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Data Mining for Business Analytics in PGCM
- 1. MIT School of Distance Education Data Mining for Business Analytics
- 2. What is Data Mining in Business Analytics ? ● Data mining in business analytics refers to the process of analyzing large datasets to discover patterns, correlations, trends, and insights that can help businesses make informed decisions. ● This process involves using various techniques from statistics, machine learning, and database systems to extract useful information from raw data. ● Data mining involves examining and analyzing extensive sets of raw data to uncover patterns and derive valuable insights. ● Businesses employ data mining tools to gain a deeper understanding of their customers, enabling them to craft more efficient marketing strategies, boost sales, and reduce expenses.
- 3. Data mining works through a series of steps designed to transform raw data into valuable insights. Here is a detailed explanation of the process: 1. Data Collection: Gathering data from various sources such as databases, sensors, web logs, social media, and transaction records. 2. Data Cleaning: Ensuring data quality by removing noise, handling missing values, and correcting inconsistencies. 3. Data Integration: Combining data from multiple sources to form a unified dataset. This step often involves data warehousing and ensuring data from different sources is compatible. 4. Data Transformation: Converting data into a suitable format for analysis, which may include normalization, aggregation, and feature extraction. 5. Data Reduction: Reducing the volume of data while retaining its essential information. This can be done through dimensionality reduction, feature selection, and sampling techniques. 6. Data Mining: Applying algorithms and techniques to the prepared data to uncover patterns. Some common techniques include: Classification, Clustering, Association Rule Learning, Regression and Anomaly Detection. How Data Mining works ?
- 4. Data mining techniques are diverse and are used to extract patterns, relationships, and insights from large datasets. Here are some data mining techniques: 1. Classification: This method is employed to sort data into established groups or categories. It involves training a model on labeled data (data with known outcomes) and then using that model to classify new, unlabeled data. 2. Clustering: Clustering is used to group similar data points together based on their characteristics or attributes. Unlike classification, clustering does not require predefined classes. 3. Association Rule Learning: This technique identifies relationships or associations between variables in large datasets. It is commonly used in market basket analysis to discover patterns of co- occurrence among items in transactions. 4. Regression Analysis: Regression is used to predict numerical values based on input variables. It establishes a relationship between dependent and independent variables in a dataset. 5. Anomaly Detection: Also known as outlier detection, this technique identifies data points that deviate significantly from the norm or expected behavior. Data Mining Techniques :
- 5. Data Mining Process : The data mining process involves several sequential steps aimed at extracting useful patterns, relationships, and insights from large datasets. Here's a structured overview of the typical data mining process: 1. Business Understanding 2. Data Understanding 3. Data Preparation 4. Modeling 5. Evaluation 6. Deployment 7. Iteration and Improvement
- 6. It is vital for business analytics professionals to embrace Data Mining methodologies, as these are key to enhancing organizational efficiency by streamlining and optimizing workflows and processes. The PGCM in Business Analytics course at MITSDE is designed to teach you the most current tools and techniques used in the field. With MITSDE’s Post Graduate Certificate Program in Business Analytics course, Through real-world case studies, the course prepares you practically so that you're ready for the job market and receive clear instructions on how to use analytical methods effectively, making data analysis understandable and giving you practical skills to apply directly in your job. Data Mining in Business Analytics
- 7. Why MITSDE? • To quantify business values by using Statistical Tools & Techniques • Data mining techniques for mining and analyzing of raw data to discover interesting patterns, extract useful knowledge, and support decision-making. • Gain detailed insight via various data interpretation & data visualization techniques. • Predictive modelling technique which help the business to predict the future market trends using historical data. • Application of analytics in various domains such as HR, Finance, Marketing & Supply chain.
- 8. Potential Careers Opportunities Successful completion of the program will ready you to pursue multiple roles in Business Analytics, across various domains. Few exceptional job prospects are: 1. Big Data Analyst 2. Financial Analyst 3. Marketing Analyst 4. Business Intelligence and Analytics Consultant 5. Research analyst 6. Data Scientist 7. Data Visualization Analyst
- 9. MIT School of Distance Education is one of the largest distance learning center in India. We offer various Post Graduate Diploma and Certificate programs & Online MBA Course across various industry sectors that include Operations Management, Project, Information Technology, Banking and Finance, Digital Marketing, Business Analytics and many more. MITSDE has, an online assessment system, flexi-learning approach and provides state-of the-art Learning Management System (LMS) which is in line with its mission 'flexible learning opportunities anywhere, anytime, and to provide ultimate convenience, ease, and flexibility to our students. About US
- 10. o Regularly updated syllabus o Industry-relevant course offerings o Courses taught by Industry Experts o Affordable courses o No cost EMI options o Self-paced learning o Live webinars and doubt solving sessions o Quick and highly-responsive student support o Dedicated student support team Advantage of learning with MITSDE
- 11. Placement Record at MITSDE MITSDE has a dedicated Placement Cell providing 100% placement, CV building workshops and Career Counseling. Our Student Placement :
- 12. Placement Record at MITSDE
- 13. Contact Us Address: MIT Alandi Campus, Pune Moshi-Alandi Road, Alandi-412105,Pune Maharashtra (India) Phone: 9112-207-207 / 9028-258-800 Email ID: [email protected] Website: www.mitsde.com
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