Srinivas Challa
Immediate joiner | Ex Infoscion | SAP BW/4HANA | SAP BW | SAP Business Intelligence | ABAP CDS Views
- Role
- System Engineer at Infosys
- Location
- Hyderabad, IN
- LinkedIn followers
- 500 followers
About Srinivas Challa
Open to Work | SAP BW/4HANA & Embedded Analytics Consultant I am an SAP BW/4HANA…
Experience
System Engineer
Jun 2022 — Present · Chennai, IN
Created Data sources from extracting from SAP & Non-SAP sources to BW system based on Function Modules and User exits for Bex Variables. •Extensive knowledge on LSA, LSA++, Composite Provider, Advanced DSO and open ODS view using BW Modelling Tool in Eclipse. •Eliminated data duplication and restructured the data models to increase query performance. •Proficient in creating and customizing Data Sources, Info Objects, ODS, Info Cubes, Mult Providers, Info sets, Transformations, Info packages and Data Transfer Process (DTP). •Worked on BI related ABAP coding in routines like (Field, Start, End) for the successful transformation of data. •Developed dashboards and reports using Bex Queries and Analysis for Office that are in accordance with Business needs. Controlled maintenance of system activity by managing the PSA size and updating the useless logs.•Streamlined SAP BW/4HANA process chains by aligning tasks with reporting deadlines and introducing optimized scheduling and parallel processing.•Managed end-to-end data flow across ADSOs, InfoObjects, and Composite Providers.•Handled incident resolution, fixed process chain errors, and optimized runtime performance.•Delivered dashboards using BEx Query and Analysis for Office tools based on user requirements.•Maintained PSA management and request log cleanup to ensure system efficiency.•Designed and optimized Core Data Services (CDS) views to enable high-performance real-time reporting in SAP Analytics Cloud (SAC) and SAP Fiori.•Built advanced data models using associations, joins, and calculated fields to support business reporting needs.•Implemented complex logic within CDS views for dynamic aggregations and filters, improving analytical capabilities.•Focused on data model efficiency, reducing data fetch times, and improving report performance for end-users.
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