Data warehouse

KPMG’s approach to data warehouse implementation and due diligence projects is to first develop a list of proposals based on the needs of the different business areas involved, which can include reporting specifications, reporting gaps, incorporating business calculation/transformation rules, data availability analysis, identifying missing data and data transformation processes.

Thereafter, based on the prioritised list of proposals, it is possible to plan and redesign the future BI and data warehouse architecture, data model, data transformation loading procedures and data markets.

The final step in our methodology is to develop a data warehouse in line with the agreed future target status, and a BI solution based on the data warehouse.

Our services

Data warehouse strategy development, design and construction


Integration of new data sources, due diligence of existing data processes

Development of monitoring solutions

Design of a new data presentation layer (views, data cubes, data markets)

Compliance testing of fitting business transformations into the data stream


Reviewing, and if necessary fine-tuning, access rights at data warehouse and reporting level

Development of controls to promote and enforce high data quality

Data lake

KPMG’s experts can assist you with data lake solutions, implementing various data loading processes, whether they be sensor data, telemetric data, log entries or the processing of individual free-format data types.

Corporate data assets can grow via analytical data analysis processes capable of processing large volumes of data, which KPMG designs and develops on demand, also helping to expand existing solutions.

Our services

Mapping and developing use cases

Preparing data inventories on source systems or untapped data lake solutions


Designing and constructing data lake environment

Designing and constructing data lake environment

Expanding existing data lake solutions to include further source systems

Data extraction and analysis proposals


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