Definition of Business Intelligence and Illustrative Case Studies – One element or component that a business must implement in order to achieve maximum profitability is business intelligence, or BI. Without business intelligence, it will be challenging for organizations to identify or comprehend where their biggest profit margins lie.
Here is a definition, list of advantages, and some instances of business intelligence!
Definition of Business Intelligence and Illustrative Case Studies
As stated by bbs.binus.ac.id, A collection of analytical tools known as business information, or business intelligence, are helpful for gathering, evaluating, storing, and retrieving large amounts of data in the context of business operations. These tools help in decision-making and action-taking with the goal of enhancing business or business performance.
Business intelligence: what is it?
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Business Intelligence can make it easier for us to make the right decisions. Generally, Business Intelligence explains a concept and method about how we can improve the quality of decision making in a business based on data-based systems. The data is then converted into information which is analyzed and arranged first according to the context.
Benefits of Business Intelligence for Companies
There are 4 types of benefits of Business Intelligence according to Turban, Rainer and Potter quoted from the bbs.binus.ac.id site, namely:
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Increase the value of organizational data and information.
Makes it easier to measure organizational performance.
Increasing the investment value of existing information technology.
Increase cost efficiency.
Skills that a Business Intelligence Person Must Have
To become a reliable Business Intelligence, certain skills or abilities are needed to be able to make the right business decisions and achieve business goals. The following are seven skills that must be possessed as quoted from geeksforgeeks.com:
1. Data preparation
To gain any insight from data, it needs to first be collected, cleaned, and organized in a uniform way. There are many data preparation tools capable of collecting data from multiple sources and prepared with the same dimensions and measurements.
To become familiar with data preparation, you need to master a number of tools such as Tableau Prep and Improvado. Alteryx.
2. Data Mining
Data mining is the process of finding patterns in data that were previously invisible. This capability converts raw data into useful information used for decision making.
Knowledge of data mining requires an understanding of various technologies such as machine learning, databases, statistical analysis, and computer science algorithms. Some tools that help with data mining are Rapid Miner, Oracle data mining, and Konstanz Information Miner.
3. Statistical Analysis
You should have knowledge of various statistical components such as mean, median, range, variance, and max. This can be used to get a more detailed view of the data.
Advanced statistical topics such as combinatorics, set theory, probability, discrete, continuous, and bivariate distributions need to be understood as well. There are many analytical tools that help businesses to understand their metrics better and thus create appropriate BI strategies, for example SAS, Hadoop, Spark, Hive, and Pig.
4. Descriptive Analysis
Descriptive analysis involves examining the data to understand if there are missing values, outliers, abnormal or skewed distributions, and more. In essence, descriptive analysis is part of understanding and getting to know the data before presenting the data to decision makers in a clean form.
5. Data Visualization
As a BI analyst, an important part of your job is not only to uncover patterns in the data, but also to visualize the data in such a way that those patterns are clearly visible. You should have knowledge of various charts that can be used to visualize data such as Area Charts, Bar Charts, Heat Maps, TreeMaps, Scatter Plots, and Gantt Charts.
All these charts allow decision makers to understand the data more deeply by visualizing it and understanding slowly changing trends or places where sudden critical changes occur.
6. Business Knowledge
You must also have good business knowledge. It is important to know the business model of the company where you work and understand how to utilize data to get maximum benefits for the business based on key performance indicators.
You must understand the company’s short and long-term business goals so that you can help chart its future path with the help of data.
7. Data Reporting
Data Reporting or Communication Skills are soft skills that are very important for BI analyst jobs. You must have good speaking skills to report insights gained from data to higher-ups in the business, such as stakeholders and board members in order to make necessary decisions for the business.
Additionally, it is important to remember that most decision makers may come from a technical background so it is important to use lay language in explaining technical concepts so that they are easy to understand.
Example of Business Intelligence
An example of BI can be seen from a global car business that wanted to analyze their car sales in each country and understand which models performed better. They can use Business Intelligence to collect data about all the car models they own such as worldwide sales, level of popularity among customers, and feedback for improvements.
By analyzing this data, businesses can understand which models are more popular in each country and how to make improvements to increase their profits.
That is the concept of Business Intelligence (BI) that applies in the business world, namely a set of business information analysis tools that direct companies to make the right decisions and actions. To become a reliable Business Intelligence analyst, you need a number of skills such as data mining, data visualization, business knowledge and proper communication.
