Business Analytics using Tableau

Business Analytics using Tableau

Why Tableau for Data Analysis & Visualization? 
Gartner has rated Tableau in Leadership Quadrant for last 4+ years
(Click for details : www.bit.ly/kw-gartner).
 
Duration:  15 hours (Spread Over 5 Saturday's)

About Quality Policy:

KnowledgeWorks believes in providing high quality training, where over 50+ major software clients (http://bit.ly/kw-clients) have reposed confidence and come back to us for their technical training needs.. If you are unhappy after registering, we would be happy to refund the amount.

Course Objective:
The data analysis approaches normally used in the managerial decision making focus on validating predefined business questions, which are unable to discover unaware business questions or the “Unknown Unknowns” from the data and discover hidden patterns which may be indicative of several opportunities and risks that have not been factored in by the organisation. This short course will equip the participants in various industry segments including IT and others domains like retail, finance, manufacturing, banking to conduct Exploratory Data Analysis (EDA) on business datasets using the world leading Business Analytics tools – Tableau.

Tableau Software transforms the way people use data to solve problems by analyzing data faster, which are beautiful and useful for everyone.

Case Studies for Industry segments such as Retail/Ecommerce, Consumer Goods, will be discussed during the course.

Target Audience:
Team Leaders, Project Leaders / Managers, Technical Managers, Business Managers  (Retail/E-Commerce, Consumer Goods, Telecom, Finance)

Pre-requisites:
No Programming Language required but understanding of domain will help visualize use cases. Some basic knowledge of statistics will help understand and appreciate Machine Learning algorithms.

Workshop Topics:
Module-1: Basics of Data
1. Handling data, Data Cleaning and Transformation.
2. Understanding Variables and Observations
3. Types of Variables, Central Tendency, Distribution of the Data.
4. Concepts of Exploratory Data Analysis

Module-2: Exploratory Data Analysis and Visual Analytics using Tableau
1. Importance of Data Visualization for understanding data
2. Introduction to Visual Analytics using Tableau
a. Basics of Descriptive Analytics
b. Understanding Measures and Dimensions
c. Working with different variable types – Numerical, Categorical and Dates.
d. Building Basic Charts for understanding single variable – Histogram, Box Plot, Bar Chart, Line Chart, Pareto Chart etc.
e. Building Charts for examining relationship between various variable types – Scatter Plot, Matrix plot, Mosaic plot etc.
3. Advanced Data Analysis features in Tableau
a. Performing calculations – using Calculated fields, Table Calculations
b. Time Series Forecasting
c. Regression Lines
d. Creating Sets, Groups for aiding dynamic analysis
e. Use of Clustering techniques for segmentation
4. Creating dashboards and interactive visualizations in Tableau (for analysing and understanding relationship between a large number of variables)
a. Creating Dashboards
b. Creative Interactive visualizations
c. Use of Filters

Facilitator Profile: KnowledgeWorks Accredited Trainer
Over 22 years of experience in Information Technology (IT) Industry, focused at offering solutions for enterprises in the areas of skill enhancement, Web & Mobile application development and Business Analytics. The trainer experiences spans multiple industry domains ( Consumer, Telecom, Banking & Insurance, IT, etc). With passion for analytics, the trainer loves working with data, and its application across domains to explore meaningful outcome for the businesses to take informed decisions. The trainer has been extensively working with Tableau for Exploratory Data Analysis (EDA) and further taking it to next level of using Tableau for Predictive Analysis by interfacing with Python & R to take advantages of inbuilt libraries to build Machine Learning algorithms like Regression, Classification techniques.