Business Analytics Training

With every company decision being data-driven, analytics is a de-facto talent expected of each manager, as you will be the one making decisions. This course will teach you how to turn a business problem into an analytics problem, then figure out how to fix it. Therefore, if you want to lead teams working to solve problems for the digital age, launch your own company, or merely seek advice from others while making business decisions, this programme is for you.

This course's main goals include laying a strong foundation in analytics fundamentals, developing data manipulation and analysis skills, applying analytical methods to real-world issues, mastering data visualisation and communication, comprehending ethical and legal issues, industry relevance, teamwork and collaboration, and encouraging a mindset of continuous learning.

Course Duration: 3 Months

Course Objectives

  • Foster a mindset of continuous learning and adaptability in the field of business analytics.
  • Actively explore new technologies, stay updated with emerging trends in analytics, and demonstrate a commitment to continuous learning through ongoing professional development.
  • Engage in self-study, attend webinars or workshops, and participate in networking opportunities to expand knowledge and skills beyond the course curriculum.
  • Develop the ability to adapt to evolving analytical tools, techniques, and industry demands.
    Set personal learning goals, track progress, and regularly evaluate and update skills and knowledge to stay current in the field.

Course Topics

  • Learning Python for Business.
  • Learning SQL for Business.
  • Learning Business analytics platform.
  • Learnig how to create various tables for business use cases.
  • Learning pre-processing of data and loading the data in tables.
  • Learning Basic of Machine Learning.
  • Learning Machine Learning Visualization.
  • Learning Basic of Text Analytics.
  • Learning some of Visualization tools - Power BI or Tableau or others.

Course Methodology

  • Big data maturity model : TDWI or CSC or Others  
  • CRISP-DM : The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model that serves as the base for a data science process.
  • SEMMA : SEMMA is a list of sequential steps developed by SAS Institute, one of the largest producers of statistics and business intelligence software.
  • OSEMN : OSEMN stands for Obtain, Scrub, Explore, Model, and iNterpret. It is a list of tasks a data scientist should be familiar and comfortable working on.
  • TDSP : The Team Data Science Process (TDSP) is a method for developing predictive analytics solutions and intelligent applications in a cost-effective and timely manner.
  • TPC-X : Transaction Processing Performance Council benchmark for Hadoop, DS (Decision support), DI (Data Integration), AI (Artificial Intelligence)