INTRODUCTION

There are numerous sources and formats for information. Significant business advantages may result from the ability to extract, model, and analyze information. Big Data analytics may help businesses spot trends and make necessary operational changes to capitalize on the findings, boost sales, and improve customer satisfaction.

This training session will offer a practical approach to identifying the needs for the use of data science, how they might be adopted, available technologies, which analytical models may be suited to deliver useful data, and how to make sense of Big Data and Analytics.

COURSE OBJECTIVES

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

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

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

• Our seasoned instructors, who have years of experience as seasoned professionals in their respective fields of work, will be teaching this course. A combination of practical exercises, theory, group projects, and case studies are used to teach the course.
• The participants receive training manuals and supplementary reading materials.
• Participants who complete this course successfully will receive a certificate.
• We can also create a course specifically for your organization to match your needs. To learn more, get in touch with us at training@dealsontrainers.org.
• The training will take place at DEALSON TRAINERS IN NAIROBI, KENYA in Nairobi, Kenya.
• The training fee includes lunch, course materials, and lodging for the training session. Upon request, we may arrange for our participants' lodging and transportation to the airport.
• Payment must be made to our bank account before the training begins, and documentation of payment should be emailed to training@dealsontrainers.org