ExcelR’s Certificate of Advanced Studies – Data Analysis / Business Analysis

Intro Data Analysis

Data Analytics provides a subtle way to analyze the data in a qualitative and quantitative manner to draw logical conclusions. Gone are the days where one has to think about gathering the data and saving the data to form the clusters. For the next few years, it’s all about Data Analytics and it’s techniques to boost the modern era technologies such as Machine learning and Artificial Intelligence. .

ExcelR’s Certificate of Advanced Studies – Data Analysis / Business Analysis program curriculum

provides extensive knowledge of Data Collection, Extraction, Cleansing, Exploration, and Transformation. Alongside the Data Mining, Data Integration is done with feature Engineering to build Prediction models for Data Visualization and deploying the solution. You name the skillset and our trainers are always there to handle the new generation tools with latest versions. As a part of the Data Analytics training, the range of skills and tools that are emphasized in the course include Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, Tableau, Spark, Hadoop, programming languages like R and Python.


Graduate in commerce, science and engineering any stream, working professional from any domain with logical, analytical skills.

Aspirant with good analytical abilities / background - Finance and accounting, management domain
"Steinbeis University, Berlin Accreditation, “It is continuing faithfulness in the founding and development of this institution and outstanding competence, and excellence in deliveries".

Steinbeis accreditation recognizes ExcelR’s excellence in areas such as curriculum, faculty qualifications, support services, institutional effectiveness, planning and learning resources and student learning outcomes

Topics What We Cover


  • Excel: Basics to Advanced
  • SQL
  • Tableau
  • Power BI
  • SAS
  • R Basic
  • Python Basics

Advanced Excel –Basic

  • Customizing the Ribbon
  • Worksheets
  • Format Cells
  • Various selection techniques
  • Shortcuts Keys
  • Protecting and un-protecting worksheets

Advanced Excel -Sorting and Filtering Data

  • Sorting tables
  • Using multiple-level sorting
  • Using custom sorting
  • Filtering data for selected view (AutoFilter)
  • Using advanced filter options

Advanced Excel -Data Validations

  • Specifying a valid range of values for a cell
  • Specifying a list of valid values for a cell
  • Specifying custom validations based on formula for a cell

Advanced Excel -Text Function

  • Upper, Lower, Proper; Left, Mid, Right;
  • Trim, Len, Exact
  • Concatenate

Advanced Excel -Function & Formula

  • Basic Function –Sum, Average, Max, Min, Count, Count A
  • Conditional Formatting
  • Logical functions (AND, OR, NOT)
  • Lookup and reference functions (VLOOKUP, HLOOKUP, MATCH, INDEX)
  • V-lookup with Exact Match, Approximate Match
  • Nested V-lookup with Exact Match
  • V-lookup with Tables, Dynamic Ranges
  • Nested V-V-lookup with Exact Match
  • Using V-lookup to consolidate Data from Multiple Sheet
  • Mathematical Functions
  • SumIf, CountIf, Averag

Advanced Excel -Pivot Tables

  • Creating Simple Pivot Tables
  • Basic and Advanced value field setting
  • Grouping Based on number and Date
  • Calculated field and Calculated items

Advanced Excel –Charts & Slicers

  • Using Charts; Formatting Charts
  • Using 3D Graphs
  • Using Bar and Line Chart together
  • Using Secondary Axis in Graph
  • Sharing Charts with PowerPoint / MS Word, Dynamically

Advanced Excel -Working with Templates

  • Designing the structure of a template
  • Using templates for standardization of worksheets

Advanced Excel -VBA-Macro

  • Introduction to VBA; What is VBA ?
  • What can you do with VBA ?
  • What can you do with VBA ?
  • Procedures and Function in VBA

Advanced Excel -Variable in VBA

  • What is Variables ?
  • Using Non-declared variables; Variable Data Types

Advanced Excel -Message-Box and Input-box functions

  • Customize Message-Box and Input-box
  • Reading cell values into messages
  • Various button groups in VBA

VBA Coding Advanced function

  • If and Select statement
  • Looping in VBA
  • Mail Function –send automated email
  • Automated report will be shown


  • Introduction to Databases
  • Databases; Introduction to DBMS
  • Popular DBMS Software
  • Concepts of RDBMS
  • Tables
  • Tuples
  • Attributes
  • Normalization
  • First Normal Form
  • Second Normal Form
  • Third Normal Form
  • NoSQL Database
  • Types of NOSQL
  • Comparison

SQL Commands

  • Types of SQL Commands
  • Data Definition Language
  • Create, Drop, Truncate, Alter and Rename Objects
  • Data Query Language
  • Select Statements
  • Data Manipulation Language
  • DCL and TCL
  • Grant, Revoke and transaction statement
  • SQL Data Types; Numeric, Date and Time, LOB Types

DML Commands

  • Insert, Update and Delete Statements
  • DDL Commands
  • Create and Drop Databases

