INTRODUCTION

Information can exist in many forms and sources. The ability to extract, model and analyses information, can provide significant commercial benefits. Big Data Analytics can assist organizations identify trends and adjust operational procedures to harness the results, to increase revenue and client experience.

This training course will provide a practitioner approach to identify requirements for the application of data science, how these can be adopted, technologies available, which analytical models may be appropriate to provide valuable data and how to make sense of Big Data and Analytics.

COURSE OBJECTIVES

By the end of the course, participants should be able to:

• Understand the role of Big Data for their organization
• Appreciate when to apply Data Analytics and the Best Methods of Approach
• Consider How to Choose Appropriate Models and Technology for Big Data
• Learn from case study examples and use case scenarios
• Successfully achieve results from applying best practice in Data Analytics

DURATION

5 Days

WHO SHOULD ATTEND

This training course has been designed for senior executives, technical engineers and those involved in the technology, research and statistical analysis of corporate data.

This training course is suitable to a wide range of professionals but will greatly benefit:

• Statistical and Research Analysts
• Key Application Development and data Research Personnel
• Technology Engineers, CTO and CIO
• Strategic Development Directors

COURSE CONTENT

Day One: Big Data Analytics

• Current Practices and trends in Big Data Analytics
• Business Intelligence v Data Science
• Analytical Architecture for Big Data
• Roles for Big Data within the Technology and Commercial Enterprise
• Key Drivers for Big Data Analytics
• Case Study and Summary

Day Two: Data Analytics Models and Lifecycle

• Data Analytics Lifecycle
• Stage 1 - Discovery
• Stage 2 - Preparation of Data
• Stage 3 - Model Planning and Review
• Stage 4 - Model Creation
• Stage 5 - Communication Plan
• Stage 6 - From Planning to Operation
• Case Study and Summary

Day Three: Data Analytical Methods and Programs Overview

• Overview of R Framework
• Overview of Big Data Analytics
• Exploratory Data Analysis
• Statistical methods of Evaluation
• Advanced Methods of Clustering
• Advanced Theory and Methods of Association Rules
• Advanced Theory and Methods of Regression
• Case Study and Summary

Day Four: Advanced Theory and Methods Overview

• Advanced Analytical Theory of Classification
• Advanced Analytical Theory of Time Series Analysis
• Advanced Analytical Theory of Textual Analysis
• Technology and Tools for Advanced Data Analytics
• Use Case and Assessment
• Case Study and Summary

Day Five: Technology, Tools and Achieving Results

• Unstructured Data Analytics
• Advanced Analytical Tools in Database Analytics
• How integrate Data Analytics
• Current Best Practice Management and Approach for Project Delivery
• Data Visualation Overview
• Summary ad Case Study

GENERAL NOTES

• This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.
• Training manuals and additional reference materials are provided to the participants.
• Upon successful completion of this course, participants will be issued with a certificate.
• We can also do this as tailor-made course to meet organization-wide needs. Contact us to find out more: training@data-afriqueconsultancy.org
• The training will be conducted at DATA-AFRIQUE TRAINING CENTRE, NAIROBI KENYA.
• The training fee covers tuition fees, training materials, lunch and training venue. Accommodation and airport transfer are arranged for our participants upon request.
• Payment should be sent to our bank account before start of training and proof of payment sent to: training@data-afriqueconsultancy.org