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Data Analytics Courses

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What you’ll learn

Program Highlights

Convenient learning format

Convenient learning format

Online learning format with mentorship from industry experts

Dedicated career services

Dedicated career services

Resume & interview preps with industry experts & exclusive job board

Learn from the best

Learn from the best

Award winning faculties in Data Analytics domain from top IT background.

Structured program with dedicated support

Structured program with dedicated support

Dedicated program manager to ensure that students make progress and have learning outcomes

Hands on learning

Hands on learning

Become job-ready by applying what you learn and build real-life projects in Data Analytics and Data Science

Data Analytics Course Content

Business Statistics

Introduction to Statistical Analysis

  • Counting, Probability, and Probability Distributions
  • Sampling Distributions
  • Estimation and Hypothesis Testing
  • Scatter Diagram
  • Anova and Chisquare
  • Imputation Techniques
  • Data Cleaning
  • Correlation and Regression

Introduction to Data Analytics

  • Data Analytics Overview
  • Importance of Data Analytics
  • Types of Data Analytics
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Benefits of Data Analytics
  • Data Visualization for Decision Making
  • Data Types, Measure Of central tendency, Measures of Dispersion
  • Graphical Techniques, Skewness & Kurtosis, Box Plot
  • Descriptive Stats
  • Sampling Funnel, Sampling Variation, Central Limit Theorem, Confidence interval

Excel: Basics to Advanced

Basic Excel

  • Excel tutorial
  • Text to Columns
  • Concatenate
  • The Concatenate Function
  • The Right Function with Concatenation
  • Absolute Cell References
  • Data Validation
  • Time and Date Calculations
  • Conditional Formatting
  • Exploring Styles and Clearing Formatting
  • Using Conditional Formatting to Hide Cells
  • Using the IF Function
  • Changing the “Value if false” Condition to Text
  • Pivot Tables
  • Creating a Pivot Table
  • Specifying PivotTable Data
  • Changing a PivotTables Calculation
  • Filtering and Sorting a PivotTable
  • Creating a PivotChart
  • Grouping Items
  • Updating a PivotTable
  • Formatting a PivotTable
  • Using Slicers
  • Charts
  • Creating a Simple Chart
  • Charting Non-Adjacent Cells
  • Creating a Chart Using the Chart Wizard
  • Modifying Charts
  • Moving an Embedded Chart
  • Sizing an Embedded Chart
  • Changing the Chart Type
  • Chart Types
  • Changing the Way Data is Displayed
  • Moving the Legend
  • Formatting Charts
  • Adding Chart Items
  • Formatting All Text
  • Formatting and Aligning Numbers
  • Formatting the Plot Area
  • Formatting Data Markers
  • Pie Charts
  • Creating a Pie Chart
  • Moving the Pie Chart to its Own Sheet
  • Adding Data Labels
  • Exploding a Slice of a Pie Chart
  • Data Analysis − Overview
  • types of Data Analysis
  • Data Analysis Process
  • Working with Range Names
  • Copying Name using Formula Autocomplete
  • Range Name Syntax Rules
  • Creating Range Names
  • Creating Names for Constants
  • Managing Names
  • Scope of a Name
  • Editing Names
  • Applying Names
  • Using Names in a Formula
  • Viewing Names in a Workbook
  • Copying Formulas with Names
  • Difference between Tables and Ranges
  • Create Table
  • Table Name
  • Managing Names in a Table
  • Table Headers replacing Column Letters
  • Propagation of a Formula in a Table
  • Resize Table
  • Remove Duplicates
  • Convert to Range
  • Table Style Options
  • Table Styles
  • Cleaning Data with Text Functions
  • Removing Unwanted Characters from Text
  • Extracting Data Values from Text
  • Formatting Data with Text Functions

Advance Excel

  • Date Formats
  • Conditional Formatting
  • Sorting
  • Filtering
  • Lookup Functions
  • Pivoting


Syllabus of SQL Training

  • Introduction to Oracle Database
  • Retrieve Data using the SQL SELECT Statement
  • Learn to Restrict and Sort Data
  • Usage of Single-Row Functions to Customize Output
  • Invoke Conversion Functions and Conditional Expressions
  • Aggregate Data Using the Group Functions
  • Display Data from Multiple Tables Using Joins
  • Use Sub-Queries to Solve Queries
  • The SET Operators
  • Data Manipulation Statements
  • Use of DDL Statements to Create and Manage Tables
  • Other Schema Objects
  • Control User Access
  • Management of Schema Objects
  • Manage Objects with Data Dictionary Views
  • Manipulate Large Data Sets
  • Data Management in Different Time Zones
  • Retrieve Data Using Sub-queries
  • Regular Expression Support


