Difference Between Business Intelligence vs Data Mining
Business Intelligence transforms the data into actionable information. It helps optimize organizations’ strategic and tactical business decisions using the applications, infrastructure and tools, and the best practices that facilitate access to an organization’s operational facts and figures. Data Mining is evaluating the unrecognized patterns in large raw data sets, as per the different perspectives, to categorize the data into useful information resulting in gaining business insights to solve issues beforehand.
Business Intelligence (BI)
In layman’s language, Business Intelligence will analyze the complex raw data of an organization and transform them into useful information as required by the business. By using this useful information, the business will know what is working, what is not, what is the future, and how you can improve your business.
Below are the process involved in Business Intelligence:
- Aggregate the complex raw data of an Organization.
- Analyze the data.
- Present the data in a meaningful visualization.
- Based on these facts, businesses will take intelligent decisions for the organization’s wellness.
There are many tools available in the market for Business Intelligence, and any organization can use this tool to improve their business:
- Microstrategy
- Tableau
- QlikView
- Sisense
- Oracle Enterprise BI Service
- IBM Cognos Intelligence
- icCube
- Accurate Business Intelligence and Reporting Tool (BIRT)
- DOMO
- SAP Business Objects
Data Mining
In layman’s language, as the word explains, it is just mining useful information or knowledge. Data mining helps find useful information or knowledge from an ocean of data.
There is an ocean of data available in an organization. There is no value for the data until you convert that into valuable information. It is required to analyze this data and convert them into valuable information. Therefore, Data Mining will help to extract this valuable information from huge sets of data available.
The other process involved in Data Mining are:
- Cleansing the Data: It will handle corrupt, irrelevant, inaccurate, and incomplete data.
- Integrating the Data: Combine multiple data sources into meaningful information.
- Selection of Data: Data, which are meaningful for the analysis, will be retrieved from the database.
- Transformation of Data: Converts data into a specific form relevant to mining.
- Data Mining: This will extract data patterns that are required.
- Evaluating the Patterns in Data: Will extract patterns representing information or knowledge depending on interesting measures.
- Presentation of information or Knowledge: Will present the mined knowledge to the business using different visualizations.
The valuable information or knowledge revealed from Data Mining can be used for many purposes, such as:
- Management Analysis
- Market Analysis
- Risk Management
- Corporate Analysis
- Customer Management
- Fraud Detection
There are many data mining tools available; some of the best tools in the market are listed below:
- R-Programing
- RapidMiner (YALE)
- WEKA
- Orange
- Knime
- DataMelt
- SPARK
- Hadoop
Head-to-Head Comparison Between Business Intelligence and Data Mining (Infographics)
Below are the top 7 comparisons between Business Intelligence and Data Mining:
Key Differences Between Business Intelligence and Data Mining
Below is the list of points that describe the key difference between Business Intelligence and Data Mining:
- Business Intelligence is data-driven, whereas Data Mining analyzes patterns in data.
- Business Intelligence helps in Decision-making, but Data Mining will solve a particular issue and contribute to decision-making.
- The volume of data involved in Business Intelligence is huge, whereas in data mining volume of data is small.
- Business Intelligence involves business processes and data analysis methods, whereas Data Mining uses computational intelligence to discover the solution for a business factor.
- Business Intelligence includes data generation, aggregation, analysis, and visualization. However, Data Mining includes cleansing, integrating, transforming, and evaluating patterns in data.
- Business Intelligence Informs and facilitates Business Management and Executives, whereas data mining provides KPIs to be presented in BI results.
- BI provides Dashboards, Reports, and Documents in a consolidated view of many KPIs in graphics and charts, while Data Mining provides reports to contribute to decision-making.
- Business Intelligence is part of decision-making in an organization, whereas Data Mining is part of BI and helps to create the KPIs for decision-making.
Business Intelligence and Data Mining Comparison Table
The following is the comparison table between Business Intelligence and Data Mining.
| Basis For Comparison | Business Intelligence | Data Mining |
| Meaning | Converting raw data into useful information for the business. | Designed to explore data and find the solution for an issue in business. |
| Use for Business | Data-driven helps in decision-making for a business. | Finds answers to an issue or a problem in business. |
| Data Volume | Large Datasets are processed on dimensional/relational databases. | Small datasets are processed on a small portion of data. |
| Quality of Solutions | Volumetric in nature and presents accurate results using visualizations. | It uses algorithms to identify accurate patterns for an issue and identify the blind spots. |
| Results Presentation | Dashboards and Reports represented by graphs and charts with KPIs. | Identifies the solution for an issue to be represented as one of the KPIs in Dashboards or reports. |
| Analysis | No intelligence is involved depending on small-scale past data; management has to decide based on the information. | Focused on a particular issue in business on small-scale data using algorithms to find the solution. |
| Focus | Shows price value, profit, total cost, etc., as KPIs. | Identifies solution for an issue creating new KPIs for BI. |
Conclusion
Although in this blog Business Intelligence vs Data Mining, I have specified only a few characteristics difference, the result shows an important and substantial difference between Business Intelligence vs Data Mining.
There is an increase in the use of the internet, mobile applications, different software, and cloud services in business processes and IT; this has a significant increase in the demand for Data Mining and Business Intelligence for Business. Hence, it is important to understand the key difference between the process of Business Intelligence and Data Mining. The most important points are:
- The organization that uses the Business Intelligence solution has a high success rate and is more mature to handle all data mining projects. The knowledge discovered by the data mining can be tested quickly on the BI solutions, and the results are accurate.
- BI helps to decode complex raw data by using data mining techniques and, understandably, presenting the complex data using different visualizations, using graphs, and charts. This will help the higher management make the necessary decision for the company’s wellness.
- The result of Data Mining and BI will generate intelligence for business. However, it is very important to assess whether it is necessary to meet the desires of a company.
- Data never stops coming, the volume and complexity grow daily, and the data is never the same. It always changes. This shows the growing demand for BI solutions and Data Mining for an organization to be on the market.
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