What Do Business Intelligence Systems Analyze: Key Insights

Learn what do business intelligence systems analyze, from predictive analytics to data storage, driving informed decisions in ecommerce and enterprise sectors.

August 14, 2023
Predictive analytics

What do business intelligence systems analyze? In today's data-driven world, organizations are increasingly relying on advanced analytics and modern BI tools to make informed decisions. BI systems offer a holistic view of an organization's functioning by processing data from multiple sources and converting it into useful information.

In this blog post, we will explore what do business intelligence systems analyze, and the different types of data analysis performed by these powerful software solutions, including predictive, descriptive, and prescriptive analytics. We'll also discuss the importance of interactive dashboards in providing real-time insights through visualizations tailored to each user's needs.

Furthermore, we'll delve into how integrating data and business analytics can lead to more comprehensive insights using speed-to-insight features like Tableau's Explain Data. Additionally, we will emphasize the role of dedicated analysts within an organization for creating standardized reports across departments.

Last but not least, you'll learn about empowering employees with self-service BI tools that enable them to derive their own insights while fostering a culture of data literacy. Finally, we'll touch upon modern storage solutions such as Hadoop that support the ever-evolving requirements of business intelligence platforms in handling massive amounts of raw data efficiently.

Types of Business Intelligence Analysis Process and What's Analyzed?

Predictive analytics

To know what do business intelligence systems analyze, you must first know the types of BI analysis. There are three major types of BI analysis that help organizations make informed decisions. Descriptive analytics summarizes raw data into comprehensible formats, while predictive analytics forecasts future events based on past patterns and prescriptive analytics suggests steps to accomplish objectives.

Predictive Analytics: Forecasting Future Trends Using Historical Data

Predictive analytics uses advanced algorithms and machine learning techniques to analyze past data in order to predict future outcomes. This analyzing data helps businesses anticipate customer needs, optimize marketing strategies, and improve operational efficiency.

Descriptive Analytics: Summarizing Raw Data for Easy Understanding

To further understand what do business intelligence systems analyze, you need to know about descriptive analysis. Descriptive analytics, the most common form of business intelligence analysis, focuses on summarizing large volumes of raw data into meaningful insights through visualizations such as charts and graphs. This enables decision-makers to understand trends and identify areas requiring attention.

Prescriptive Analytics: Recommending Actions to Achieve Business Goals

Prescriptive analytics, a more advanced form of BI analysis, combines the findings from predictive and descriptive analyses with optimization models to recommend specific actions that will lead to desired outcomes. This empowers businesses to proactively address challenges while maximizing opportunities.

The Power of Dashboards in Business Intelligence Systems

In our what do business intelligence systems analyze blog post, next is the power of dashboards. Dashboards are arguably the most useful tool in business intelligence systems as they offer faster analysis with intuitive visualizations. Dashboards can offer users instantaneous understanding of customer trends, projections for profits and more, thus allowing them to make wiser decisions.

Real-time Insights through Interactive Visualizations

Modern business intelligence software incorporates interactive dashboards that allow business users to examine data at a glance. These visual representations help them understand trends and key performance indicators (KPIs) without having to dig deep into raw data or generate reports manually.

Customizable Dashboard Elements for Personalized Reporting

Tableau, one of the leading self-service BI tools, offers customizable dashboard elements that cater to individual needs and preferences. Users can create personalized views of their data by selecting relevant metrics, filters, and visualization types. This flexibility empowers employees across different departments to analyze their own datasets efficiently while promoting a data-driven organizational culture.

Integrating Data and Business Analytics in BI Processes

Predictive analytics

The use of both data analytics and business analytics is integral to effective business intelligence (BI) processes. By combining these analytical approaches, organizations can gain comprehensive insights into their operations and make informed business decisions. One way modern BI tools facilitate this integration is through self-service capabilities that prioritize speed-to-insight features.

Combining Analytical Approaches for Comprehensive Insights

  • Data Analytics: Focuses on analyzing raw data to derive insights, trends, and patterns.
  • Business Analytics: Applies statistical methods to understand the impact of various factors on business metrics and performance indicators.

Speed-to-Insight Features like Tableau's Explain Data

Tableau's Explain Data feature, for example, helps businesses identify possible explanations for outliers or trends in their datasets by automatically generating relevant visualizations. This enables users to quickly examine data without needing extensive technical expertise, ultimately leading to more efficient decision-making processes within an organization.

Importance of Dedicated Business Intelligence Analysts

A company serious about implementing a robust business intelligence system will need dedicated business intelligence analysts who set up standardized reports generated by managers across various departments to know what do business intelligence systems analyze. This ensures consistent results are achieved over time due to continuous monitoring activities performed on a regular basis, making sure nothing falls through the cracks unnoticed and causing unnecessary delays later down the line when trying to resolve issues arising unexpectedly during normal operations procedures followed diligently at all times without exception whatsoever.

The Role of a Dedicated Analyst Team within an Organization

Analysts dedicated to business intelligence are essential for ensuring data accuracy, relevance, and availability for decision-makers while also working with IT and data science teams to improve the underlying infrastructure and employ advanced analytics. They also collaborate with other teams such as IT and data science to optimize data infrastructure and implement advanced analytics techniques.

