Difference between Business Intelligence and Data Mining
Business intelligence (BI) refers to a technology-driven process that transforms the data into actionable information. Organizations have a huge flow of data coming from their customer end. All information about the customer’s likes, previous purchases, search engine queries, social media platforms (Facebook, Instagram, Snapchat, etc.) is a clue into what a customer will buy next. The term data mining itself explains its meaning, and it is the mining of important information, patterns, and trends. Data mining helps in extracting significant data from huge data sets. There is a huge data available in any company. There is no use of raw data until you convert that into useful information. Before starting the differentiation between business intelligence and data mining, let’s understand the two terms separately. Read the given article to know the basic difference between business intelligence and data mining.
What is Business Intelligence?
Business Intelligence is one of the most powerful tools many organizations use to know their customer base and market better. It describes the business methodology in which the raw data is transformed into useful information which helps in decision making.
Benefits of Business Intelligence
Business intelligence has broad applications, and if talking about the benefits of business intelligence in the retail sector, nowadays business intelligence tools enable organizations to take benefit of data not only to assume current sales but also to estimate future potential, patterns, trends and know the demand of the customer on a deeper level.
Business Intelligence techniques
These are the given business intelligence techniques
Data analysis visualization:
Data analysis visualization is all about how you visualize your data. It presents data on dashboards and utilizes customized metrics related to the business to make better decisions based on facts.
Reporting:
Business intelligence tools are used for reporting information gathering from all the sources and process it to enable better reporting and financial decision making with a rational mind.
Predictive Analytics:
Predictive analytics is all about how do you know a strategy will work? The fact is you don’t know, and if you know, not 100 percent. However, with business intelligence, you can create an evidence-based decision to drive business further. Business intelligence enables you to make a reasonable prediction of the latest trends and customer behaviors that impact the organization’s overall development.
What is Data Mining?
Data mining refers to a process of finding interesting trends, patterns, and knowledge from huge data sets. The data source may include a data warehouse, web, database, raw data, and another information repository streamed into the system dynamically.
Why does a business need data extraction?
With the advent of new technologies like Big Data, data mining has become more come. Big data refers to a huge set of data that can be analyzed with the help of computers to reveals certain trends, patterns, and useful information that humans can understand.
Thus, simple statistics with manual interference would not work with these data sets, so the data mining techniques fulfill this requirement. It changes simple data statistics to complex data mining algorithms.
The data mining techniques extract useful information from raw data such as videos, photos, files to develop reports which are useful for decision-making purposes in any organization.
Data Mining Process
The following steps are involved in the process of data mining:
- Business Understandings
- Data Understandings
- Data Preparation
- Modeling
- Evaluation
- Deployment
Data Mining Tools
In this digital era, a large amount of data is generated within seconds. To manage this data, we should have some knowledge of various tools and techniques. Data Mining tools refer to a set of methodologies used to analyze the data and other relationships between the data sets.
These are some data mining tools that are helpful for us to analyze the data.
- Orange
- Rapid Miner
- Weka
- Sisense
- SSDT
Difference between Business Intelligence and Data Mining
| Business Intelligence | Data Mining |
|---|---|
| Business intelligence (BI) refers to a technology-driven process that transforms the data into actionable information. Organizations have a huge flow of data coming from their customer end. | The term data mining itself explains its meaning, and it is the mining of important information, patterns, and trends. |
| The data-driven decisions help in decision-making purposes in the organization. | It finds the answer to a problem in the business. |
| It has a large dataset processed on relational databases. | It has small data sets processed on a small portion of data. |
| It represents results on dashboards and reports by charts and graphs with KPI’s | It identifies the solution for a problem to be represented as one of the KPI’s in dashboards or reports. |
| It depends on a small scale of past data, and there is no intelligence involved; business management has to decide based on the information. | It focused on a specific problem in business management on small-scale data using various algorithms to determine the solution. |
| The quality of the solutions is volumetric and presents the accurate solution using data visualizations. | It uses algorithms to identify accurate patterns for a problem and identifies the blind spots. |
| It shows price value, total cost, profit, etc. | It identifies a solution for a problem creating new KPI’s for business intelligence. |