Diligent technology teams partnered with client teams to co-create and implement technical solutions supporting ongoing business strategies. Selecting and evaluating new technologies, defining product development road maps, identifying testing strategies, and implementing to delivery excellence were key components of the successful project. Multiple technologies were involved and end-customer experience was a key priority that was diligently followed resulting in accelerated feature releases and cost savings in terms of on-boarding technical expertise.
The largest state-owned natural gas processing and distribution company in India. … It has the following business segments: natural gas, liquid hydrocarbon,
liquefied petroleum gas transmission, petrochemical, city gas distribution, exploration and production, GAILTEL and electricity generation.
- Looking for enhanced scalability and performance for faster decision making in Marketing sector.
- Implement increased flexibility through SAP BO Design Studios leveraging parallel processing of data sources for dashboard development.
- Reduce the TCO and improve development efficiency and Accelerate financial reporting
- Existing BW environment too slow to permit analysis and reporting on purchases
- Implement BW on HANA DB footprint Solution
- Non disruptive DB migration with SAP standard tools and service has been achieved
- Using HANA optimized DSO(advanced) and Composite providers has speeded up the data staging by a factor of 10 to 15 with a complete integration of delta calculations
- Additional modeling flexibility has be achieved by combining ad-hoc SAP HANA data.
- Data persistency layers are cut out and admin efforts reduced: No aggregates, indexes, rollups, statistics.
- Stream line landscape and simplify data management using HANA Optimized Data models.
- Reporting runs 33 times faster than the legacy database with real time monitoring of sales
- 5.5 times improvement in data compression ratio
- CMD team are getting timely inputs on financial status
- Processing of transactional updates also accelerated
- Average query time reduced from 7 minutes to 0.7 seconds