Upgrade your career with the Data Analytics Training in Chennai at Softlogic Systems. Our Data Analytics Syllabus covers the data analytics fundamentals, statistical analysis, data visualization, SQL, Excel, Python for analytics, and business intelligence tools. Our Data Analytics course in Chennai comes with placement support, flexible schedules, real-time projects, and certification to help you successfully launch your career. Our placement team connects you with top IT companies for a smooth career transition.
Data Analytics Training In Chennai
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DURATION
2 Months
EMI
0% Interest
Mode
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Course Syllabus
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Fees, Duration & Batch Timings for Data Analytics Course
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2026
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
Course Fee
July 2026
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
Course Fee
Save up to 20% in your Course Fee on our Job Seeker Course Series
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Syllabus of Data Analytics Course
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CORE PYTHON
- Python Introduction & history
- Color coding schemes
- Salient features & flavors
- Application types
- Language components
- String handling management
- String operations – indexing, slicing, ranging
- String methods – concatenation, repetition, formatting
- Supporting functions
- Native data types
- List
- Tuple
- Set
- Dictionary
- Decision making statements
- If
- If…else
- If…elif…else
- Looping statements
- For loop
- While loop
- Function types
- Built-in functions
- Math functions
- User defined functions
- Recursive functions
- Lambda functions
- OOPs
- Classes and objects
- init constructor
- Self-keyword
- Data abstraction
- Data encapsulation
- Polymorphism
- Inheritance
- Exception handling
- Error vs exception
- Types of error
- User defined exception handling
- Exception handler components
- Try block, except block, finally block
POWER BI INTRODUCTION
- Data Visualization
- Reporting Business Intelligence (BI)
- Traditional BI
- Self-Serviced BI Cloud Based BI
- On Premise BI
- Power BI Products
- Power BI Desktop (Power Query, Power Pivot, Power View)
- Flow of Work in Power BI Desktop
- Power BI Report Server
- Power BI Service, Power BI Mobile
- Power BI Architecture
- A Brief History of Power BI
POWER QUERY
- Data Transformation
- Benefits of Data Transformation
- Shape or Transform Data using Power Query
- Overview of Power Query / Query Editor
- Query Editor User Interface
- The Ribbon (Home, Transform, Add Column, View Tabs)
- The Queries Pane
- The Data View / Results Pane
- The Query Settings Pane, Formula
- Bar Saving the Work
- Data types
- Changing the Data type of a Column Filters in Power Query
- Auto Filter / Basic Filtering Filter a Column using
- Text Filters Filter a Column using Number Filters
- Filter a Column using Date Filters Filter Multiple Columns
- Remove Columns / Remove Other Columns Name
- Rename a Column Reorder Columns or Sort Columns
- Add Column / Custom Column Split Columns Merge
- Columns PIVOT, UNPIVOT Columns Transpose Columns
- Header Row or Use First Row as Headers Keep Top Rows
- Keep Bottom Rows Keep Range of Rows Keep Duplicates
- Keep Errors Remove Top Rows
- Remove Bottom Rows
- Remove Alternative Rows
- Remove Duplicates, Remove Blank Rows
- Remove Errors Group Rows / Group By
M LANGUAGE
- IF..ELSE Conditions
- TransformColumn()
- RemoveColumns()
- SplitColumns()
- ReplaceValue()
- Table.Distinct() Options and GROUP BY Options
- Table.Group()
- Table.Sort() with Type Conversions
- PIVOT Operation and Table.Pivot ().
