BI (Business Intelligence) definition & meaning
BI stands for “Business Intelligence” is a process that includes converting raw historical and current data into actionable insights. It uses various strategies, services, and technologies allowing organizations to make more data-driven decisions. To be able to provide this information, it combines business analytics, data mining, data visualization, data tools, performance benchmarking, descriptive analytics, and infrastructure enabling an organization to make the most accurate strategic and tactical decisions. In basic terms, business intelligence aims to evaluate and transform complex data into meaningful, actionable information.
What are business intelligence techniques?
To be able to get a piece of meaningful information, business intelligence technologies benefit from advanced statistics and predictive analytics. Business intelligence covers all of these processes and methods that are used for collecting, storing, and analyzing data. The most popular of these processes are:
- Data mining: It aims to uncover trends in large datasets by using databases, statistics, and machine learning.
- Performance benchmarking: It compares the performance metrics to historical data to evaluate and track performance.
- Descriptive analytics: It includes analyzing the historical data to better understand changes that have happened in an organization.
- Data preparation: It aims to prepare the data for analysis by compiling and structuring it.
- Querying: It is asking questions to the dataset in order to get specific data
- Reporting: It includes sharing the analysis with the decision-makers.
- Data visualization: Converts the analysis into easy-to-understand visual representations, such as charts or graphs.
- Visual analysis: It uses visual storytelling while exploring the data during the analysis.
How does business intelligence work?
The process of transforming raw data into actionable insights comprises four steps. The first one is to collect and transform data from multiple sources by using the extract, transform, and load method. To allow applications to easily analyze and query the data, it is transformed and remodeled and then stored in a central location. The second step includes data mining that uses automation to find out patterns and outliers.
Most business intelligence tools come with various data modeling and analytics types. Once the data is explored, trends are predicted and recommendations are made, the findings are reported by using various data visualization techniques, which is the third step of the process. Reporting phase includes interactive data dashboards, charts, graphs, and maps to help the decision-makers. And the final step is to take action according to the information provided. It can be a real-time adjustment or long-term strategic decisions.
Why is business intelligence important?
There are tons of benefits of business intelligence for organizations. The most important benefit of business intelligence, it transforms the raw data into actionable insights, allowing organizations to make data-driven decisions. Business intelligence is very important for organizations because it provides a comprehensive view of the organization, which is vital for most companies.
Business intelligence also enables organizations to compare themselves with competitors to better understand their position in the market. Organizations can also increase the efficiency of operations by identifying new ways to increase profit, analyze customer behavior, track their performance, spot market trends, and make predictions. Business intelligence mainly focuses on six areas: customer experience, sales and marketing, operations, finance, inventory control, and security and compliance.
Business intelligence software and platforms
There are various tools that the business intelligence process benefits from. Some of these tools are:
- Spreadsheets: Spreadsheets are widely used in business intelligence, such as Microsoft Excel and Google Docs.
- Dashboard: Interactive dashboard allows users to easily access the data needed.
- Data visualization tools: Data visualization software transforms the information into easy-to-understand visual representations, such as charts or graphs.
- Data mining tools: Data mining tools uses methods like artificial intelligence, machine learning, and statistics to find meaningful data from large datasets.
- Online analytical processing (OLAP): OLAPs are online tools enabling users to analyze datasets from different business perspectives.
There are also various platforms that handle the process for their customers. Some of these platforms can integrate with cloud-based platforms. Most business intelligence platforms come with essential tools, such as customizable dashboards, data visualizations, report scheduling, etc. but it is crucial for organizations to choose the ideal vendor to suit their needs. Some of the most popular business intelligence platforms in the market are Microsoft Power BI, Google Marketing Platform, Qlik, Oracle Analytics Cloud, Tableau, and Splunk.
What is the difference between business intelligence and business analytics?
Although the line between business intelligence and business analytics, there are some distinctive differences. The most significant difference between business intelligence and business analytics is that business analytics is predictive and prescriptive, which means they are more focused on what is going to happen and what should decision-makers be doing to achieve better outcomes. On the other hand, business intelligence focuses on the current state of the organization by using historical and current data. However, BI tools are getting better and providing more accurate reports and business intelligence closing the gap every day.
The difference between traditional BI and modern BI
Just like anything related to the digital era, business intelligence is always evolving and improving itself with the use of new methods. Modern business intelligence solutions are trying to find out new methods that can enable organizations to leverage all of their available data. It also focuses on helping users to access and share real-time data about the organization.
One of the differences between traditional BI and modern BI is the ease of use. Modern business intelligence services are simplifying how professionals can access the reports. Traditional business intelligence tools, most of them were on-premise solutions, were not capable enough to handle the large datasets and lack the ability to integrate with multiple data sources. With multi-cloud support, modern BI solutions can handle large datasets easily and can also be scaled to meet the customers’ needs. Unlike traditional BI, modern BI also benefits from artificial learning and machine learning methods to gather the most insightful information out of data as possible. Traditional BI solutions that use pre-set or manually controlled tools were much slower than modern BI.
Who is a Business Intelligence Analyst?
A business intelligence analyst is a professional that transforms data into insights by using data analytics, data visualization, and data modeling solutions. Their role requires identifying trends to help decision-makers. It requires skills like programming, data modeling, statistics, analytical thinking, and problem-solving. The BI analyst role became very popular in recent years and most companies are looking for professionals who have a bachelor’s degree in computer science, business, mathematics, economics, statistics, management, accounting, or in a related field for this role.
Business intelligence analysts are responsible for reviewing and validating the data, overseeing the deployment of the data, developing policies and procedures to collect and analyze the data, working with IT to software and hardware upgrades, monitoring analytics and metrics, implementing new analysis methods, and performing data profiling. Even the organizations that rely on self-service BI solutions prefer to employ business intelligence analysts for managing and maintaining the tools their vendor provides.