Data Mining Applications and Use Cases
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We studied in our last session, Data Mining Process. Here, we will explore the Data Mining Applications. Also, we will cover Data Mining Use Cases of each and every field.
So, let’s start Data Mining Applications.
2. Data Mining Applications & Use Cases
Following are the applications of data mining in various sectors:
a. Data Mining in Finance
- We have to Increase customer loyalty by collecting and analyzing customer behavior data. Also, one needs to help banks that predict customer behavior and launch relevant services and products.
- Helps in Discovering hidden correlations between various financial indicators that need to detect suspicious activities with a high potential risk.
- Generally, it identifies fraudulent or non-fraudulent actions. As it done by collecting historical data. And then turning it into valid and useful information.
b. Data Mining in Healthcare
- Basically, it provides government, regulatory and competitor information that can fuel competitive advantage. Although, it supports the R&D process. And then go-to-market strategy with rapid access to information at every phase.
- Generally, it discovers the relationships between diseases and the effectiveness of treatments. That is to identify new drugs or to ensure that patients receive appropriate, timely care.
- Also, it supports healthcare insurers in detecting fraud and abuse.
c. Data Mining for Intelligence
- Generally, it reveals hidden data related to money laundering, narcotics trafficking, etc.
- Also, helps in Improving intrusion detection with a high focus on anomaly detection. And identify suspicious activity from a day one.
- Basically, convert text-based crime reports into word processing files. That can be used to support the crime-matching process.
d. Data Mining in Telecommunication
- In this, data mining gains a competitive advantage and reduce customer churn by understanding demographic characteristics and predicting customer behavior.
- Increases customer loyalty and improve profitability by providing customized services.
- As it supports customer strategy by developing appropriate marketing campaigns and pricing strategies.
e. Data Mining for Energy
- As data mining capture weak signals of potentially threatening events. Also, identify previously unidentified patterns, connections.
- Structure identification of important information, and distill it to boost technical problem-solving. Also, empower more informed decision-making and enable immediate notification of prospective technical breakthroughs.
- Improve core processes in upstream, midstream and downstream. As with analysis and intelligence capabilities using a variety of sources.
f. Data Mining in Marketing and Sales
- Basically, it enables businesses to understand the hidden patterns inside historical purchasing transaction data. Thus helping in planning and launching new marketing campaigns.
- Generally, the following illustrates several data mining applications in sale and marketing.
- We use it for market basket analysis. That is to provide information on what product combinations have to purchased together. This information helps businesses promote their most profitable products and maximize the profit. In addition, it encourages customers to purchase related products.
- Retail companies use data mining to identify customer’s behavior buying patterns.
g. Data Mining in E-commerce
h. Data Mining in Biological Data Analysis
- Semantic integration of heterogeneous, distributed genomic and proteomic databases.
- Alignment, indexing, similarity search and comparative analysis multiple nucleotide sequences.
- Discovery of structural patterns and analysis of genetic networks and protein pathways.
- Association and path analysis.
- Visualization tools in genetic data analysis.
i. Data Mining for Crime Agencies
j. Data Mining in Retail
- Large retailers like Walmart utilize information on store footfall, advertising campaign even weather forecast to predict sales and stock up accordingly.
- Credit card companies mine transaction records for fraudulent use of their cards. That was based on purchase patterns of consumers. As they can deny access if your purchase patterns change drastically!
- In Genomics, Research gathers Speed using Computational Methods
- Generally, the Human Genome Project mounts up piles of data. Although, getting the data to work for humankind need to develop a new drug and weed out diseases. That will require pattern recognition in the data which is handled in bioinformatics.
- As scientists use microarray data to look at the gene expressions. And also sophisticated data analysis techniques. That is employed to account for the background noise and normalization of data.
k. Data Mining for Information Retrieval
l. Data Mining in Communication Systems
m. Data Mining in Education
n. Data Mining in Manufacturing Engineering
o. Other Scientific Applications
- Data Warehouses and data preprocessing.
- Graph-based mining.
- Visualization and domain-specific knowledge.
So, this was all about Data Mining Applications & Use Cases. Hope you like our explanation.