Creating Standardized Reports across Different Departments

To further understand what do business intelligence systems analyze, you must create reports that include:

  • Data Reporting: Analysts create comprehensive reports that present KPIs clearly and concisely for each department.
  • Data Visualization: Utilizing modern BI software like Tableau or Power BI enables analysts to design visually appealing dashboards that make complex information easy to understand.
  • Cross-Functional Collaboration: Working closely with multiple departments helps ensure consistency in metrics definition, measurement methodologies, and report generation processes throughout the organization.

Becoming a Data-driven Organization with Self-service BI Tools

BI tools empower employees across different departments and levels of expertise to analyze their own data, driving an organization towards being data-driven. However, for these tools to be effective, organizations must invest in employee education and support the adoption of BI systems within their workforce.

Empowering Employees through Self-service Analytics

Modern business intelligence software enables users to easily access and examine data without relying on dedicated data scientists. This not only increases efficiency but also encourages collaboration among teams as they work together to derive insights from raw data.

Investing in Education and Support for Successful Adoption

  • Data literacy: Providing training programs focused on building essential skills such as understanding key performance indicators (KPIs), using advanced analytics techniques, and interpreting results accurately is crucial for successful implementation.
  • User-friendly interfaces: Selecting self-service BI tools that offer intuitive user interfaces can help reduce the learning curve while increasing overall adoption rates.
  • Ongoing support: Offering continuous assistance through resources like tutorials, webinars, or internal forums ensures employees have access to necessary guidance when needed.

By utilizing BI systems, organizations can gain a comprehensive view of their business operations and make informed business decisions. BI tools enable data analysts to examine data from data warehouses and online analytical processing (OLAP) cubes, streamlining the analysis process. With the help of artificial intelligence and data science, BI capabilities have expanded to include data visualization and generating reports that help business users answer business questions and understand trends.

Overall, business intelligence tools provide business insights that are essential for making informed decisions. By investing in employee education and support, organizations can ensure the successful adoption of BI systems and derive maximum value from their data.

Modern Data Storage Solutions for BI Platforms

In addition to traditional data warehouses that have been the go-to source historically, newer solutions like Hadoop are capable of extracting raw information directly. This allows businesses greater flexibility in how they store and access essential datasets required by various teams throughout each stage involved during any given project lifecycle period.

The Evolution from Traditional Data Warehouses to Modern Solutions

  • Data Warehouses: Provide a centralized repository for structured data storage and analysis.
  • Data Lakes: Store large volumes of raw, unstructured data which can be accessed by multiple users simultaneously.
  • Hadoop: Offers distributed storage and processing capabilities ideal for handling big data workloads.

Harnessing Technologies like Hadoop for Flexible Storage Options

By leveraging modern business intelligence tools such as Hadoop, organizations can efficiently process vast amounts of raw data while reducing infrastructure costs. Additionally, these advanced systems offer improved scalability and performance compared to traditional methods. As a result, companies can derive insights more quickly from their ever-growing datasets - ultimately driving better decision-making across all aspects of their operations.

How do BI Systems Analyze Data?

Business intelligence (BI) systems analyze data by collecting, processing, and transforming raw data from various sources into meaningful insights. They use techniques like predictive analytics, descriptive analytics, and prescriptive analytics to identify patterns and trends. BI tools often provide interactive visualizations through dashboards for easy interpretation of the analyzed data.

What Does a Business Intelligence Analysis Do?

A business intelligence analysis helps organizations make informed decisions by turning raw data into actionable insights. It involves using BI tools to process large volumes of structured and unstructured data from multiple sources, uncovering hidden patterns or trends that can drive strategic decision-making in areas such as sales performance, customer behavior, market trends, and operational efficiency.

What is the Main Function of BI Systems?

The main function of business intelligence systems is to enable organizations to make better-informed decisions based on accurate and timely insights derived from their data. This includes gathering relevant information from multiple sources; analyzing it using advanced algorithms; presenting results through intuitive visualizations; identifying opportunities for growth or improvement; predicting future outcomes; recommending actions aligned with organizational goals.

What are the Four Concepts of Business Intelligence?

The four key concepts of Business Intelligence include:

  • Data Warehousing: Centralized storage for consistent reporting
  • Data Mining: Discovering hidden patterns within datasets
  • Data Visualization: Representing complex information visually
  • Data Analysis: Interpreting findings to inform decision-making


So, what do business intelligence systems analyze? BI systems assess a plethora of data to furnish organizations with knowledge for making informed decisions. From predictive analytics to customizable dashboards, these tools offer a comprehensive view of business operations and trends.

To fully leverage the power of business intelligence, it's important for organizations to invest in dedicated analysts and modern storage solutions. Self-service BI tools can also empower employees across departments with access to data-driven insights.

If you're looking for a powerful business intelligence solution, consider Zenlytic. Our platform offers robust capabilities for analyzing data and generating reports, as well as education and support for successful adoption.

  • Visit our website to learn more about how we can help your organization harness the power of business intelligence!

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