Database Constraints

  • Types of Constraints
  • Relational Integrity Constraints
  • Key Constraints
  • Domain Constraints
  • Referential Integrity
  • Types Of Constraints
  • Primary and Foreign Keys
  • Application of Indexes
  • Checking Constraints
  • Alter Tables
  • Repeat and Leave Statements
  • Cursors
  • Operators and Functions
  • Joining Tables
  • Inner Join, Left Join, Right join
  • Advantages of Procedures

SQL Transactions

  • Examples
  • ACID Properties
  • TCL Statements
  • Start, Commit and Rollback Statements
  • Auto Commit
  • Save Points
  • Identifier
  • Rollback and Release

Database Objects

  • Tables
  • Creating, Altering and dropping tables
  • Sequences
  • Auto Increments
  • Re-Sequencing
  • Views
  • Advantages
  • Creating and Dropping Views
  • Indexes
  • Types of Indexes
  • B-Tree and Hash Indexes
  • Creating and dropping Indexes

Stored Procedures and Functions

  • Stored Objects
  • Types of Stored Objects
  • Stored Procedures
  • Create, call and drop stored procedures
  • Using Variables
  • Handling Exceptions
  • Named Errors and Re-signals
  • Programming
  • If-then-Else and Case Statements
  • Loops
  • Repeat and Leave Statements
  • Cursors
  • Operators and Functions
  • Joining Tables
  • Inner Join, Left Join, Right join
  • Advantages of Procedures

Database Triggers Accessing Database From R and Python

  • Triggers
  • Database Triggers
  • Data Definition Language (DDL) Triggers
  • Data Manipulation Language (DML) Triggers
  • CLR Triggers
  • Logon Triggers
  • Triggers v/s Stored Procedures
  • Accessing Database from R
  • Install R Packages
  • Configuration Information
  • Python Database Access
  • Databases Supported
  • Libraries
  • Read Operations
  • Insert, Update and Delete
  • Performing Transactions
  • Handling Errors


  • What is Data Visualization
  • Advantages & Disadvantages of visualizations

Age of Big data

  • Why Data visualization Important
  • Understanding data
  • Examples of Data visualizations in Action
  • Different data visualizations

Principles of Visualizations

  • Design Principles
  • Best Practices
  • Data Viz Inspiration

Tableau –Data Visualization Tool

  • Introduction to Tableau
  • What is Tableau
  • Overview Of Tableau Tool(Servers , data , visualizations)
  • Tableau Architecture
  • Advantages & Disadvantages

Different Products of Tableau

  • Tableau Desktop
  • Tableau Public
  • Tableau Prep
  • Tableau Online
  • Tableau Server
  • Tableau Analytics

Extensions in Tableau

  • Tableau Workbook
  • Tableau Data Source
  • Tableau Data Extract
  • Tableau Packaged Workbook (TWBX)
  • Tableau Packaged Data Source (TDSX)
  • Tableau Book Mark
  • Tableau Map Source
  • Tableau Preferences

Features of Tableau Desktop

  • Connecting to Data from servers
  • Connecting Data from ODBC
  • Connecting data from local repositories

Tableau-Joins and Data Pane

  • What are Joins in Tableau
  • Types Of Joins in Tableau
  • Inner Join
  • Left Join
  • Right Join
  • Full Outer Join
  • Union
  • Creating Joins Using Data

Tableau Data Pane

  • Dimensions
  • Measures
  • Parameters
  • Sets

Pivot Table and Split Tables in Tableau

  • In built Charts in Tableau
  • Basic Charts
  • Text Tables
  • Highlight Tables
  • Bar charts
  • Stacked Bar
  • Line Graphs
  • Dual axis
  • Pie chart etc

Maps in Tableau

  • Symbol Maps
  • Filled maps
  • Combined maps
  • Map layers
  • WMS
  • Polygon Maps
  • Custom coding etc.
  • How to Interpret Bullet Graphs
  • Actual Profit vs Budget Profit Analysis
  • Market wide Analysis etc

How to Interpret Scatter Plot

  • Correlation Analysis
  • Direction of Relationship
  • Strength of Relationship etc.

How to Interpret Histogram

  • Distributive Analysis, Bin Sizes, Custom bin sizing etc.

How to Interpret Box Plot chart

  • Distributive Analysis, Quartile Analysis, 5 Point Chart Analysis

Data Interpretation

  • Understanding of data types, discussing about dimensions and measures etc.
  • Creating Calculated Fields
  • Attribute functions
  • Quick table calculations

Creation of calculated fields

  • Aggregate and disaggregate functions etc.

Logical Functions

  • Understanding If-else statements, applications of if-else statements (eg: high profit , low profit etc.)

Case-If Function

  • Understanding Case Statements with examples
  • Applications of case statements

ZN Function

  • Creation of ZN functions
  • Application of ZN functions
  • Dealing with calculated fields etc.

Ad-Hoc Calculations

  • Calculations using parameters
  • Sets
  • Filters etc and applications

Manipulating Text-Left & Right Functions

  • Understanding different string functions etc.