- List Functions Using Parameters with M Language
DATA MODELING
- Data Modeling Introduction Relationship
- Need of Relationship Relationship Types
- Cardinality in General
- One-to-One
- One-to-Many
- Many-to-One
- Many-to-Many
- AutoDetect the relationship
- Create a new relationship
- Edit existing relationships
- Make Relationship Active or Inactive
- Delete a relationship
DAX
- What is DAX
- Calculated Column, Measures
- DAX Table and Column Name Syntax
- Creating Calculated Columns
- Creating Measures
- Calculated Columns Vs Measures
- DAX Syntax & Operators
- Types of Operators
- Arithmetic Operators
- Comparison Operators
- Text Concatenation Operator
- Logical Operators
DAX FUNCTIONS TYPES
- Date and Time Functions
- YEAR, MONTH,DAY
- WEEKDAY, WEEKNUM FORMAT (Text Function)
- Month Name, Weekday Name
- IF
- TRUE, FALSE NOT,
- OR, IN, AND
- Text Function
- LEN, CONCATENATE
- LEFT, RIGHT, MID UPPER
- LOWER TRIM, SUBSTITUTE, BLANK
- Logical Functions
- IF TRUE, FALSE NOT
- OR, IN, AND IF ERROR SWITCH
- Math & Statistical Functions
- INT ROUND, ROUNDUP
- ROUNDDOWN
- DIVIDE EVEN, ODD
- POWER, SIGN SQRT
- FACT SUM, SUMX MIN, MINX MAX
- MAXX COUNT,
- COUNTX AVERAGE
- AVERAGEX COUNTROWS
- COUNTBLANK
REPORT VIEW
- Report View User Interface
- Fields Pane
- Visualizations pane
- Ribbon, Views, Pages Tab
- Canvas Visual Interactions Interaction Type (Filter, Highlight, None)
- Visual Interactions Default Behavior, Changing the Interaction
- Grouping and Binning Introduction
- Using grouping, Creating Groups on Text Columns
- Using binning, Creating Bins on Number Column and Date Columns
- Sorting Data in Visuals
- Changing the Sort Column
- Changing the Sort Order
- Sort using column that is not used in the Visualization
- Sort using the Sort by Column button
- Hierarchy Introduction
- Default Date Hierarchy
- Creating Hierarchy
- Creating Custom Date Hierarchy
- REPORT VIEW
- Change Hierarchy Levels
- Drill-Up and Drill-Down Reports
- Data Actions, Drill Down, Drill Up, Show Next Level
- Expand Next Level Drilling filters other visuals option
VISUALIZATIONS
- Visualizing Data
- Why Visualizations
- Visualization types
- Create and Format Bar and Column Charts
- Create and Format Stacked Bar Chart
- Stacked Column Chart
- Create and Format Clustered Bar Chart
- Clustered Column Chart
- Create and Format 100% Stacked Bar Chart 100% Stacked Column Chart
- Create and Format Pie and Donut Charts
- Create and Format Scatter Charts
- Create and Format Table Visual
- Matrix Visualization
- Line and Area Charts
- Create and Format Line Chart, Area Chart
- Stacked Area Chart Combo Charts
- VISUALIZATIONS
- Create and Format Line and Stacked Column Chart
- Line and Clustered Column Chart
- Create and Format Ribbon Chart
- Waterfall Chart, Funnel Chart
POWER BI SERVICE
- Power BI Service Introduction
- Power BI Cloud Architecture
- Creating Power BI Service Account
- SIGN IN to Power BI Service Account
- Publishing Reports to the Power BI service
- Import / Getting the Report to PBI Service
- My Workspace / App Workspaces Tabs
- DATASETS, WORKBOOKS, REPORTS & DASHBOARDS
- Working with Datasets Creating Reports in Cloud using Published
- Datasets
- Creating Dashboards Pin Visuals and Pin LIVE
- Report Pages to Dashboard
- Advantages of Dashboards Interacting with
- Dashboards
- Formatting Dashboard, Sharing Dashboard
ADVANCED PANDAS FUNCTIONS
- Group by()
- Pivot tables()
- Multi-indexing()
- merge()
- concatenate()
- join()
- data transformation using apply()
- map()
- query()
- Resampling time series functionality
- excel writer()
- pipe()
- creating dataframes
- reading CSV files with intrinsic index
- converting CSV files to dataframes
- converting dataframes to CSV files
- converting dataframes to excel file
ADVANCED SQL FUNCTIONS
- Common Table Expressions (CTE)
- Recursive CTE’s
- temporary functions
- pivoting data with sum() and CASE WHEN
- Except vs Not in
- self joins, rank vs dense_rank vs row number
- ranking data
- calculating delta values,
- multiple groupings using rollup
- calculating running totals
- computing a moving average
- date time manipulations
- Formatting strings, stored methods
- JOINS
- Sub Queries
- Manipulation of date and time
- procedural data storage
- Connecting SQL to Python or R language, window Functions
PROJECT
- Project1 – Product Sales Analysis – Power BI Project and review
- Project2 – Financial Performance Analysis – Power BI Project and review
- Project3 – Health care sales Analysis –
- Intermediate Power BI project and review
- Project4 – Anamoly detection in Credit card transactions – Intermediate Power BI project and review
Objectives of Data Analytics Training
The main objective of the Data Analytics course is to make students fully well-versed on the subject of Data Analytics. Students will get the opportunity to learn from the newly updated Data Analytics syllabus where they will learn interesting topics like: Hadoop ecosystem, HiveQL, AzureML and more.
By the time students complete this course they will be knowledgeable on the following:
- Querying Data with Hive
- Big Data & Machine Learning
- Handling files in Hadoop
Why Softlogic Systems is the Best Choice for Data Analytics Training – Learn, Practice, and Get Placed!
