Understanding Analytic Systems

Analytic systems are critical to managing and making sense of large amounts of information in today’s data-driven world. These systems are organized collections of data that can be easily accessed, managed, and updated. They enable users to store, retrieve, and manipulate data in an organized and efficient manner.

Analytic systems are usually composed of three tiers, which are used to manage data at different levels. If you’re planning to use an application stack for your business, it’s imperative you understand these three levels and the tools that are used to manage them.

Bottom (Database) Tier

The bottom tier of an analytic system is typically the database tier, which is responsible for data ingestion, ETL (extract, transform, load), and storage. This tier is critical for the success of an analytic system, as it determines the speed, scalability, and reliability of the system.

The data ingestion process involves the extraction of data from various sources, such as databases, files, or APIs, and the transformation of the data into a format that can be easily stored and analyzed.

The ETL process is then used to clean and normalize the data to ensure consistency and accuracy. The data is then stored in a database, which can be a relational or non-relational database, depending on the requirements of the system.

The database tier should be designed to handle large volumes of data, support complex queries, and provide fast access to data for analysis. It is essential to ensure that the database tier is properly configured, optimized, and secured to ensure the integrity and availability of the data.

Middle (Analytics) Tier

The middle tier of the system deals with crunching numbers, analyzing data, and applying algorithms to turn the raw storage from the bottom tier into usable metrics and measures.

In many cases, an SSaS, which stands for SQL Server Analysis Service, is the brains of an analytics system and is responsible for managing the data analysis and processes.

Additionally, the middle tier may include machine learning algorithms, which can be used to build predictive models or to automate decision-making processes.

Top (Presentation) Tier

The top tier of an analytic system is the view level. It is so-called because of the way in which data is presented to users. It includes the user interface, reports, and queries that are used to retrieve and analyze data.

This presentation tier is also responsible for showing visualizations and reports based on the analyzed data. These visualizations can help users easily understand and interpret the data, allowing them to make informed decisions.

Analytic Systems Platforms

There are two well-known and popular platforms for analytics: Power BI and Tableau. Power BI is a user-friendly tool that enables users to create dashboards, reports, and data visualizations quickly and easily. It is the top-level tool for managing data at the view level. Power BI addresses all three levels of the analytic system for users who do not want to manage the other levels themselves.

Tableau, on the other hand, is a more advanced tool that is designed for data analysts and business intelligence professionals. It provides users with a wide range of tools and resources for managing data at the view level, but it can be more difficult to use than Power BI. Tableau is often used by organizations that require advanced data analysis capabilities.

More About Power BI

Power BI is a suite of business analytics tools that allow users to analyze data and share insights. It was developed by Microsoft and is part of the Microsoft Power Platform. Here are some of the key capabilities of Power BI:

Data Visualization

Power BI allows users to create visually appealing and interactive reports and dashboards that can be customized to meet their needs. Users can select from a range of charts, graphs, and other visualizations to display their data.

Data Modeling

Power BI includes a data modeling engine that allows users to transform and shape data from various sources. This makes it easier to create accurate and reliable reports and dashboards.

Data Exploration

Power BI allows users to explore data in a variety of ways, such as filtering, sorting, and grouping. Users can also drill down into specific data points to get a more detailed view of their data.

Data Sharing

Power BI allows users to share their reports and dashboards with others within their organization, or externally. Users can also collaborate on reports and dashboards, allowing them to work together to gain insights from their data.


Power BI integrates with a wide range of data sources, including Excel, SharePoint, Dynamics 365, and many others. It also integrates with other Microsoft tools such as PowerApps and Microsoft Teams.

Overall, Power BI is a powerful tool for analyzing and sharing data. Its capabilities make it an ideal choice for businesses of all sizes that must make data-driven decisions.


Analytic systems are crucial for managing large volumes of data in businesses and organizations. They are composed of three levels, which are used to manage, access, and use data.
Analytic systems, such as Power BI and Tableau, are used to manage data at the view level and provide users with the tools and resources needed to analyze and visualize data. While Power BI is a top-level tool that addresses all three levels of databases, Tableau is a more advanced tool that is often used by organizations that require advanced data analysis capabilities.

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