Data Analytics Course

Real-Time Data Analytics Training — Online & Offline in Bangalore

At Crystalspiders Institute, our Data Analytics Course is designed to equip you with the skills to interpret data, uncover insights, and make data-driven decisions that drive business success. Whether you are a beginner or a professional looking to upskill, this program provides hands-on experience and practical exposure to industry-standard tools.

Master the Art of Turning Data into Business Insights:

In the current data-centric environment, businesses depend on data analytics to enhance decision-making, forecast trends, and secure a competitive advantage. At Crystalspiders Institute, we offer an extensive Data Analytics Training Program that connects theoretical knowledge with practical application.

Whether you are just starting out or a seasoned professional aiming to improve your skills, this course delivers practical training, live projects, and expert guidance to empower you to become a proficient data analyst.

What You’ll Learn:

Data Fundamentals: Grasping the concepts of data types, sources, and methods of collection.

SQL for Data Management: Executing queries, filtering, and overseeing structured data.

Python for Analytics: Manipulating data with libraries such as Pandas, NumPy, and Matplotlib.

Data Visualization: Developing interactive reports and dashboards using Power BI and Tableau.

Statistics & Probability: Utilizing analytical reasoning on real-world datasets.

Exploratory Data Analysis (EDA): Detecting trends, patterns, and anomalies.

Case Studies & Projects: Comprehensive problem-solving with business datasets

Prerequisites for Data Analytics Course:

Our Data Analytics course is designed to be beginner-friendly, so no prior technical experience is required. However, having the following basic skills or understanding will help you grasp the concepts more easily:

Recommended Prerequisites:

Basic Computer Skills: Comfort with using spreadsheets, browsing, and file handling.
Analytical Thinking: A curiosity for problem-solving and logical reasoning.
Mathematics Foundation: Basic understanding of statistics, percentages, and averages.
Communication Skills: Ability to interpret and explain findings clearly.

Who Can Join Without Prior Experience?

Absolutely anyone with an interest in data and a willingness to learn!

Our trainers at Crystalspiders Institute start from the fundamentals and provide step-by-step guidance, making sure every learner — regardless of background — builds confidence in data analytics.

After completing the Data Analytics Course at Crystalspiders Institute, you’ll be equipped with the technical, analytical, and business skills needed to build a successful career in one of the fastest-growing industries today.

Data Analytics professionals are in high demand across all sectors — from IT, Finance, and Retail to Healthcare, E-commerce, and Consulting. Organizations are actively seeking data-driven talent to help them make smarter business decisions.

Popular Career Paths You Can Explore:

Data Analyst – Analyze business data, prepare dashboards, and provide actionable insights.
Business Analyst – Bridge the gap between data and business strategy.
Data Visualization Specialist – Design and develop interactive dashboards using Power BI or Tableau.
Data Engineer – Manage, clean, and prepare data pipelines for analysis.
Marketing Analyst – Use analytics to understand consumer behavior and improve marketing campaigns.
Financial Analyst – Perform data-based financial modeling, forecasting, and reporting.
Operations Analyst – Optimize business operations using data-driven approaches.

Module 1: Getting Started with Data Analysis

Understand and define data analysis and data analyst
Discovering data analyst
Organizational roles in data
Understanding types of data job roles
Discovering skills of the data analyst

Module 2: Fundamentals of data understanding - Work with databases

Learning to identify data
Learning about data fields and types
Dealing with the data that you don't have
Learning SQL syntax and basic SQL statements - DDL and DML commands
Challenges and Solutions while Reading data from databases

Module 3: Key Elements to Understand when Starting Data Analysis

Learn to interpret existing data
Finding existing data sets
Cleaning data
Understand data and flow
Understanding combine, joins and merge data sets
Work with joins in SQL and validation of data
Challenges and Solution where products are not categorized

Module 4: Getting Started with a Data Project

Getting started with data projects
Discovering common beginner mistakes
Learning Excel datasets
Learning Database datasets
Maintain the original data and understanding truths about data

Module 5: Data Importing, Exporting and Connections

Learning about data governance
Understanding Source data
Working with flat files
Working with connections
Creating datasets for others

Module 6: Getting Started with Data Cleaning and Modeling

Understanding ELT in data
Cleaning data by using Excel macros
Cleaning data with Power Query
Working with reusable data
Modeling data with queries
Modeling data in Power Query
Challenges and solutions in Rename headers in Power Query

Module 7: Applying Common Techniques for All Data Analysts

Convert data in Power Query
Finding and removing duplicates
Changing case and replace values
Combining data with merge columns
Creating logical functions
Building aggregate datasets
Challenges and Solutions in count and amounts of products

Module 8: Working with Business Data

Understanding Business Rules
Understanding noise in data
Breaking down the ask
Challenges and Solutions

Module 9: Building Data Sets with Queries

Understanding Queries
Building basic SELECT queries
Building DISTINCT queries
Building SQL queries with Joins
Building SQL queries by using various SQL functions
Building SQL queries with Aggregated functions
Understand the ORDER BY clause

Module 10: Chart Data Anytime and Anywhere

Ad hoc reporting
Building basic charts visual
Visuals using conditional formatting
Setting templates and default charts
Linking verus embedding chats and data
Challenges in Ad hoc presentation

