Microsoft Business Intelligence to Drive Robust Analytics and Insightful Reporting
Business intelligence (BI) suit from Microsoft comprises a set of tools to build smart analytics solutions. Being a Microsoft Gold partner, ScienceSoft renders Microsoft BI consulting, implementation, and support services to help companies transform data into intelligent immersive visualizations.
Microsoft offers a wide technology stack for implementing cloud, on-premises, and hybrid analytics solutions. The portfolio includes tools for data ingestion, storage, integration, quality management, processing, and building intuitive reporting.
Two Pillars of Microsoft-Based BI Solutions
The combination of Microsoft BI tools from the diagram above can be used to create a BI solution, though two names appear in real-life projects more often than others: Microsoft SQL Server and Microsoft Power BI.
In 2018 (for the sixth year in a row), Gartner has positioned Microsoft with its SQL Server technology as a leader in operational database management systems.
Microsoft SQL Server is a database management system that:
In 2019 (for 12 consecutive years), Gartner has recognized Microsoft with its Power BI tool as a leader in analytics and business intelligence.
A highly user-friendly self-service analysis and visualization tool, Microsoft Power BI allows:
Microsoft Power BI in Action: Demo
View our demo to see how a BI solution implemented on Microsoft Power BI helps to run root cause analysis.
Pricing for Microsoft Business Intelligence Tools
Microsoft has several licensing options for different BI software: it can be billable per user (as in the case with Microsoft Power BI), per core (i.e., Microsoft SQL Server), or per hour (as most of the Azure cloud services).
Being an official reseller of Microsoft licenses and having 16 years of Power BI consulting and implementation practice, ScienceSoft can calculate the pricing of Microsoft BI platform that your particular project needs.
Mapping your business needs to Microsoft technology stack.
Designing a high-level architecture for your analytics solution.
Elaborating on implementation and user adoption strategies.
Deploying and configuring all the components of the analytics solution. For example, implementing a data warehouse on SQL Server, OLAP cubes on SQL Server Analysis Services and visualization on Power BI.
Applying SQL Server Integration Services (or another relevant Microsoft BI tool) to create ETL processes and build up complicated data flaws to ensure proper data integration from multiple sources.
Setting up data management practices with SQL Server Data Quality Services.
Creating and training machine learning models (if any) using Azure Machine Learning service.
Being a Microsoft Gold partner, ScienceSoft can help you tick all the above mentioned points.