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Wed 16 Oct 2019
  • Runs till: Wednesday, 16th October 2019
  • Time: 09:00 AM - 03:00 PM
  • Location: THE HERON PORTICO Nairobi, Kenya
  • Host : Jill Cannon Associates

 The industry, expert-led sessions will equip you with the building blocks and advanced technical concepts to propel your data analytics strategy, combine the power of Data Science, Machine Learning and Business Intelligence to create powerful data analytics for Real-World applications. The programme is organized around 6 areas of business analytics: 

1.Decision Biases: Identify the types of biases in a decision making process and learn how to ask for the right information.

2.Descriptive Analytics: Be able to collect, clean, and describe the data you have, including the summary statistics.

3.Big Data Opportunities: Identify what big data means to you and what you can do with it.

4.Experimentation: Design experiments to gather meaningful data to make data driven decisions.

5.Predictive Analytics: Use machine learning tools/models, identify neural networks, and analyze data to optimize decisions for your business.

6.Organizational, Ethical and Legal Issues: Identify organizational issues that you will need to consider when making decisions; identify the legal and ethical issues behind gathering, storing, and using data.

Learn the key Business Intelligence, Machine Learning and Artificial Intelligence concepts and intuition training to get you quickly up to speed with all things BI and AI. The Topics to be covered include:

Module 1: Introduction to the Analytics landscape

•Big Data and Analytics

•Business Intelligence and Analytics

•Business Analytics Vs. Predictive Analytics

•Self-service Reporting (Self-service BI and analytics).

Module 2: How to compete on Analytics

•Data discovery;

•The Key Questions to ask your data; 

•Overview of enterprise ‘Data to Decisions’ process;

•Centralizing and Actioning your Customer data.

Module 3: Analytics Capabilities

•Data integration;

•Data preparation;

•Data warehousing;

•Data architecture;

•Data Management and Data Governance; 

•BI & DW modernization;

•Data Quality assurance.

Module 4: Case Simulation

•AI for Business Processes (Artificial Intelligence and Machine Learning);

•Walkthrough Projects in Different Industries (Challenges and Solutions);

•Visualization-BI Tools in the market (Microsoft Power BI and Tableau Hands-on Demo).

•BI and analytics for big data;

•BI and analytics for cloud apps.

* A certificate of completion shall be issued to attendees who will have attended all the module sessions above.

Gain an understanding of the complete data analytics life cycle, from problem definition to solution deployment through various industry-specific examples and case studies, and learn how analytics, data visualization and data science methodologies can be used to drive better business decisions.


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