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Business Intelligence Solutions

Business Intelligence Solutions

Picture yourself getting into a car: buckle up, start the engine, and get on the road. A quick look at the dashboard tells you the essentials—speed, fuel, mileage. Your GPS shows the route, estimated arrival, and traffic updates.

You’re focused on the critical data: speed, location, and ETA. Behind the scenes, complex systems churn out detailed data, but you only see what you need to make decisions.

Business Intelligence (BI) works the same way. It processes vast amounts of data from purchases, sales, and customer behavior, but as a manager, you only see key metrics. These insights help you make smart, timely decisions.

With a BI system, transform complex data into clear, actionable insights—just like checking your car’s dashboard

BI SUBSYSTEMS

Data Collection – seamlessly gather data from diverse IT systems such as accounting software, CRM applications, and more.

Data Cleansing – correct errors and harmonize discrepancies across systems—for example, ensuring consistent customer addresses between marketing and accounting platforms.

Data Consolidation – merge all data into a centralized data warehouse, providing a “single source of truth” for your organization.

BI SUBSYSTEMS WORK WITH DATA WAREHOUSE INFORMATION BY:

  1. Presenting data in report form, much like a car’s dashboard.
  2. Performing forecasting, similar to how navigation systems estimate arrival times.
  3. Monitoring selected business parameters (e.g., sentiment analysis of reviews on Facebook or customer visitation statistics in an online store) and responding accordingly. For instance, employees might be alerted to increased website traffic so they can take action to boost sales with minimal effort.
  4. By adding additional components, data can be supplemented with statistical forecasts or insights derived from artificial intelligence (AI).

THE RESULTING REPORTS ANSWER VARIOUS QUESTIONS:

What happened in the past? For example, what was the profit in the first quarter of this year, and how did it change compared to the first quarter of last year?

Why did it happen? For example, why did sales increase by 50% in March of last year but then decrease again afterward?

What will happen in the future? For instance, will the demand for a product decrease or increase next month?

What should be done to ensure that this (doesn’t) happen again?

Each type of report increasingly relies on Machine Learning, which is implemented using the company’s accumulated data in the data warehouse and artificial intelligence. The best way to implement such systems is on the Azure cloud platform, allowing flexibility in increasing resources for AI tasks and quickly scaling them down as needed.

Ways to Implement BI Systems

On-Premises

  • Using the Microsoft SQL Server platform. This requires servers in your data center.
  • Reports would be generated using Power BI.

Azure Cloud Platform

  • Integrating various components into a single system, such as Azure Data Factory, Azure SQL, Azure Synapse Analytics, and Azure Databricks.
  • Reports would be generated using Power BI.

Microsoft Fabric

  • Utilizing the same Azure components (Azure Data Factory, Azure Synapse Analytics, etc.), integrated into a unified analytical platform.