The term data mining was introduced in the late 80s among the data researchers and gained popularity as and when the use of Computer Science became an established scope. The increase in popularity and use of the term data mining was the outcome of technological advancement, the processing power of computer Science and its data storage capabilities. Thus, all the data related to the commercial enterprise began to be stored in order to support commercial activities. The popularity of data mining continued to grow over years, putting emphasis on the mining of non-standard data generating a lot of data mining jobs.
Future proof your career with MBA in Data Mining - What is Data Mining?
Data mining, in essence, refers to the process of extraction of useful information from raw data sets in order to help companies make better decisions, policies and strategies. Also referred to as knowledge mining, knowledge extraction, data/pattern analysis, data archaeology, data dredging or the more popular Knowledge Discovery in Data or ‘KDD’, data mining involves studying patterns or trends in ‘big data’ which can help businesses formulate strategies, market effectively and improve sales.
Also Read: 15+ Courses for Learning Data Mining
Steps involved in Data Mining
There are primarily three steps involved in process of data mining mainly involves three steps:
Studying the data to uncover themes, trends or patterns
Building models to help explain the data and verify the patterns
Applying the models to make new predictions
Data mining is being used across economic sectors today by companies large and small to make better and prompt decisions. The fast-paced rate at which big data and data warehousing technology has evolved over the past few decades has only accelerated this process of adoption of data mining tools and techniques.
“The major reason that data mining has attracted a great deal of attention in the information industry in recent years is due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge,” says Dr. Rajeev Srivastava, Assistant Professor at the School of Business, UPES, Dehradun. “The information and knowledge gained can be used for applications that range from business management, production control, and market analysis, to engineering design and science exploration,” he adds.
Data Mining Groups
Data mining techniques can be broadly categorised into the following two groups according to their use:
Study of the target datasets
Prediction of the outcomes using machine learning algorithms.
Today data mining is widely used by business intelligence and data analytics teams to help extract information and provide solutions for the organisation or industry.
MBA in Data Mining and Its uses
An MBA in data mining will help you stand on a firm footing in this burgeoning industry. Let us check some popular applications of Data Mining which can be mastered with an MBA in Data Mining degree. Some of the applications are mentioned below:
Operational optimisation
Fraud detection
Loan/credit card approval
Trend analysis
Customer churn
Website designing and promotion.
MBA in Data Mining - Sales and marketing
Companies collect a huge amount of data about their customers. This data could reveal information about their behaviour, tastes, spending habits, visiting times, and other activities which, in turn, could help companies optimise their marketing and sales strategy in such a way as to boost profits while also ensuring customer satisfaction.
MBA in Data Mining - Education
The education industry is another sector where the use of data mining techniques is widespread. Educational institutions today use data mining to collect information about their students, their performance as well as factors which will contribute to success. As more and more courses and programmes are offered online, a variety of metrics and tools are being used to study and evaluate student performance, such as keystroke, student profiles, their time spent in classes, and other students activities.
MBA in Data Mining - Operational optimisation
Data mining techniques have also helped reduce costs on improving operational functions by helping organisations identify costly bottlenecks.
MBA in Data Mining - Fraud detection
It is not just patterns and trends among data sets that can provide companies with useful information on customer behaviour, but even studying data anomalies can help companies detect fraud. This, in fact, is quite a popular use case among banking and financial institutions. Nowadays, SaaS-based companies have started using this technique to spot fake user accounts and remove them from their datasets.
Other course in Data Mining
Apart from pursuing a degree in MBA Data Mining, a learner can pursue other courses or certification programmes in data mining. There are many providers offering the course which will help the learner get a hang of the subject and excel in the industry. Some of the courses are mentioned below .
Also, go through some of the providers offering the data mining courses mentioned in the table below:
On Question asked by student community
Hello aspirant,
Here below I am providing you with the name of some of the best MBA colleges in Hyderabad:
To know about more colleges, you can visit our site through following link:
https://bschool.careers360.com/colleges/list-of-mba-colleges-in-hyderabad
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Hello,
Here are some top MBA colleges in India with fees under Rs. 2 lakh and their exam/cutoff details:
SIMSREE, Mumbai – Fee around Rs. 1.3–1.4 lakh for 2 years. Accepts CAT, CMAT, MAH-CET, MAT, ATMA. Cutoff is very high, usually 99+ percentile in CAT/CMAT.
PUMBA (Dept. of Management Sciences, Savitribai Phule Pune University) – Fee around Rs. 1.2–1.3 lakh. Accepts CAT, CMAT, MAH-CET, ATMA. Cutoff approx. 75+ percentile in CAT, 90–95+ percentile in CMAT, high scores in MAH-CET.
TISS, Mumbai (MA HRM & other management-related programmes) – Fee around Rs. 1.7–1.9 lakh. Accepts CAT for some courses. Qualifying cutoff is around 60–70 percentile, but final selection cutoffs are higher.
These are the main government institutes where the full MBA/PG programme fee is within Rs. 2 lakh. Cutoffs vary slightly each year and by category, but SIMSREE and PUMBA generally need high scores, while TISS has its own process along with CAT shortlisting.
Hope it helps !
Yes, MBA in FinTech is a good option if you are interested in the combination of finance and technology. After this course you can work in roles like FinTech product manager, financial analyst, blockchain/crypto specialist, risk & compliance manager, or business development manager in banks, startups, and financial companies.
For the salary part, freshers usually start with around 5–10 LPA in normal companies and in bigger FinTech firms or banks it can even go up to 10–15 LPA, depending on your skills, college, and location.
If you do Data Science and then an MBA in Finance, you can get many high-paying jobs. Some of the best options are:
1. CFO (Chief Financial Officer) – You manage a company’s finances, budgeting, and reports. Big companies pay 40 lakh to 1 crore per year.
2. Investment Banker – You help clients raise money and do mergers or acquisitions. Salaries start around 10–12 lakh for freshers and can go up to 30 lakh or more with experience.
3. Chief Data Officer – You lead data strategies in companies. Pay can be 80 lakh to 1.3 crore per year.
4. Machine Learning Engineer / AI Scientist – You create AI and ML models. Salary is around 35–42 lakh per year.
5. Product Manager – You manage product strategy and market positioning. Can earn 89 lakh to 1.1 crore per year in big tech companies.
6. Financial Actuary – You analyze financial risks. Pay is around 25–30 lakh per year.
Hello,
If you have made a mistake while entering your education details in KEA PGCET MBA option entry, you cannot edit it directly once it is submitted. You need to contact KEA immediately.
You can:
Call the KEA helpline numbers.
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They will guide you on how to correct the mistake. Do it quickly, as corrections are allowed only within the given time.
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