Module 1: Tableau Course Material

  • Start Page
  • Show Me
  • Connecting to Excel Files
  • Connecting to Text Files
  • Connect to Microsoft SQL Server
  • Connecting to Microsoft Analysis Services
  • Creating and Removing Hierarchies
  • Bins
  • Joining Tables
  • Data Blending

Module 2: Learn Tableau Basic Reports

  • Parameters
  • Grouping Example 1
  • Grouping Example 2
  • Edit Groups
  • Set
  • Combined Sets
  • Creating a First Report
  • Data Labels
  • Create Folders
  • Sorting Data
  • Add Totals, Sub Totals and Grand Totals to Report

Module 3: Learn Tableau Charts

  • Area Chart
  • Bar Chart
  • Box Plot
  • Bubble Chart
  • Bump Chart
  • Bullet Graph
  • Circle Views
  • Dual Combination Chart
  • Dual Lines Chart
  • Funnel Chart
  • Traditional Funnel Charts
  • Gantt Chart
  • Grouped Bar or Side by Side Bars Chart
  • Heatmap
  • Highlight Table
  • Histogram
  • Cumulative Histogram
  • Line Chart
  • Lollipop Chart
  • Pareto Chart
  • Pie Chart
  • Scatter Plot
  • Stacked Bar Chart
  • Text Label
  • Tree Map
  • Word Cloud
  • Waterfall Chart

Module 4: Learn Tableau Advanced Reports

  • Dual Axis Reports
  • Blended Axis
  • Individual Axis
  • Add Reference Lines
  • Reference Bands
  • Reference Distributions
  • Basic Maps
  • Symbol Map
  • Use Google Maps
  • Mapbox Maps as a Background Map
  • WMS Server Map as a Background Map

Module 5: Learn Tableau Calculations & Filters

  • Calculated Fields
  • Basic Approach to Calculate Rank
  • Advanced Approach to Calculate Ra
  • Calculating Running Total
  • Filters Introduction
  • Quick Filters
  • Filters on Dimensions
  • Conditional Filters
  • Top and Bottom Filters
  • Filters on Measures
  • Context Filters
  • Slicing Fliters
  • Data Source Filters
  • Extract Filters

Module 6: Learn Tableau Dashboards

  • Create a Dashboard
  • Format Dashboard Layou
  • Create a Device Preview of a Dashboard
  • Create Filters on Dashboard
  • Dashboard Objects
  • Create a Story

Module 7: Server

  • Tableau online.
  • Overview of Tableau Server.
  • Publishing Tableau objects and scheduling/subscription.

Power BI

Module 1: Introduction to Power BI

  • Get Started with Power BI
  • Overview: Power BI concepts
  • Sign up for Power BI
  • Overview: Power BI data sources
  • Connect to a SaaS solution
  • Upload a local CSV file
  • Connect to Excel data that can be refreshed
  • Connect to a sample
  • Create a Report with Visualizations
  • Explore the Power BI portal

Module 2: Viz and Tiles

  • Overview: Visualizations
  • Using visualizations
  • Create a new report
  • Create and arrange visualizations
  • Format a visualization
  • Create chart visualizations
  • Use text, map, and gauge visualizations and save a report
  • Use a slicer to filter visualizations
  • Sort, copy, and paste visualizations
  • Download and use a custom visual from the gallery

Module 3: Reports and Dashboards

  • Modify and Print a Report
  • Rename and delete report pages
  • Add a filter to a page or report
  • Set visualization interactions
  • Print a report page
  • Send a report to PowerPoint
  • Create a Dashboard
  • Create and manage dashboards
  • Pin a report tile to a dashboard
  • Pin a live report page to a dashboard
  • Pin a tile from another dashboard
  • Pin an Excel element to a dashboard
  • Manage pinned elements in Excel
  • Add a tile to a dashboard
  • Build a dashboard with Quick Insights
  • Set a Featured (default) dashboard
  • Ask Questions about Your Data
  • Ask a question with Power BI Q&A
  • Tweak your dataset for Q&A
  • Enable Cortana for Power BI

Module 4: Publishing Workbooks and Workspace

  • Share Data with Colleagues and Others
  • Publish a report to the web
  • Manage published reports
  • Share a dashboard
  • Create an app workspace and add users
  • Use an app workspace
  • Publish an app
  • Create a QR code to share a tile
  • Embed a report in SharePoint Online

Module 5: Other Power BI Components and Table Relationship

  • Use Power BI Mobile Apps
  • Get Power BI for mobile
  • View reports and dashboards in the iPad app
  • Use workspaces in the mobile app
  • Sharing from Power BI Mobile
  • Use Power BI Desktop
  • Install and launch Power BI Desktop
  • Get data
  • Reduce data
  • Transform data
  • Relate tables
  • Get Power BI Desktop data with the Power BI service
  • Export a report from Power BI service to Desktop

Module 6: DAX functions

  • New Dax functions
  • Date and time functions
  • Time intelligence functions
  • Filter functions
  • Information functions
  • Logical functions
  • Math & trig functions
  • Parent and child functions
  • Text functions

Python Basics

Objective: To Understand Python basic concepts.

