Data Analytics

Become an expert in gathering, collating and analysing data. Learn the skills, tools and technologies to perform marketing, social media, financial data analytics and more

Admissions Open

Running regular batches. Contact us to get further details.

About Course

Data analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.

There are several applications of business analytics today. It is used across industries and job functions. It is widely used in Health care, Banking, IT, Insurance and basically any industry that generates and uses data to make decisions. Some applications of business analytics include

- Marketing analytics
- Pricing analytics
- Risk & Credit analytics
- Fraud analytics
- Health care analytics
- Financial Services analytics
- Social media data analytics and more


Features & Benefits


- 40 hours of online instuctor led training or classroom training
- Taught by Industry experts
- Learn In-demand skills and the software used in the industry
- Real world case studies
- Placement assistance

Is it good for me?

This course will make you comfortable with reviewing and working with data which is the basis of all analysis and decisions we take today. Whether you are working in Finance, marketing, HR, IT or consulting, this course will help you take big strides in your career. You will be able to use popular tools like R, Tableau, Excel to get useful insights into your data and make better decisions.

Mode of Delivery

Online instructor led sessions and Classroom training

Duration and Schedule

Duration: 10 weeks
Duration of class: 2 hours
Days: Saturdays & Sundays

Course Fees

INR 32,500 inclusive of taxes

Course Contents

* Tools used in Data Analytics
* Career Aspects with Data Analytics
* Case Studies of Successful campaigns and companies 

Chapter-1: Introduction to R

* Installing R
* Installing R Studio
* Workspace Setup
* R Packages

Chapter-2: R Programming

* R Programming
* if statements
* for statements
* while statements
* repeat statements
* break and next statements
* switch statement
* scan statement
* Executing the commands in a File

Chapter-3: R Data Structure

* Data structures
* Vector
* Matrix
* Array
* Data frame
* List
* Factors

Chapter-4: Apply Functions

* DPLYR & apply Function
* Import Data File
* DPLYP - Selection
* DPLYP - Filter
* DPLYP - Arrange
* DPLYP - Mutate
* DPLYP – Summarize

Chapter-5: Projects, Exercises, and best practises 

Chapter-1: Database Introduction

* What are Databases?
* What's the Role of Databases in Application Programming?
* Tables and Relations
* Primary and Foreign Keys and Other Constraints

Chapter-2: SQL querying

* What is Querying?
* The ANSI SQL Standard
* DML, DDL and More
* Common Query Tools

Chapter-3: Basic Queries

* The SELECT Statement
* Limiting Output Columns
* Formatting and Sorting Output
* Column Aliases

Chapter-4: Filtering

* The WHERE Clause
* Creating a Filter Condition
* Applying Multiple Filter Conditions
* More Filter Options

Chapter-5: Consolidating your data

* Counting Records
* Common Aggregate Functions: SUM, AVG, MIN, MAX
* Do's and Don'ts When Consolidating
* Unions and Other Multiset Consolidations

Chapter-6: grouping your data
* The GROUP BY Clause
* The HAVING Clause
* Do's and Don'ts When Grouping

Chapter-7: Joins

* Table Aliases
* Inner Joins
* Outer Joins
* Self Joins
* Complex Multi Table Joins

Chapter-8: Subqueries

* Filtering Using Subqueries
* The EXISTS Clause
* Subqueries as Alternative to Joins
* Derived Tables

Chapter-9: Manipulating Data

* The INSERT Statement
* The UPDATE Statement
* The DELETE Statement

Chapter-10: Transaction control

* What are Transactions?
* Initiating a Transaction
* The COMMIT and ROLLBACK Commands


* Creating Tables
* Creating and Using Views
* Developing and Calling Stored Procedures
* Implementing Triggers

Chapter 12: Big projects with best practises 

Chapter-1: Introduction to BI, Visualization, and Tableau

* Spheres of analytics
* BI & Reporting
* Why Visualization?
* Why Tableau?
* Tableau Product Line
* Tableau Environment, Architecture & Components
* Level setting terminologies
* Tableau Interface
* Visual cues for fields
* Fields in the data window
* Fields on shelves
* Tour of Shelves
* Basic connections
* Dimensions and Measures
* Basic Charting
* Saving and file formats 

Chapter-2: Talk to Tableau

Tableau generated fields
* Measure names
* Measure values
* Number of records
* Latitude and longitude

Data Preparation
* Analysing Data
* Tableau Data Re-shaper
* Connecting to Files / Databases / Servers
* Advanced connections (Joins, Live / Extracts)
* Editing Data Connections and Data Sources
* Replacing data sources
* Using and Refreshing Extracts
* Data Blending

* Using Show, Me!
* Dual Axis / Synchronize Axis
* Multiple Measures Combo Charts with different mark types (bar-in-bar)

* Playing with colors, sizes, tooltips, labels
* Transparency Highlighting

Titles, Captions, Headers Effective usage
* Edit axes
* Format results with mark labels and annotations

* Filter shelf
* Quick filters
* Measure filtering
* Dimension filtering
* Advanced filtering
* Filtering conditions
* Cascading

* Ascending / Descending
* Advanced techniques
* Dimension and Measures
* Table calculations
* Trend lines
* Drop lines
* Actions (worksheet & dashboard)
* Replace References
* Discrete versus Continuous

* File formats
* Packaged Workbooks
* Sharing Workbooks Publish to Reader / Office / PDF / Tableau Server
* Sharing over the Web

* Tableau's Mapping Capabilities
* Advanced Mapping Techniques
* Background Images
* Map Data & Pan/Zoom
* Lasso & Radial Selection
* Custom Geo-coding

Chapter-3: Advanced Functionalities and Engaging with Tableau

* Calculated Fields
* Bins
* Totals and Subtotals
* Sets
* Dashboard Formatting
* Granularity, Interactivity, Intuitiveness
* Parameters

Chapter-4: Advance Charts & Visualization

* Combined axis charts
* Combo charts – bar and line or mixed mark
* Pie charts, Heat maps, Scatter plots, Bins, Histograms, Box plots – box and whisker diagram or plot, Gantt bar chart, Pareto Charts, Sparklines, Waterfall Charts, Density Chart, Bump Charts, Funnel Charts, Bollinger Bands, Treemaps, Word Clouds, Bubble Charts
* Motion charts – working with Page Shelf and History, Bullet graphs

Chapter-5: Analytics with Tableau

* Forecasting
* Reference lines
* Reference bands
* Trend lines
* Statistics Calculations

Chapter-6: Analytics with Tableau

* Dashboard Distribution & Security
* Describe the security configurations for:
* Site level, Project level, Group level, User level
* Enable/disable Guest User
* Data source level, Workbook level
* Adding Users, License level, Admin level, Publisher level
* Permissions
* System permission composition
* Viewer / Interactor / Default license levels

Chapter-7: Dashboard Building & Story telling

* Various advanced projects
* Resume preparation
* Interview tips & preparation 


Career Options

* Data Analyst

* Business Analyst

* Data Science Expert

* Tableau Developer

* R Developer

* Business Intelligence Tableau Analyst

* Senior Software Engineer

* Analytics Consultant


Fill up the form below to enroll for our course.


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Email: skillingarena at skillingarena dot com                    
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