Data Mining and Business Strategies


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    100% Online

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  • Self-Paced


  • Time to Complete

    Time to Complete

    4 Weeks
  • Total Tuition

    Total Tuition


Gain an in-depth understanding of data mining and strategic management techniques for improving business decision-making. Through an examination of data mining and machine learning terminology and techniques, you’ll be introduced to data blending and wrangling concepts applicable to formulating a strategic data management plan. The challenge is to select the appropriate method. You’ll learn to use and design data mining-based solutions to solve ‘real-time’ business problems.


You’ll explore the strategic planning concept for using decision support systems or hybrid platforms when wrangling NoSQL and text data. The coursework examines data mining concepts for blending unstructured data sets or working with semi-structured data using the Extract, Load, Transform (ELT) process. You’ll also study automated processes, like Extract Transformation and Load (ETL) or loading data sets as use cases. This course theorizes on data optimization techniques for using machine learning and artificial intelligence for deep learning of the data.


Finally, you’ll conduct statistical data modelling used in predictive and descriptive analysis such as classification trees, segmentation, clustering, and perform basic exploratory data analysis with Excel to create data analytical presentation projects.

You will learn how to…

  • Apply common Data Mining concepts, including NoSQL, Big Data, and data wrangling, to real-world data sets, and develop strategies for selecting and implementing appropriate technologies and techniques.
  • Explore and critically analyze the principles of data mining and machine learning, and evaluate their suitability for different organizational contexts.
  • Analyze and compare a range of advanced data analysis techniques, including clustering, decision trees, and neural networks, and evaluate their effectiveness in supporting data mining and decision making.
  • Develop and implement classification tree models that effectively structure and analyze complex data sets, and evaluate their reliability and validity.
  • Apply advanced data mining techniques, including cluster analysis and association rules, to extract insights and identify patterns in complex data sets, and evaluate their effectiveness in supporting organizational decision making.

And learn the skills connected to careers including…

Business Intelligence Analyst, Data Strategist, Data Architect, Data Scientist, Data Mining Specialist, Data Analyst, Business Systems Analyst, Logistics Analyst, Machine Learning Engineer

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