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Data Analytics Training

Learn Excel, SQL, Power BI, Python, and real-world analytics. Get job-ready skills for top roles in data science and business intelligence.

"Become a Data Analyst - Learn Excel, SQL, Power BI & Python!"

Real-world projects Certification 100% Job Support

Data Analytics Training

Data Analytics Training is a job-oriented program that teaches you how to extract insights from data using statistical tools, programming, visualization platforms, and real-time datasets. The course prepares students to become Data Analysts, Business Analysts, or Data Visualization Experts, with hands-on experience in tools like Excel, SQL, Python, Power BI, and Tableau.

This course is ideal for fresh graduates, B.Tech/MCA students, and working professionals who want to switch to or grow in the analytics domain.

Building Future-Ready Professionals? CALLUS

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Important Things

    • 💡 No coding background? You can still start with Excel & Power BI, then move to Python & SQL.

    • 🧪 Practice is key – daily exercises on real datasets help retain concepts.

    • 📚 Understand statistics and business logic – analytics is not just about tools.

    • 🔍 Learn storytelling with data – how to present your insights visually and clearly.

    • 🎓 Consider certifications like:

      • Google Data Analytics Professional Certificate

      • Microsoft Power BI Data Analyst Associate

      • IBM Data Analyst Certification

    • 📈 Career roles after this training include:

      • Data Analyst

      • Business Analyst

      • MIS Executive

      • Data Visualization Developer

      • Junior Data Scientist

Key Benifits

BenefitDescription
📊 Industry-Relevant Curriculum Covers Excel, SQL, Python, Power BI, Tableau, and real-world projects
👨‍💻 Hands-On Projects Work on live datasets, dashboards, and case studies to gain practical experience
🧑‍🏫 Expert Mentorship Learn from industry professionals and certified trainers
🎯 Job-Focused Learning Tailored to roles like Data Analyst, Business Analyst, MIS Executive
🌐 High Demand & Salaries Data Analytics is one of the top in-demand skills in IT and business
📜 Certification Support Helps prepare for Microsoft, IBM, or Google Data Analytics certifications
💼 Placement Assistance Resume building, interview preparation, and job referrals included

🔰 Foundational Courses

  1. Data Analytics Basics for Beginners

    • Data types, statistics basics, Excel, data visualization

    • Ideal for absolute beginners

  2. Microsoft Excel for Data Analysis

    • Formulas, PivotTables, VLOOKUP, data modeling

    • Practical for office & analytics roles

📈 Core Data Analytics Certifications

  1. Google Data Analytics Professional Certificate

    • Offered via Coursera

    • Covers Excel, SQL, Tableau, and business analytics

  2. IBM Data Analyst Professional Certificate

    • Python, SQL, Excel, IBM Cognos, and project-based learning

🧑‍💻 Programming-Focused Courses

  1. Python for Data Analysis

    • Numpy, Pandas, Matplotlib, Seaborn

    • Real-world projects and data wrangling

  2. R for Data Analysis

    • ggplot2, dplyr, statistical modeling in R

    • Popular in academic and research fields

💾 SQL & Databases

  1. SQL for Data Analysis

    • Joins, subqueries, window functions

    • MySQL / PostgreSQL / SQL Server based

  2. Database Management for Analysts

    • Relational databases, normalization, schema design

📊 Data Visualization Tools

  1. Tableau Training

    • Dashboards, charts, calculated fields

    • Business intelligence reporting

  2. Power BI Training

  • Data transformation with Power Query

  • DAX formulas and interactive dashboards

🧠 Advanced / Career-Oriented Courses

  1. Business Analytics with Excel & Power BI

  • For working professionals and business managers

  1. Advanced Excel + Power Query

  • Automation, reports, advanced formulas

  1. Data Science with Python

  • Analytics, machine learning, EDA, and stats

  1. Machine Learning for Analysts

  • Scikit-learn, supervised/unsupervised learning

🌐 Cloud-Based Analytics Courses

  1. AWS Data Analytics Specialty

  2. Google BigQuery & Looker Studio

  3. Microsoft Azure Data Analyst (DP-500)

Course Modules

🔹 Module 1: Introduction to Data Analytics

  • What is Data Analytics?