Module 11: Pivot Data Anytime and Anywhere

What are the pivots?
Build basic pivot tables
Modifying pivots for readability
Visualizing pivot tables
Using pivots to filter data sets

Module 12: Building in Power BI Desktop

Building a dashboards
Building a matrix and visuals
Use cards for numbers
Using visuals in Power BI for filters
Publishing visuals and data sets
Challenges and Solutions in developing Product dashboard

Module 13: Power Query Tips and Tricks for Data Analysts

Using column profile to learn the data
Appending data by leveraging folders
Duplicate and reference data sets
Unpivoting data from existing reports
Custom sorting in Power BI
Challenges and Solutions in Custom Sort

Module 14: Get Data - Power BI

Power BI Data sources
Load data into Power BI Desktop
Save files for use in Power BI
Create a new data set
Upload a Power BI Desktop file

Module 15: Create a Report with Visualizations

Overview of Visualizations
Work with visualizations in a repot
Create a new report
Create and arrange visualizations
Save and format a visualization
Create chart visualizations
Use text and map visualizations
Create a Guage visualization
Use a slicer to filter visualizations
Sort, copy and paste visualizations
Download and use a custom visual from the gallery

Module 16: Create a Dashboard

Create a dashboard and pin a title
Pin a live report page to a dashboard
Add standalone tile to a dashboard
Edit a dashboard
Create a mobile view
Add a comment or alert to a tile
Subscribe to a dashboard
Set a featured dashboard
Use Lineage view

Module 17: Share Data with Colleagues and Others

Overview: Sharing reports and dashboards
Publish a report to a website or portal
Embed a report in SharePoint online
Add a Power BI report tab to Microsoft teams
Share a dashboard or report

Module 18: Use Power BI Desktop to Model Data

Install and launch Power BI Desktop
Get data, use views, reduce data and Transform data
Tweak your dataset for Q&A
Relate tables

Module 16: Modify and print a report

Manage report page
Add a filter to a page
Add a filter to a report
Set visualizations interactions
Print a report or report page
Export slides to PowerPoint
Data Storytelling in PowerPoint

Module 17: Introduction of Python

From data to insight with Python
What we need to know
Set up: Using Codespaces

Module 18: Python Data Structures

Warmup with Python loops
Tuples, Lists, and the slicing syntax
Dictionaries and sets
Comprehensions
Data Classes
Various programs to practice List, Set, WHILE and FOR loops

Module 19: Project: Finding Anagrams

Overview: Finding anagrams
Loading dictionaries from text files
Finding anagrams

Module 20: NumPy

NumPy overview
Creating NumPy arrays
Indexing NumPy arrays
Doing math with NumPy arrays
Special arrays: Record and dates

Module 21: Pandas

Pandas overview
Pandas Data Frames and Series
Indexing in pandas
Math and plotting in pandas
Database operations in pandas
Understand challenges in Temperature anomaly

Module 22: Importing and Wrangling Data with pandas

Overview: The structure of data
Importing data with pandas
Cleaning data
Filtering, reshaping, and tidying data
Simulating data

Module 23: Summerizing and visualizing data

Overview: Exploring data
Summarizing quantitative data
Visualizing distributions
Comparing quantitative variables
Summarizing and visualizing categorical data

Module 24: Introduction to Data Modeling

Overview: Understanding data
Fitting models to data
Model evaluation and selection
Testing hypotheses with monte Carlo
Understand the Gapminder model fit

Module 25: Projects

COVID-19:

Overview: COVID-19 data
Summarizing COVID-19 data
Visualizing COVID-19 data
Modeling COVID-19 data

Weather Data:

Overview: Analyzing weather
Loading station and temperature data
Cleaning weather data
Smoothing and plotting time series
Weather carts
Understand challenges in Temperature anomaly

Baby Names:

Overview: Analyzing baby names
Loading name datasets
Comparing name popularity
Compiling top tens
Challenges with unisex names

Module 26: Understand the SQL

Quick review of SQL
RDBMS
Common SQL structures

Module 27: Using Data Types

Using data types and identifying the wrong data types
Understand and find the missing values
Finding possible inaccurate data values

Module 28: Working with Data Sets

Manipulate the data (INSERT, UPDATE and DELETE)
Key Constraints
Relationships among the tables
Combine the data sets - UNION, UNION ALL, INTERSECT, EXCEPT
Join the data sets - INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN, CROSS JOIN

Module 29: SQL Functions

Understand and practice String Functions

SUBSTRING(), UPPER(), LOWER(), REPLACE()

Understand and practice Date Functions

GETDATE(), DATEADD(), DATEDIFF(), DATENAME(), DAY(), MONTH(), YEAR()

Understand and practice NULL Functions

ISNULL(), and COALESCE()

Understand and practice Aggregate Functions

SUM(), MIN(), MAX(), COUNT() and AVG()

Understand and practice analytical functions

RANK(), DENSE_RAN(), ROWNUMBER()

Module 30: Sub Queries and Programming Object's

Write sub-queries for various requirements
Understand the Views and Functions in SQL
Create and execute the Stored Procedures

Crystalspiders Institute

Master Data Analytics with Hands-On Training — Online & Offline