
SAP BW on HANA
SAP HANA boosts BW performances in execution time for data load and queries in a truly impressive way, while at the same reducing the database size (a factor of 70% is not uncommon). But, beside these immediate benefits there are other side advantages:
- Some objects in the Data Warehouse are made redundant because of the speed of loading and querying. Physical models for InfoCubes and Datastore Objects (DSOs) have also been simplified due to the capabilities of real-time processing. These simplified structures imply simplified configuration and operational management.
- Re-modelling the objects do not require unload and reload as before. Thus re-modelling responds much faster to changing business requirements.
- The workload of the IT department is reduced due to the fact that users design and perform their own queries themselves.
It should be noted that SAP HANA represents a strong improvement with respect to BW Accelerator (BWA). With BWA, only part of the data could be accelerated, and additional work was needed to replicate this data subset from the BW database to BWA. With BW on HANA, the whole database is stored in the fast RAM memory. Furthermore BWA required another separate server with additional hardware installations and licenses plus maintenance costs.
Real-time Analytics for the utilities
In the near future, with the proliferation of smart meters, sensors, SCADA and control systems, new customer interaction channels (such as text messaging and e-mail via smart phones or Web portals, social networks) and geographical databases, the Utilities sector will definitely be confronted with the problem of handling "Big Data" in real-time for creating new business value.
The problems are multiple: the "simple" ones are reducing operations and maintenance costs while increasing energy delivery efficiency, improving the grid reliability and the effective balancing of energy demand and supply.
But there are even more impressive challenges looming in the near future. Smart grids are coming slowly but surely on the scene and it becomes clear that a truly efficient smart grid should be self-healing. This implies that it should be able to automatically detect and resolve failures such as power outages, equipment malfunction, accidents due to storms, etc….
This looks like a tall order, but the smart grid connectivity (in both sense) combined with the greatly improved real-time analytical processing capabilities made possible by SAP HANA will soon transform this dream into reality. Delays in data treatment of hours or even minutes, the so-called "latency problem", are unacceptable. The self-healing smart grid vision depends on the ability to handle big data in true real-time. In SAP's vision, the solution is a high-performance Analytics Environment able to analyse “cold” data (for example, smart meter data stored in a database) in a matter of seconds or minutes, together with real-time event monitoring of “hot” data.
Once SAP’s integrated smart grid analytics platform will be fully deployed, the possibilities for utilities will be endless. Retailers, grid operators, and power generators will be able to profile customers in detail and offer targeted energy packages. They will have the possibility to capture trend data to let the customer assess their energy use relative to their means, monitor and redirect the energy flow along the grid, bring repair teams to the correct spot more quickly and at a lower cost, etc...
BI Self-Services Analytics
The current vision of BI is essentially static. Following business demands, the IT department provides reports, as a fixed and unique view of the reality, typically two or three days behind the facts. The data is rendered in the form of predefined reports and frozen dashboards.
Today's users are no longer satisfied with simply consuming reports produced by the IT department. Enterprises evolve at a quick pace and users need more autonomy to discover the data themselves and analyse it according to their immediate needs. This requires intuitive tools, allowing business experts to produce their own reports. They should be able to experiment and change their point of view as often as they like, and have the possibility to aggregate and analyse various data in any way they see fit, not necessarily as foreseen by IT. They should be allowed to discover trends in real-time. This is typically the kind of problem that SAP HANA can solve.