  • Data Types & Data Life Cycle

  • Business Intelligence vs. Data Science

  • Role of a Data Analyst

  • Analytics Tools Overview

🔹 Module 2: Microsoft Excel for Data Analysis

  • Data Cleaning & Preparation

  • Sorting, Filtering, and Conditional Formatting

  • Advanced Formulas (VLOOKUP, INDEX-MATCH, IF, COUNTIFS, etc.)

  • Pivot Tables & Pivot Charts

  • Dashboard Creation in Excel

🔹 Module 3: SQL for Data Retrieval

  • Introduction to Relational Databases

  • SQL Basics: SELECT, WHERE, ORDER BY

  • JOINS: INNER, LEFT, RIGHT, FULL

  • Aggregate Functions: COUNT, SUM, AVG, GROUP BY

  • Subqueries, CTEs, and Window Functions

  • Data Manipulation: INSERT, UPDATE, DELETE

  • Real-Time SQL Case Studies

🔹 Module 4: Statistics & Data Interpretation

  • Descriptive Statistics (Mean, Median, Mode, Std. Dev.)

  • Data Distributions and Outliers

  • Hypothesis Testing

  • Correlation vs. Causation

  • Probability Basics for Analytics

  • Sampling Techniques

🔹 Module 5: Python for Data Analysis

  • Python Basics (Data Types, Loops, Functions)

  • Working with Libraries: NumPy, Pandas, Matplotlib, Seaborn

  • Data Cleaning and Transformation using Pandas

  • Exploratory Data Analysis (EDA)

  • Importing/Exporting Data (CSV, Excel, SQL, Web APIs)

🔹 Module 6: Data Visualization Tools

🟡 Power BI

  • Power BI Interface & Data Loading

  • Data Modeling, Relationships, DAX Basics

  • Creating Interactive Dashboards

  • Publishing & Sharing Reports

🔵 Tableau (optional/add-on module)

  • Tableau Interface and Data Connections

  • Charts, Filters, Parameters, and Calculations

  • Dashboard Design Best Practices

  • Storytelling with Tableau

🔹 Module 7: Capstone Project & Case Studies

  • Real-time project using Excel + SQL + Power BI

  • End-to-end data pipeline for a business scenario

  • Presentation of insights using dashboards

  • Resume Portfolio Building

🔹 Module 8: Interview & Career Preparation

  • Top Interview Questions Practice (Tool-wise & Scenario-based)

  • Resume Writing for Data Analyst Roles

  • Mock Interviews & HR Screening Practice

  • LinkedIn & Job Portal Guidance

🎓 Certifications Covered / Suggested

  • Google Data Analytics Certificate

  • Microsoft Certified: Power BI Data Analyst Associate

  • IBM Data Analyst Certificate (Coursera/edX)

  • Optional: Python or SQL certifications (HackerRank, DataCamp)

Interview Questions

Excel & Data Handling:

  1. How do you use VLOOKUP and INDEX-MATCH?

  2. What is the difference between a Pivot Table and a regular table?

  3. How do you clean and validate large datasets in Excel?

SQL:

  1. What is the difference between INNER JOIN and LEFT JOIN?

  2. How do you find duplicate rows in a SQL table?

  3. How can you calculate the total revenue per month using SQL?

Python (for Data Analysis):

  1. What libraries are used for data analysis in Python?

  2. How do you handle missing data in Pandas?

  3. Explain the difference between NumPy and Pandas.

Power BI / Tableau:

  1. What are measures and dimensions in Power BI/Tableau?

  2. How do you create a calculated field?

  3. How do you handle large datasets in visualization tools?

General & Scenario-Based:

  1. Walk me through a recent data project you worked on.

  2. How do you decide which chart to use for a given dataset?

  3. How do you explain technical insights to non-technical stakeholders?

🎓 Bonus: Combo Career Tracks

You can offer Job Role-Based Tracks:

  • Junior Data Analyst: Excel + SQL + Power BI

  • Data Analyst Pro: Python + SQL + Tableau + Projects

  • Business Analyst: Excel + Power BI + Communication Skills

  • Cloud Data Analyst: BigQuery + Looker Studio + SQL

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