Data Warehousing &
Data Architecture
Organising and centralising data to deliver an enterprise view of your company - improving ability to use data to drive business success.
Overcome these common challenges that arise from rigid or aging architectures:
Incapacity to handle data instantaneously or with minimal delay
Challenges in managing large-scale data (massive quantities, streaming, and diverse data sources and formats)
Discrepancies in data collection, processing, and utilization methods
Inadequate infrastructure to sustain advanced analytics requirements
We assist to incorporate disjointed data assets, combining them into a data warehouse (cloud or on premises) so as to deliver an enterprise view of your company. These data warehouses are the cornerstone to good accurate reporting and analytics, providing that all important “one source of the truth”.
Steps:
Determine the goals, objectives, and business processes for your organization to lay out a blueprint for success.
Design a comprehensive and functional data warehouse dimensional model (OLAP, star schema, snowflake schema, etc).
Develop operational data stores (ODS) for interim data storage.
Identify and define the type of data being stored and the sources being used.
Launch a tiered deployment to ensure successful implementation.
Leverage ETL best practices, including development, tuning, and maintenance.