Data Analytics Essentials

  • High Demand In The It And Business Industry: Data analytics is in demand because companies need professionals who can analyze data, create reports, and support business decisions.
  • Useful For Technical And Non-technical Learners: Data analytics is suitable for learners from commerce, management, computer science, and other backgrounds because it focuses on practical data understanding.
  • Build Decision-making Skills: Learners understand how to convert raw data into meaningful insights, dashboards, reports, and business recommendations.
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Course Overview

Data Analytics is the process of collecting, cleaning, analyzing, visualizing, and interpreting data to support better business decisions. This 1 month course helps learners build a strong foundation in Excel, SQL basics, Python basics, statistics, data cleaning, dashboard creation, KPI reporting, Power BI basics, and beginner-level analytics project development.

Course with Live Project

No Refund Available

business data analysis foundation: learners understand how to clean, organize, analyze, and interpret business data using excel, sql, python, and basic statistics.

dashboard and reporting basics: work with excel dashboards, power bi basics, charts, kpi reports, business summaries, and visual data presentation.

Beginner-level Analytics Projects: Develop Practical Projects Like Sales Analysis Dashboards, Customer Data Reports, Business Kpi Reports, And Small Analytics Case Studies.

Course Content

  • • introduction to data analytics
  • • what is data analytics?
  • • types of data analytics
  • • data analytics lifecycle
  • • role of data analyst in organizations
  • • applications of data analytics across industries
  • • understanding business problems through data

  • • excel interface and data management
  • • data cleaning techniques
  • • sorting and filtering data
  • • formulas and functions
  • • conditional formatting
  • • data validation
  • • pivot tables and pivot charts
  • • dashboard creation in excel

  • • introduction to databases
  • • sql basics
  • • select, where, order by
  • • filtering and sorting data
  • • aggregate functions
  • • group by and having
  • • sql joins
  • • subqueries basics
  • • data extraction for reporting

  • • python basics for analytics
  • • variables and data types
  • • conditional statements and loops
  • • functions in python
  • • introduction to numpy
  • • introduction to pandas
  • • working with dataframes
  • • reading csv and excel files
  • • data cleaning basics

  • • mean, median, mode
  • • standard deviation & variance
  • • probability basics
  • • correlation analysis
  • • trend analysis
  • • outlier detection
  • • descriptive statistics

  • • introduction to power bi
  • • data import and cleaning
  • • power query basics
  • • data modeling concepts
  • • charts and visualizations
  • • kpi dashboard development
  • • interactive reports and filters
  • • business reporting using power bi

  • • data visualization principles
  • • choosing appropriate charts
  • • data storytelling techniques
  • • kpi and metric analysis
  • • business reporting best practices
  • • insight presentation techniques

  • • excel kpi dashboard creation
  • • sql business report analysis

  • • local store sales analytics dashboard

Skills Developed with Data Analytics Course

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

Sql Data Assistant:

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

Excel Analytics Assistant:

Use excel formulas, charts, pivot tables, and dashboards 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, and business summaries.
Industry-relevant Tools: The course covers excel, sql, python basics, pandas, numpy, power bi basics, charts, dashboards, and reporting tools.
Mentor-guided Learning: Learners receive mentor support for concept clarity, assignments, dashboard creation, report building, and project development.
Strong Foundation For Advanced Analytics Courses: The course builds a solid base before moving into 45 days, 2 months, 3 months, 4 months, or 6 months 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

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