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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

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

    • πŸ§ͺ Practice is key – daily exercises on real datasets help retain concepts.

    • πŸ“š Understand statistics and business logic – analytics is not just about tools.

    • πŸ” Learn storytelling with data – how to present your insights visually and clearly.

    • πŸŽ“ Consider certifications like:

      • Google Data Analytics Professional Certificate

      • Microsoft Power BI Data Analyst Associate

      • IBM Data Analyst Certification

    • πŸ“ˆ Career roles after this training include:

      • Data Analyst

      • Business Analyst

      • MIS Executive

      • Data Visualization Developer

      • Junior Data Scientist

Key Benifits

BenefitDescription
πŸ“Š Industry-Relevant Curriculum Covers Excel, SQL, Python, Power BI, Tableau, and real-world projects
πŸ‘¨‍πŸ’» Hands-On Projects Work on live datasets, dashboards, and case studies to gain practical experience
πŸ§‘‍🏫 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
πŸ“œ Certification Support Helps prepare for Microsoft, IBM, or Google Data Analytics certifications
πŸ’Ό Placement Assistance Resume building, interview preparation, and job referrals included

πŸ”° 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

πŸ“ˆ 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

πŸ§‘‍πŸ’» 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

πŸ’Ύ 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

πŸ“Š 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

πŸ”Ή 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

πŸ”Ή 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

πŸ”Ή 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

πŸ”Ή 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

πŸ”Ή 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)

πŸ”Ή Module 6: Data Visualization Tools

🟑 Power BI

  • Power BI Interface & Data Loading

  • Data Modeling, Relationships, DAX Basics

  • Creating Interactive Dashboards

  • Publishing & Sharing Reports

πŸ”΅ Tableau (optional/add-on module)

  • Tableau Interface and Data Connections

  • Charts, Filters, Parameters, and Calculations

  • Dashboard Design Best Practices

  • Storytelling with Tableau

πŸ”Ή 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

πŸ”Ή 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

πŸŽ“ 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?

πŸŽ“ 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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