Professional Data Analytics Bootcamp

  • High Demand In Business And It: Data analytics is in demand because companies need professionals who can analyze data, create reports, build dashboards, and support decision-making.
  • Useful For Multiple Backgrounds: Data analytics is suitable for learners from commerce, management, computer science, and non-technical backgrounds because it focuses on practical data understanding.
  • Build Decision-making Skills: Learners understand how to convert raw data into meaningful insights, dashboards, visual reports, and business recommendations.
2 Months ₹18,999 ₹14,999
Enroll Now

Join 990+ students who have already benefited from this course.

Professional Data Analytics Bootcamp
Limited Seats Available

Upgrade Your Skills
With Industry Ready Courses

Enroll Now

Fast onboarding • Secure • AI-powered experience
Enrollment submitted successfully.

Enrollment Successful 🎉


Course Overview

Data Analytics is the process of collecting, cleaning, analyzing, visualizing, and interpreting data to support better business decisions. This 2 months course helps learners build practical analytics skills using Excel, SQL, Python, statistics, data cleaning, Power BI, dashboard development, KPI reporting, business intelligence basics, and real-world analytics project development.

Course with Live Project

No Refund Available

business data analysis tools: learners work with excel, sql, python, pandas, numpy, statistics, and power bi to analyze and understand business data.

dashboard and kpi reporting: the course focuses on excel dashboards, power bi reports, kpi cards, charts, slicers, filters, and business performance reporting.

Practical Analytics Project Development: Develop Projects Like Gym Membership Analytics, Social Media Analytics Dashboards, Sales Reports, Customer Analysis, And Business Kpi Dashboards.

Course Content

  • • understanding data analytics fundamentals
  • • exploring types of data analytics
  • • learning data analytics lifecycle
  • • understanding data-driven decisions
  • • exploring real-world analytics applications
  • • understanding business problem solving
  • • setting up analytics environment
  • • learning analytics career opportunities

  • • understanding excel interface and tools
  • • cleaning and formatting business data
  • • using formulas for data analysis
  • • working with logical excel functions
  • • using vlookup and xlookup functions
  • • creating pivot tables and charts
  • • applying conditional formatting techniques
  • • building interactive excel dashboards
  • • tracking kpis through reports
  • • creating business performance reports

  • • understanding database management concepts
  • • writing sql query statements
  • • filtering and sorting database records
  • • using aggregate functions efficiently
  • • working with group by queries
  • • understanding sql joins and relationships
  • • using subqueries for data analysis
  • • working with window functions
  • • creating reports from database data
  • • solving business problems using sql

  • • learning python programming fundamentals
  • • understanding variables and data types
  • • working with conditional statements logic
  • • using loops for data processing
  • • creating functions and reusable modules
  • • managing data with python collections
  • • understanding file handling concepts
  • • exploring python libraries for analytics

  • • understanding numpy for data operations
  • • working with arrays and calculations
  • • learning pandas for data analysis
  • • managing data using dataframes
  • • reading csv and excel files
  • • cleaning and preparing datasets
  • • handling missing data efficiently
  • • transforming data for better analysis
  • • performing exploratory data analysis
  • • generating data insights efficiently

  • • understanding mean, median, and mode
  • • learning variance and standard deviation
  • • exploring probability and data patterns
  • • understanding correlation between variables
  • • identifying trends and outliers
  • • applying statistics in data analysis
  • • understanding forecasting basics

  • • understanding data visualization concepts
  • • creating charts for data analysis
  • • working with matplotlib and seaborn
  • • building interactive business dashboards
  • • understanding kpi and metrics tracking
  • • presenting insights through visual stories
  • • designing professional dashboard layouts

  • • understanding power bi fundamentals
  • • importing and cleaning business data
  • • creating interactive reports and dashboards
  • • working with power query editor
  • • understanding data modeling concepts
  • • creating kpi performance dashboards
  • • building business intelligence reports
  • • sharing reports across teams

  • • understanding business reporting workflow
  • • analyzing customer behavior patterns
  • • exploring sales and revenue analysis
  • • creating business performance reports
  • • understanding predictive analytics basics
  • • solving real-world data problems

  • • assignments
  • • business data reporting task
  • • dashboard visualization exercise
  • • kpi tracking analysis
  • • excel advanced functions task

  • • hospital analytics system
  • • retail chain kpi dashboard
  • • hr performance analytics platform