Application: Used in Program to give comments, print the values.

  • The print statement
  • Comments
  • Python Data Structures & Data Types
  • String Operations in Python
  • Simple Input & Output
  • Simple Output Formatting
  • Deep copy
  • Shallow copy
  • Operators in python

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Frequently Asked Questions

Besant Technologies is a global, best e-learning site in India with 200+ short online courses and Micro-Credentials. At Besant technologies, we deliver fully online, and our learning content is accessible to everyone. Our course categories include Business, Marketing, Education, Fitness & Health, Human Resources; Training & Assessment.

Besant Technologies is the Best Institute for Data Analytics Course in Chennai & Bangalore. If you don't want to dive into programming or spend many hours coding on becoming a Data Analyst, then the data analytics course by Besant Technologies is for you.

The online Data Analytics courses involve the following:
  • You will get hands-on experience with real-life projects
  • You will work on industry-grade assignments with high relevance in the corporate world
  • You can apply for the best Data Analyst and Data Science jobs in top MNCs

You should carry a Bachelor's Degree in Statistics, Mathematics, Computer Science, or a related subject.

Besant Technologies offers you the most current, relevant, and high-value projects as part of this course. This allows you to put your newly gained information and abilities to use in a real-world industry setting. All of our training includes several projects that put your abilities, learning, and practical knowledge to the test, ensuring that you are industry-ready.

We offer Classroom Training and Online Training.

Yes, We at Besant Technologies offer 100% Big Data Analytics training course with job placement in Chennai & Bangalore for certified data analytics professionals. For this, we are exclusively tied-up with top MNCs from around the world. It helps us place you in leading organizations such as Sony, TCS, Mu Sigma, Cognizant, and Cisco, among other equally great enterprises. We help you with the job interview and résumé preparation as well.

Business Analytics / Data Analytics Certification / Data Science Certificate Program Training are a reasonable next step for professionals who want to further their careers. This includes:

  • Professionals involved in the development of business intelligence and reporting software
  • Professionals who operate in the field of data warehousing
  • Statisticians, Economists, and Mathematicians are all types of statisticians.
  • Programmers of software
  • Business Analysts

We provide you certificates that are valid for a lifetime! You will receive a Certificate of Completion that is recognized in India, demonstrating your commitment to learning new skills.

Besant Technologies does not offer full refunds outside of the 7 days under any circumstances due to our significant intellectual property and goodwill.

We accept all major kinds of payment options. Cash, Card (Master, Visa and Maestro etc), Net Banking, razorpay, ccavenue, paypal and etc...

What is Data Analysis?

Data analysis is the act of cleansing, transforming, and reporting data to provide helpful information that can be used to make business decisions.

What is the objective of the Data Analytics Course?

The Data Analytics courseware is expertly designed to help you become skilled with Data Analytics tools and methodologies.

  • Learn about statistical computing and the R programming language.
  • Firm grasp of the Linear and Non-Linear Regression models and the classification techniques utilized in data analysis.
  • Understand how to use Excel to do Business Analytics.
  • Excel, Advanced Excel, Tableau, SQL, Power BI, R, and Python are all covered in the Data Analytics Course.

Prerequisites to learn Data Analytics Course

The Data Analytics Course is for professionals who have good expertise in excel, business analysis, Hadoop, etc. Moreover, there are specific skills required to be a data analyst. This include:-

  • Programming Languages: He should be familiar with programming languages such as R and SAS and data gathering and analysis.
  • Strong communication: An intelligent strategy to succeed is to communicate assertively. They must specify if the audience or team members are involved in the decision-making process.
  • Advanced MS Excel hands-on training: They must have a thorough grasp of sophisticated modeling and analysis.

Skills Covered in Data Analytics Course

  • Data Visualization
  • Data Cleaning
  • R
  • Python
  • SQL and NoSQL
  • Machine Learning
  • Linear Algebra and Calculus
  • Microsoft Excel
  • Critical Thinking
  • Communication

What are the Benefits of Data Analytics Courses?

With the aid of data cleaning, it detects and fine-tunes problems in data sets. It helps to improve data quality, which benefits both customers and organisations like banks, insurance firms, and financing businesses. It further benefits organizations as:-

  • It eliminates duplicate data from data sets, saving a significant amount of RAM. This lowers the company's costs.
  • It aids in presenting appropriate advertising on online shopping websites based on customer purchasing behavior and historical data.
  • It lowers banking risks by detecting potentially fraudulent clients through historical data analysis. This assists the institution in determining whether or not to provide applicants with a loan or credit card.

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