Every reporting solution must be supported by a high-quality and efficient data model.
Data modeling is in many cases the most crucial stage of BI project implementation. It involves an extensive data quality analysis and directly contributes to user experience. Smooth data modeling helps to achieve optimal data flow performance and creates efficient interaction between data entities.
Data quality, its accessibility, and usage are just among the criteria that need consideration before implementing data models for your BI solutions.
Data warehouses serve as a data repository for historical and high-volume data. This type of database is usually used for building organizational reports.
A data warehouse structure differs from the more commonly used transactional database as it contains a more denormalized data schema and the ability to efficiently support historical data.
Based on the business requirements and nature of the data, we’re either using Microsoft SQL Server or Azure Synapse Analytics platforms to implement an enterprise level data warehouse.
Most of the enterprise level reports must be able to efficiently consume and analyze high data volumes. Long running queries and lack of data quality can challenge on-time decision making.
Analysis Services databases can provide a significant boost to your reporting systems. It encapsulates all necessary business rules and pre-calculates heavy calculations that could otherwise slow down your reports.
We are offering Analysis Services solutions to organizations that need a reliable analytical data engine to guarantee fast analytical operations for Power BI, Excel and Reporting Services reports.
Ad hoc data modeling is also used to support reports and dashboards that are not built already on analysis services models.
Low-quality data models are usually the main reason for complicated and inefficient reporting solutions.
We use Power BI to design data models that, together with optimized DAX expressions, support extensive and high-scale analytical operations.