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Beginner · Job-ready foundations

Data Analytics Essentials

Learn how to turn raw data into clear decisions — cleaning, SQL querying, analysis, dashboards, and real business-style projects.

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4–6
Weeks (flexible)
3+
Portfolio projects
1:1
Mentor guidance
Overview

What this course covers

Data analytics includes collecting data, cleaning it, exploring patterns, and communicating results through visuals and dashboards.

What is analytics?

You'll learn the core types used in business — descriptive ("what happened"), diagnostic ("why"), and basics of predictive thinking.

Tools you'll use

Excel for fast analysis (PivotTables), SQL for querying databases, and dashboard concepts that map to tools like Power BI and Tableau.

ExcelSQLDashboards

Outcome

You'll finish with portfolio projects and a repeatable workflow you can apply to any dataset in any company.

Curriculum

Structured like real analyst work

Ask → fetch → clean → analyze → explain.

Module 1

Analytics Foundations

  • Metrics, KPIs, and business questions
  • Data types, common mistakes, sanity checks
  • How analysts communicate — executive summary format
Module 2

Excel for Analysis

  • Cleaning data: duplicates, blanks, inconsistent formats
  • PivotTables + PivotCharts for summarizing datasets
  • Conditional formatting and basic forecasting ideas
Module 3

SQL Essentials

  • SELECT, WHERE, GROUP BY, ORDER BY
  • JOINs, filtering, basic window concepts
  • Answer real business questions using queries
Module 4

Visualization + Dashboard Thinking

  • Chart selection — avoid misleading visuals
  • Dashboard layout, filters, drill-down
  • Presenting insights clearly: story → evidence → recommendation
Module 5

Capstone Prep

  • Data dictionary and assumptions documentation
  • Deliverables: report + dashboard + summary
  • Interview-style explanation practice

What you submit each week

Mini-assignments that build directly into your portfolio.

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Tools & Concepts

We teach the skill, not just buttons

So you can switch tools easily as your career evolves.

Excel

Fast analysis, PivotTables, quick charts, summaries. The most common tool in real analyst roles.

PivotTablesChartsCleaning

SQL

Query and summarize data from relational databases using a language every company depends on.

JOINsGROUP BYFiltering

Dashboards

Learn how dashboards answer questions with visuals, filters, and drill-down. Concepts apply in Power BI, Tableau, or Looker.

LayoutKPIsStorytelling
Portfolio Projects

Work samples you can talk about in interviews

Designed to look and feel like real analyst deliverables.

Sales Performance Dashboard

Excel + Dashboard

Clean sales data, build Pivot summaries, identify top products and regions, and present recommendations.

  • KPIs: revenue, margin, growth
  • Region & product breakdown
  • Executive summary slide

SQL Business Questions Pack

SQL

Answer 15–20 business questions (retention, AOV, repeat customers) using structured queries.

  • JOINs + aggregations
  • Clean output tables
  • Insights + conclusions

Customer Support Insights

Analysis + Story

Analyze ticket data to find root causes, peak times, and improvement opportunities.

  • Issue categories & trends
  • Resolution time distribution
  • Actionable recommendations
Pricing

Simple, transparent, affordable

No hidden fees. Pay for the tier that matches your goals.

Starter

₹4,999

Self-paced + assignments

  • Full curriculum access
  • Project templates
  • Community support
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Most Popular

Mentored

₹9,999

Best for job prep

  • Everything in Starter
  • Weekly mentor check-ins
  • Portfolio review
  • Interview practice
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Team

Custom

For colleges / companies

  • Custom schedule
  • Group mentoring
  • Progress reporting
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FAQ

Common questions

No. This course starts beginner-friendly. SQL is taught from scratch, and Excel is used heavily first before anything more technical.
Yes — your portfolio projects and your ability to explain your workflow are what recruiters look for in entry-level and internship roles.
Analytics focuses more on reporting, dashboards, and decision support. Data science typically goes deeper into modeling, statistics, and machine learning.
4–6 weeks at your own pace. You can finish faster or slower depending on your schedule — there's no strict deadline.
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Course: Data Analytics Essentials
Skills: Excel, SQL, Dashboards, Insight writing
Level: Beginner-friendly