Pre-Defined Analytics

  • Forecasting ,LOD Expressions , Functions, Groups, Filters, etc

Dashboards Hands-On in Tableau

  • Understanding concept of Dashboards
  • Building Interactive dashboards
  • Dashboard actions, etc.

Story Hands-On in Tableau

  • Relevance of stories in Dashboards, Working with examples on stories etc.

Animated Visualization Hands-On

  • Animation charts, play controls, page shelf, applications of animation charts

Tools for Sharing Information

  • Understanding Tableau Reader, Tableau online etc.
  • Publishing our Workbooks in Tableau Server
  • Exploring publishing options using Tableau
  • Discussing sharing of workbooks, etc.

Connecting Tableau with Tableau Server

  • Overview of how to connect Tableau with Tableau server.

What is R?

  • R software, installation , R studio ,Overview of how to connect Tableau with Tableau server.Understanding basic interface of R .

Connecting Tableau with R

  • R serve package, using functions such as SCRIPT_REAL etc, Understanding with examples.

How to integrate Tableau with R?

  • R serve package, external connections, ports, Understanding with examples.

Basics of R

  • Introduction of R
  • Data Types
  • Data Structures
  • Decision Making Statements
  • Conditional Loops
  • Flow Control Statements
  • If Statements
  • For loops
  • While Loops
  • Built Functions in R : Base, datasets, dplyr and ggplot
  • Changing the Method of Aggregation
  • Methods of Aggregation Challenge
  • Methods of Aggregation Challenge Completed
  • Cards and Multi Row Cards
  • Cards, Matrix and Multi Row Card Challenge
  • Answers to Cards Challenge
  • Percentage Calculations
  • Filtering Data -Using Slicers
  • Filtering Data -Visual Filters
  • Filtering Data -Page Filters
  • Filtering Data –Drill Through Filter
  • Practical Activity -Filters
  • Practical Activity Filters Completed

Basics of Python

  • Introduction to Python & Data Science Python Installation on laptops
  • Python Basics -Variables -Python Build in functions -Modules -Python Libraries installation using PIP
  • Python Basics -Python Operators
  • Decision Making Statements
  • Python Basics -Flow Control Statements - If Statements -While Loops
  • Python Basics -Data & time modules in python -Interfaces in Python -For Loops

Python modules for Data Analysis

  • Python Basics –Web scrapping-Python custom functions -Lambda Function - Regular Expressions
  • Data science Life cycle –Numpy Module
  • Data science Life cycle –Pandas Module
  • Data science Life cycle –Matplolib Module

Power BI (E-Learning Module)

  • Introduction to Power BI Preview
  • Download the Training Data Files
  • Introduction to Signing Up for Power
  • Signing up for Power BI Preview
  • Load Data into the Power BI Service
  • Preview
  • Practical Activity

The Power BI Desktop

  • Intro to Power BI Desktop Section
  • Introduction to the Power BI Desktop Preview
  • Creating Reports in Power BI Desktop

Create Reports in Power BI Desktop Section

  • Creating Tables in Power BI
  • Table Styles and Formatting Preview
  • Matrix Visualization 06:11
  • Tables and Metrics Practical Activity
  • Answers to Tables and Metrics Practical Activity

Create Reports in Power BI Desktop Section

  • Introduction to Visualization Section
  • Clustered Column Graphs
  • Stacked and 100% Graphs
  • Column Graph Challenge
  • Column Graph Challenge Completed
  • Graph Options
  • Trend Analysis Graphs
  • Area Graphs
  • Ribbon Graphs
  • Additional Graphs
  • Scatterplots and Bubble

Interactive Dashboards

  • Creating Interactive Dashboards
  • Challenge -Create an Interactive Report
  • Completed Challenge -How to Create an Interactive Report
  • Publishing Reports to the Power BI Service
  • Pinning Visualizations to Dashboards
  • Mobile Reports
  • Q and A
  • App Workspaces
  • Publishing an App
  • Using Themes in Power BI
  • Using Custom Visualizations

DAX Formulas

  • DAX Formulas Section
  • DAX Formulas
  • Date Functions
  • Formatting Dates
  • Date Master Tables

DAX Measures

  • Introduction to Measures Section
  • Introduction to DAX Measures
  • DAX Measures Practical Activity
  • DAX Measures Activity Completed
  • The =Calculate Formula


  • Relationships Section
  • Creating and Managing Relationships in Power BI
  • Relationship Calculations

Power BI Query Editor

  • Introduction to Power BI Query Editor
  • Basic Transformations -Part 1
  • Basic Transformations -Part 2
  • Aggregating Data

Duration 160 Hours


These given topics are very important for examination point of view. Student must learn these.


Examination details

1 Pattern 60 Multiple Choice Questions
2 Topics Data Analysis 100%
3 Time in minutes 90
4 Mode Online - Computer Based(Web proctoring)
5 Pass Percentage 60%
6 Number of attempts allowed 2
7 When will be the examination Every 1st / 3rd Sunday of a month
8 Criteria 80% attendance
9 Mock tests 2

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