Online & Offline Training Options
Learn at your convenience with flexible classroom and live online training.
Learn from 100+ Real-Time Developers
Get trained by industry professionals with years of hands-on experience.
Hands-on Projects & Codeathons
Practice with real-time projects and coding challenges to build confidence.
0% EMI Fee Options
Pay your course fees flexibly with easy EMI plans at zero interest.
Resume & Interview Support
Get expert help with resume building, mock interviews, and soft skills.
Placement with Top IT Firms
Access placement opportunities with leading MNCs and IT companies.
1000+ Hiring Partners
Benefit from Softlogic’s strong recruiter network for faster job placement.
No Backdoor Jobs
We ensure only genuine placement opportunities with trusted companies.
Want to Speak to a Trainer about Data Analytics?Request a Free Callback
Highlights of Data Analytics Course
What is Data Analytics?
Data analytics transforms unprocessed data into practical insights. It encompasses an array of tools, technologies, and methodologies employed to uncover patterns and address issues through data utilization. Data analytics has the power to mold operational procedures, enhance informed choices, and cultivate the expansion of enterprises.
What are the reasons to learn Data Analytics?
There are several compelling reasons to learn data analytics:
- Career Opportunities: Embark on a data-driven journey, unraveling mysteries and ascending the ladder of professional success.
- Evolving Job Market: Enter the data analytics education time capsule and secure your perpetual relevance in a job market that constantly shifts and transforms.
- Informed Decision-Making: Tap into the potential of data analytics to make decisions as precise as a fortune teller and as confident as an experienced strategist.
- Problem-Solving: Excel in the skill of transforming data into solutions and proudly don the mantle of a digital hero, saving companies from the turmoil of data complexity.
What are the prerequisites to learn Data Analytics?
While there are no prerequisites for learning Data Analytics at our Data Analytics Training in Chennai it is highly advantageous to have a foundational knowledge in Statistics and Programming languages.
Data Analytics Training is typically suitable for individuals from various backgrounds who possess an interest in data and aspire to learn data analytics as a skill set.
- Students
- Professionals switching careers
- IT professionals who want to advance their skills
- Job Hunters
What are the course fees and duration?
The fees for our Data Analyst Course may vary depending on the program level (basic, intermediate, or advanced) and the course format (online or in-person). On average, Data Analytics Certification Course Fees are affordable and lasts for 2 Months including international certification. For precise and up-to-date information on fees, duration, and certification, please contact our Business Analytics Course directly.
What are the Jobs related to Data Analytics?
Certainly, here are a few job positions associated with data analytics:
- Data Analyst
- Business Analyst
- Market Research Analyst
- Business Intelligence Analyst
- Marketing Analyst
- Web Analyst
- Social Media Analyst
List a few Data Analytics based real-time applications?
Certainly, here are a few examples of real-time applications that leverage data analytics:
- E-commerce Platforms (e.g., Amazon, eBay)
- Traffic Navigation Apps (e.g., Google Maps, Waze)
- Streaming Platforms (e.g., Netflix, Spotify)
- Emergency Response Systems (e.g., 911 services)
- Healthcare Monitoring Devices (e.g., Apple Ride-Sharing Apps (e.g., Uber, Lyft)Watch, Garmin)
- Energy Management Systems (e.g., Schneider Electric, Siemens)
What is the salary range for the position of Data Analyst?
As per data from AmbitionBox, the Data Analyst freshers salary typically with less than 2 years of experience earn approximately ₹3-5 lakhs annually. For mid-career Data Analysts with around 3 years of experience, the average annual salary is around ₹6 lakhs. An experienced Data Analyst with more than 5 years of experience can anticipate an average yearly salary of around ₹8.3 lakhs.
Boost Your Skills with Our Data Analytics Training Experts
Our Mentors are from Top Companies like:
- Our Data Analytics trainers are highly trained professionals in the field of analytics, with deep technical knowledge and expertise.
- They have vast experience in managing and implementing data-driven solutions.
- They create comprehensive study materials to help learners learn the fundamentals of data analytics and understand the available possibilities in different analytical domains.
- Our trainers have a thorough understanding of data analytics certification, and train students on the concepts of data exploration, machine learning algorithms, fundamental concepts of Big Data and data visualization.
- They are highly proficient in preparing the students for the certification exams by engaging in teaching through real-life scenario based learning and mentoring.
- Our trainers exhibit great communication and interpersonal skills to ensure effective instruction and learning with students.