Skills Developed with Data Analytics Course

Excel Analytics: Learn excel formulas, logical functions, lookup functions, pivot tables, charts, conditional formatting, and dashboard creation.
Sql For Reporting: Work with sql queries, filtering, sorting, aggregate functions, group by, joins, subqueries basics, and business reports.
Python For Analytics: Learn python fundamentals, data types, conditions, loops, functions, file handling, and basic automation for analytics tasks.
Pandas And Numpy: Practice dataframe handling, csv files, filtering, sorting, missing value handling, grouping, merging, and data transformation.
Statistics For Analytics: Understand mean, median, mode, variance, standard deviation, probability, correlation, trend analysis, and forecasting basics.
Data Cleaning: Work with missing values, duplicate records, incorrect formats, inconsistent data, outliers, and clean dataset preparation.
Data Visualization: Create charts, graphs, line plots, bar charts, pie charts, heatmaps, dashboards, and visual business reports.
Power Bi Dashboard Development: Learn data import, power query basics, data modeling basics, kpi cards, slicers, filters, visuals, and report creation.
Business Reporting: Prepare sales reports, customer reports, kpi summaries, performance dashboards, and business insight documents.
Analytics Project Skills: Practice cleaning data, analyzing datasets, creating dashboards, generating insights, documenting findings, and presenting reports.

Career Opportunities after Data Analytics Course

This course opens doors to multiple high-demand career paths across industries.

Data Analyst Intern:

Support analytics teams by cleaning data, preparing reports, creating dashboards, and generating business insights.

Business Reporting Assistant:

Prepare excel reports, kpi summaries, business dashboards, and performance tracking documents.

Power Bi Beginner Role:

Create power bi dashboards, visuals, kpi cards, slicers, and interactive business reports.

Sql Data Assistant:

Work with databases, write queries, extract business data, and prepare structured reports for analysis.

Excel Analytics Assistant:

Use excel formulas, charts, pivot tables, dashboards, and reports to analyze and present business data.

Why Enroll in Data Analytics with Solitaire Learning?

Beginner-friendly Analytics Training: The course starts from excel, sql, statistics, and data basics, making it suitable for learners from different backgrounds.
Practical Dashboard-based Learning: Learners work on real-world tasks like sales dashboards, kpi reports, customer analysis, social media analytics, and business summaries.
Industry-relevant Tools: The course covers excel, sql, python basics, pandas, numpy, power bi, charts, dashboards, and reporting tools.
Mentor-guided Project Support: Learners receive mentor support for concept clarity, assignments, dashboard creation, report building, and project development.
Strong Foundation For Advanced Analytics Learning: The course prepares learners for 3 months, 4 months, and 6 months advanced data analytics programs.
Frequently Asked Questions

Have Questions About This Course?

Find answers to the most common questions learners ask before enrolling.

No, beginners can also join the training program without prior coding knowledge. Concepts are taught step-by-step from basics.

Basic analytical thinking and simple statistics understanding are sufficient for learning Data Analytics. Advanced mathematics is not compulsory for beginners.

Yes, students from any educational background or stream can learn Data Analytics. The course is designed for both technical and non-technical learners.

A laptop with minimum 8GB RAM, i3/i5 processor, and stable internet connection is recommended for smooth practical work and dashboard development.

No, Excel basics are covered during the training program. Students gradually learn advanced formulas, reporting, and dashboard techniques.

Data Analytics is the process of collecting, analyzing, and interpreting data to identify patterns, generate reports, and support better business decisions. It helps organizations improve performance and understand customer behavior.

Students learn Excel, SQL, Python, Power BI, statistics, dashboard development, KPI reporting, and business reporting techniques. The course focuses on both analytical concepts and practical implementation.

Yes, students learn dashboard creation, data visualization, report publishing, and KPI tracking using Power BI. Practical business dashboard projects are also included.

Yes, SQL is covered from basic to advanced level with practical query exercises and reporting tasks. Students learn database handling and data extraction techniques.

Yes, students work with real-world business datasets and reporting scenarios. This helps learners understand practical analytics workflows and business problem-solving.

Yes, students create analytics dashboards, business reports, KPI dashboards, and visualization projects using Excel and Power BI. These projects help build strong portfolios.

Yes, Python is included for automation, data analysis, and advanced analytics tasks. Students learn libraries like Pandas, NumPy, and Matplotlib for data processing.

Yes, every module contains assignments, dashboard tasks, SQL exercises, and reporting activities. Regular practice helps improve analytical and reporting skills.

Yes, Data Analytics is a highly in-demand field with opportunities in business intelligence, reporting, marketing analytics, and data-driven decision-making roles.

Yes, students receive project guidance, portfolio support, and certification after successful completion of the training. Career guidance and interview preparation are also included.
Course FAQ

Ready to Take the Next Step in Your Career?

Join our expert-led training program, gain industry-recognized skills, and move closer to your professional goals. Seats are limited — enroll today!

Recommended Courses for You

DesignX Web

Duration: 2 Months
Fees:
14,999
View Course

Java Hands-On Bootcamp

Duration: 2 Months
Fees:
14,999
View Course

JavaScript Professional Program

Duration: 2 Months
Fees:
14,999
View Course

Advanced React Engineering Program

Duration: 2 Months
Fees:
14,999
View Course
👉 Search courses here!!