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Data Analytics Certification Training
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About Course
🧾 Data Analytics – About Course
The Data Analytics Online Training program is designed to equip learners with the technical and analytical skills required to extract insights from raw data and drive data-driven business decisions. This course provides a complete understanding of the data analytics lifecycle — from data collection, cleaning, and visualization to predictive modeling and reporting.
Learners will gain hands-on experience with popular analytics tools such as Excel, SQL, Power BI, Python, Tableau, and R, while mastering statistical analysis, business intelligence, and machine learning fundamentals. The training emphasizes real-world projects to help participants analyze business trends, measure performance, and make strategic recommendations.
This program is ideal for data enthusiasts, business analysts, professionals transitioning into analytics, and students aiming to build a strong career in data-driven industries.
⚙️ Key Learning Highlights
- Understand the fundamentals of data analytics and data visualization
- Perform data cleaning, manipulation, and transformation using SQL and Python
- Build interactive dashboards and reports with Power BI and Tableau
- Apply statistical and predictive analysis for business insights
- Learn data storytelling and visualization best practices
- Gain exposure to real-world datasets and end-to-end analytics projects
🎯 Course Benefits
- Learn industry-relevant tools and technologies
- Develop practical analytics and visualization skills
- Gain real-time project experience for job readiness
- Prepare for Data Analyst and Business Analyst roles
- Strengthen problem-solving and data-driven decision-making skills
Data Analytics Training Course Syllabus
🧩 Module 1: Introduction to Data Analytics
- What is Data Analytics?
- Types of Analytics – Descriptive, Diagnostic, Predictive & Prescriptive
- Data Analytics Lifecycle & Real-World Use Cases
- Role of a Data Analyst in Modern Organizations
- Overview of Business Intelligence & Data-Driven Decision Making
🧩 Module 2: Excel for Data Analysis
- Data Cleaning and Preparation using Excel
- Pivot Tables, Charts, and Dashboards
- Conditional Formatting and Advanced Formulas
- What-If Analysis & Data Modeling Concepts
- Data Validation and Reporting Techniques
🧩 Module 3: SQL for Data Analytics
- Basics of Databases and SQL Architecture
- SQL Queries – SELECT, JOIN, GROUP BY, HAVING, WHERE
- Subqueries, CTEs, and Window Functions
- Data Aggregation and Filtering for Reports
- Real-Time SQL Case Studies for Analysis
🧩 Module 4: Python for Data Analytics
- Introduction to Python and Jupyter Notebook
- Data Structures – Lists, Dictionaries, Tuples, Sets
- Data Analysis Libraries – Pandas, NumPy, Matplotlib, Seaborn
- Data Cleaning, Transformation & Visualization
- Exploratory Data Analysis (EDA) with Python
🧩 Module 5: Data Visualization with Power BI
- Introduction to Business Intelligence Tools
- Connecting Power BI to Different Data Sources
- Data Modeling and Relationships
- Creating Interactive Dashboards and Reports
- DAX Formulas and Calculations
- Publishing and Sharing Dashboards
🧩 Module 6: Tableau for Data Visualization
- Tableau Interface and Dashboard Design
- Data Connection and Preparation in Tableau
- Charts, Maps, and Storytelling with Data
- Calculated Fields, Parameters, and Filters
- Advanced Visual Analytics Techniques
🧩 Module 7: Statistics & Data Interpretation
- Descriptive and Inferential Statistics
- Probability Distributions and Hypothesis Testing
- Correlation, Regression, and Variance Analysis
- Business Problem Solving with Statistical Models
🧩 Module 8: Introduction to Machine Learning Concepts
- Basics of Predictive Analytics and AI in Business
- Linear & Logistic Regression
- Classification and Clustering Overview
- Model Evaluation Techniques
- Integration of Machine Learning with Analytics Tools
🧩 Module 9: Projects & Case Studies
- Sales & Revenue Analytics
- Customer Segmentation and Retention Analysis
- Financial Forecasting and KPI Dashboards
- Marketing Campaign Analytics
- HR Attrition and Employee Performance Dashboard
🧩 Module 10: Career Preparation
- Resume Building for Data Analysts
- Common Interview Questions & Mock Sessions
- Portfolio Creation with Dashboards & Reports
- Certification Guidance (Microsoft, Google, IBM, etc.)
Data Analytics Course Key Features
- Live Instructor based training with software
- Certification Oriented content
- Hands-on complete Realtime training
- Flexible schedule demo's & classes
- Live recorded videos access
- Study material provided
- JOB Assistance
Course completion certificate
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CHOOSE YOUR OWN COMFORTABLE LEARNING EXPERIENCE
Live Virtual Training
- Schedule your sessions at your comfortable with timings
- Instructor-Led training real time projects
- Certification Guidance
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Self-Paced Learning
- Complete set of live-online training session recorded videos.
- Learn technology at your own pace.
- Get access for lifetime.
Corporate Training
- Learn as a full day schedule with discussions, exercises.
- Practical use cases.
- Design your own syllabus based
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Data Analytics Online Training FAQ'S
What is Data Analytics?
Data Analytics is the process of examining raw data to identify patterns, correlations, and insights for business decision-making.
What are the key tools used in Data Analytics?
Common tools include Excel, SQL, Power BI, Tableau, Python, and R.
How is Data Analytics different from Data Science?
- Data Analytics focuses on analyzing existing data for insights, while Data Science involves predictive modeling and machine learning
What is data cleaning and why is it important?
Data cleaning involves removing errors and inconsistencies in data to ensure accuracy and reliability of insights
What industries use Data Analytics the most?
- Major industries include finance, healthcare, e-commerce, manufacturing, and marketing.
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