GM Big Data service
Big data analytics can deliver massive value, but too often companies let technology guide their efforts. Instead, decisions must be based on business priorities.
Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source.
Big data helps customers Improve decision making, Understand its customers, Improve customer offering, and finally Improve its operations.
Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. These massive volumes of data can be analysed and used to address business problems you wouldn’t have been able to tackle before.
Preliminary discusion, business goal identification and clarification
- Anchor to business value
- Pragmatic approach to IT
Initial data source assessment and verification
- Analysis, identification and escalation
Definition of new data structure based on existing and incoming sources
Data manipulation and reorganisation
Big Data analysis and reporting
- Implementation of insights into key areas of business as agents of change
Review results, change parameters and repeat the process.
Agile and prototypical approach, establishment of data governance standards, understand the data quality tradeoffs between in-stream, real-time, and batch analytics.
Visualization, data mining, Storage DB, Data processing, Data architecture