Certified Data Analytics Expert

  • Every Business Needs Data Analysts: Companies need analytics professionals to understand sales, customers, operations, finance, marketing, and performance trends.
  • Learn In-demand Analytics Tools: Learners gain hands-on skills in excel, sql, python, and power bi, which are widely used in analytics and reporting roles.
  • Build Decision-making Skills: The course helps learners convert raw data into meaningful reports, dashboards, and actionable business insights.
6 Months ₹45,999 ₹35,999
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Certified Data Analytics Expert
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Course Overview

The Business Analyst Mastery Program is designed to help students and professionals understand how businesses use data to make smart decisions. This course equips you with the skills to analyze business problems, gather requirements, and deliver data-driven solutions. You will gain hands-on experience with tools like Excel, SQL, Power BI, and visualization platforms while learning key concepts of business analysis, reporting, and stakeholder communication. Through real-world case studies and practical exercises, you will learn how to identify trends, create dashboards, and support business growth with data insights.

Course with Live Project

No Refund Available

Business Data Analysis Tools: Learners Work With Excel, Sql, Python, Pandas, Numpy, Matplotlib, Seaborn, Power Bi, And Dax Basics For Practical Analytics Tasks.

Dashboard And Report Building: The Course Focuses On Excel Dashboards, Power Bi Reports, Kpi Tracking, Business Reporting, And Data Visualization.

Real Business Dataset Practice: Learners Analyze Sales, Hr, Finance, Retail, E-commerce, Customer Behavior, And Business Performance Datasets.

Course Content

  • • Understanding data analytics concepts deeply
  • • Types of data analytics explained clearly
  • • Data analytics lifecycle overview
  • • Business intelligence fundamentals introduction
  • • Data driven decision making concepts
  • • Understanding kpis and business metrics
  • • Real-world analytics use cases
  • • Setting up analytics tools environment

  • • Excel interface and data handling basics
  • • Data cleaning and formatting techniques
  • • Logical functions and conditional formulas
  • • Vlookup and xlookup applications
  • • Pivot tables and pivot charts mastery
  • • Advanced excel formulas usage
  • • Data filtering and sorting techniques
  • • Interactive dashboard creation in excel
  • • Kpi tracking and reporting systems
  • • Business report generation in excel

  • • Sql database fundamentals overview
  • • Writing basic to advanced queries
  • • Data filtering and aggregation techniques
  • • Group by and having clauses usage
  • • Joins and relationships in databases
  • • Subqueries for analytical problems
  • • Window functions for advanced analysis
  • • Creating business reports using sql
  • • Query optimization basics
  • • Real-world sql problem solving

  • • Python programming fundamentals review
  • • Data structures for analytics work
  • • Functions and modular programming
  • • File handling for data processing
  • • Error handling techniques
  • • Using python for data tasks
  • • Writing efficient analytical scripts
  • • Automating data tasks using python

  • • Numpy arrays and operations
  • • Pandas dataframe handling
  • • Data cleaning and preparation
  • • Handling missing values effectively
  • • Data transformation techniques
  • • Merging and joining datasets
  • • Exploratory data analysis (eda)
  • • Extracting business insights from data
  • • Working with real business datasets

  • • Mean median mode analysis
  • • Variance and standard deviation concepts
  • • Probability for business decisions
  • • Correlation and relationship analysis
  • • Data distribution understanding
  • • Statistical interpretation of data
  • • Trend analysis techniques
  • • Forecasting basics for analytics

  • • Data visualization principles overview
  • • Matplotlib visualization library usage
  • • Seaborn statistical plotting techniques
  • • Bar line and pie chart creation
  • • Heatmaps and correlation analysis
  • • Dashboard design principles
  • • Data storytelling techniques
  • • Business insight presentation skills

  • • Power bi interface and workflow
  • • Data import and transformation
  • • Power query editor usage
  • • Data modeling in power bi
  • • Dax functions for analysis
  • • Kpi dashboard creation
  • • Interactive report building
  • • Publishing and sharing reports
  • • Business intelligence dashboard design

  • • Understanding business kpis
  • • Sales and revenue analysis
  • • Customer behavior analysis
  • • Marketing performance tracking
  • • Financial data reporting
  • • Performance metrics evaluation
  • • Business insight generation
  • • Decision making using data

  • • Predictive analytics introduction
  • • Regression basics for forecasting
  • • Trend analysis and forecasting
  • • Customer segmentation concepts
  • • Business optimization techniques
  • • Advanced reporting methods
  • • Data driven strategy building
  • • Analytics automation concepts

  • • Executive dashboard development
  • • Enterprise reporting system design
  • • Large dataset analytics task
  • • Advanced kpi framework design
  • • Predictive analytics exercise
  • • Data storytelling presentation
  • • Multi-source data integration
  • • Industry analytics case study
  • • Enterprise sales intelligence dashboard
  • • Fintech analytics platform
  • • Supply chain analytics system
  • • Executive business intelligence dashboard

  • • Enterprise sales intelligence dashboard
  • • Fintech analytics platform
  • • Supply chain analytics system
  • • Executive business intelligence dashboard

Skills Developed with Data Analytics Course

Excel Analytics: Learn advanced excel formulas, logical functions, lookup functions, pivot tables, charts, dashboards, and kpi reports.
Sql Reporting: Work with sql queries, filtering, sorting, aggregation, joins, subqueries, window functions, and analytical reports.
Python For Analytics: Learn python fundamentals, data structures, functions, file handling, and automation for analytics tasks.
Pandas And Numpy: Practice data cleaning, dataframe handling, missing value treatment, transformation, merging, and exploratory analysis.
Statistics For Analytics: Understand mean, median, mode, variance, standard deviation, probability, correlation, trends, and forecasting basics.
Data Visualization: Create charts, graphs, heatmaps, visual stories, dashboard layouts, and professional data reports.
Power Bi: Work with data import, power query, data modeling, dax basics, kpi dashboards, interactive reports, and report publishing.
Business Intelligence: Analyze business performance, customer behavior, sales, revenue, and kpi-based reporting.
Predictive Analytics Basics: Learn forecasting, regression basics, future trend analysis, and data-driven business predictions.
Analytics Project Development: Practice data cleaning, analysis, dashboard building, insight generation, and business recommendation presentation.

Career Opportunities after Data Analytics Course

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

Data Analyst:

Clean, analyze, visualize, and report data to help organizations make better business decisions.

Business Intelligence Analyst:

Build dashboards, reports, and kpi systems using tools like power bi, sql, and excel.

Reporting Analyst:

Prepare business reports, performance summaries, and data-driven insights for management teams.

Power Bi Developer:

Create interactive dashboards, data models, dax calculations, and business intelligence reports.

Sql Data Analyst:

Work with databases, write queries, extract insights, and generate structured business reports.

Why Enroll in Data Analytics with Solitaire Learning?

Tool-based Practical Learning: The course includes excel, sql, python, and power bi with hands-on tasks and dashboard development.
Real Business Case Practice: Learners work on sales, finance, hr, retail, e-commerce, and customer analytics datasets.
Dashboard And Reporting Focus: The course helps learners build portfolio-ready dashboards and reports for job interviews.
Beginner-friendly Curriculum: Learners can start from basics and gradually move toward advanced analytics and business intelligence concepts.
Career-oriented Mentor Guidance: Learners receive mentor support for assignments, projects, interview preparation, and portfolio building for data analyst roles.
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

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