Datawarehousing
Our Data Engineers can integrate various operational sources into a central repository.
This process involves collecting the data from the various operational sources (data landing), historicising and storing them if necessary (data store) and finally modelling them (data warehouse).
A key advantage of a data warehouse is that it becomes the single version of the truth.
Many of our Data Insights projects thus start off with a data warehouse as the source.
Tools: Azure Synapse Analytics, Azure Data Factory, Azure Data Warehouse, Azure Databricks, SQL Server Integration Services (SSIS)
Semantic layer
The semantic layer is where the translation between IT and the business happens.
Here we prepare the data that are available in the data warehouse for reporting. The data are further modelled with the necessary relationships and logic is added in the form of calculations. This is easier for business users to understand and enables (self-service) employees to gain insight into their data.
Reporting and analysis
Based on reporting, we enable your employees to consult the right data at the right time. We construct a modern analytics platform, one which is robust and scalable, and is based on your needs.
Tools: Power BI, SQL Server Reporting Services (SSRS)
Dashboards and scorecards
Defining and adhering to your KPIs is essential to your business strategy and for monitoring your operational activities. As well as building insightful reporting, we also help you to set up dashboards.
Tools: Power BI, SQL Server Reporting Services (SSRS)
Self Service BI
A BI solution is not complete if it cannot insert external data from the market or unstructured data and integrate them easily with existing data present within the company or in the cloud. Power BI is unquestionably the best and most flexible solution for this and it is easy to use for any type of user.
Tools: Power BI