- They have the ability to deploy secure and powerful data solutions and configure servers in high-performance computing.
- They also have the ability to develop and deploy applications with the software development life cycle.
- Data Analytics trainers make use of analytics platforms and techniques to assess student performance and provide feedback to help them nurture their analytics skills.
- The trainers have a team oriented approach and enthusiasm towards helping students gain the required knowledge and get placed in their dream jobs easily.
Want to Speak to a Trainer about Data Analytics?Request a Free Callback
What Modes of Training are available for Data Analytics Course?
Offline / Classroom Training
A Personalized Learning Experience with Direct Trainer Engagement!
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Training
Instructor Led Live Training! Learn at the comfort of your home
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
Corporate Training
Blended Delivery model (both Online and Offline as per Clients’ requirement)
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
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Certifications
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Improve your abilities to get access to rewarding possibilities
Improve your abilities to get access to rewarding possibilities
Earn Your Certificate of Completion
Validate your achievements with Softlogic's Certificate of Completion, verifying successful fulfillment of all essential components.
Take Your Career to the Next Level with Certifications
Get a certifications through our training programs to gain a competitive edge in the industry.
Stand Out from the Crowd with Codethon Certificate
Verify the authenticity of your real-time projects with Softlogic's Codethon certificate.
Hands-on Project Practices in Data Analytics Course
Dynamic Pricing
Price Optimization
Sales Forecasting
Large-scale Recommendation Systems
Geospatial Data Analysis
Sensor Data Analytics
Market Analysis and Competitor Research
Network Traffic Optimization
Social Media Analytics
The SLA Way to Get Placed in Top IT Companies
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What can I learn from this Data Analytics Training?
Through this Data Analytics Training you will learn the fundamentals of data science, machine learning, and artificial intelligence, as well as the art of communication within the data-driven organization. Additionally, the course will cover topics such as data collection, distribution, and visualization.
What are the benefits of Data Analytics?
Data analytics allows businesses to identify trends and relationships in data that were previously hidden. By using this data to improve decision making, organizations can make better use of resources, optimize operations, gain a competitive edge, and increase revenues and profits.
What is the difference between Data Analytics and Data Science?
Data Analytics is the practice of extracting insights from data. Data Science is an interdisciplinary field that combines data engineering, computer science and analytics to solve complex issues. Data Science also uses algorithms to create predictions based on data.
What programming languages will I learn during this training?
During this training, you will learn to use R and Python for data analysis, machine learning, and artificial intelligence.
What is the intended audience for this training?
This training is intended for anyone who wants to gain practical knowledge in data analytics and harness it for business value. It is suitable for those who enter data science as well as experienced data analysts.
What levels of expertise will be taught during this training?
This training offers an overview suitable for all levels of expertise, from beginners to experts. You will explore the latest technologies and techniques used by the world’s leading data scientists.
Is this Data Analytics Training certified?
Yes, this Data Analytics Training is certified by IBM, and you will receive a certification upon successful completion of the course.
What makes Softlogic System a special training institute?
Softlogic System is a leading provider of data analytics training and certification. Our experienced team of trainers has deep expertise in the field, and offers cutting-edge and up-to-date knowledge.
What job prospects can I expect after completing this Data Analytics Training?
After completing this Data Analytics Training, you will be well positioned to apply for a range of data-related jobs within various industries. These include positions such as Data Scientist, Data Analyst, Business Intelligence Analyst, Machine Learning Engineer, and Artificial Intelligence Engineer.
Additional Information for
the Data Analytics Course
Types of Data Analytics and its Purpose
Before jumping into the Data Analytics Career, you must know what are the types of Data Analytics that are used to accomplish particular task with required skills. Generally, There are four types of Data Analytics as follows:
Descriptive Analytics: This is the major form of Data Analytics process to analyze “What is exactly happening in a business?”. This analysis produces the key measures such as comprehensive details and accurate prediction on live data with the utilization of an effective visualization tool to enhance the results.
Diagnostic Analytics: This form of analysis taken into account in the circumstance of “Why it is happening in a business?”. Diagnostic tools and Business Intelligence dashboards will allow an analyst to understand the root cause of a problem and isolate it for further actions by confounding the produced information.
Predictive Analytics: It is all about forecasting the happening in a business with the key factor of “What is likely to happen in a business?”. Business Strategies, Historical Pattern are used for this analytics to take decisions automatically using algorithms and technologies.
Prescriptive Analytics: This model utilizes to understand “What do a data analyst needs to do for a business?”. It is based on the recommended actions of strategic outcomes and applying advanced analytical techniques to make specific decisions.
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