DATADRIX : Data Analytics

Deciphering Data, Illuminating Insights

The course provides comprehensive training in data analysis techniques, tools, and methodologies, equipping students with the skills to derive insights from data. Through hands-on projects and real-world case studies, students learn to manipulate, analyze, and visualize data, gaining practical experience to excel as data analysts in various industries.In today’s data-driven world, the ability to extract actionable insights from vast datasets is invaluable. Our comprehensive program equips you with the essential skills to collect, analyze, and interpret data effectively. Join us and become a proficient data analyst, ready to tackle the challenges of tomorrow’s data-driven opportunities.

Course Curriculum

A syllabus is a meticulously crafted document that serves as a comprehensive roadmap for the training program. It plays a pivotal role in guiding candidate along their learning journey, offering a structured framework for acquiring knowledge and honing skills.

Module 1

  • Introduction to Python Programming
  • Variable & Datatypes
  • Conditional & Looping Statements
  • Functions & File Handling
  • Exception Handling & Threading
  • Searching & Sorting
  • Object Oriented Programming
  • Python Libraries
  • Handling structural Datasets
  • Data Manipulation
  • Data Cleaning
  • Importing data from mutiple sources
  • Finding Insights from datasets

In our Python course, we delve into the powerful ecosystem of Python libraries that enhance the functionality and efficiency of your coding projects. Students will explore widely-used libraries such as NumPy for numerical computations, Pandas for data manipulation and analysis, and Matplotlib and Seaborn for data visualization. Additionally, the course covers libraries like Scikit-Learn for machine learning, BeautifulSoup for web scraping, and Flask for web development. Each library is introduced with practical examples and hands-on exercises, enabling students to understand their applications and integrate them into their projects. By mastering these libraries, participants will be equipped with the tools needed to tackle complex programming challenges and develop sophisticated applications, making them valuable assets in the field of software development.

  • Introduction to SQL and MySQL
  • Data Creation and Retrieval
  • Data Filtering
  • Data Analysis using aggregate functions and group by
  • Joins and Keys
  • MySQL Joins
  • Subqueries and Views
  • Window/Analytical Functions
  • Case Study

Module 2

  • What is Data Visualization?
  • Data Visualization in Python
  • Matplotlib and Seaborn
  • Line Charts & Bar Graphs
  • Histograms, Scatter Plots & Heat Maps

Data cleaning is a crucial part of our Python course, focusing on the essential techniques required to prepare raw data for analysis. This section of the course teaches students how to handle missing values, detect and correct errors, and ensure consistency in datasets using powerful Python libraries such as Pandas and NumPy. Students will learn to identify outliers, standardize data formats, and manage duplicate records, gaining hands-on experience with real-world datasets. The curriculum emphasizes practical skills through projects and exercises, enabling students to transform messy data into clean, reliable datasets ready for analysis. By mastering data cleaning, students will be well-equipped to tackle data-driven challenges and contribute effectively to data science and analytics projects.

  • Introduction to Data Cleaning and Data Types
  • Exploring and Visualization the missing values
  • Advanced-Data Cleaning Concepts
  • Introduction to Feature Engineering
  • Feature Extraction and Transformation
  • Feature Selection and Dimensionality Reduction
  • Introduction to Statistics
  • Probability Theory
  • Statistical Inference I
  • Statistical Inference II
  • Regression Analysis I
  • Regression Analysis II
  • Understanding Data Models: Data modeling in Power BI involves structuring raw data into a format that is optimized for analysis. It includes defining tables, relationships, and data types to enable efficient querying and reporting.
  • Data Relationships: Establish relationships between different tables in your data model. Power BI supports one-to-many, one-to-one, and many-to-many relationships, enabling seamless interaction between data points.
  • Star and Snowflake Schemas: Learn about designing data models using Star Schema (with fact and dimension tables) or Snowflake Schema (where dimension tables are normalized), which help improve performance and scalability in reporting.
  • Data Transformation: Power BI’s Power Query allows users to clean and transform raw data before it enters the data model. Use M language to reshape and prepare the data for analysis.
  • Calculated Columns & Measures: Understand the difference between calculated columns (computed at the data row level) and measures (aggregations such as sum, average, etc., computed on-demand). Both are powered by DAX (Data Analysis Expressions).
  • Data Types and Formatting: Ensure that the correct data types (e.g., integer, decimal, text, date) are assigned to columns for accurate calculations and analysis.
  • Data Normalization and Denormalization: Explore when to normalize (split data into multiple tables to reduce redundancy) or denormalize (combine tables to improve query performance) depending on the report’s needs.
  • Performance Optimization: Learn techniques to optimize data models, such as reducing the size of your data, removing unnecessary columns, creating summary tables, and applying relationships wisely.
  • DirectQuery vs Import Mode: Understand the difference between DirectQuery (real-time data from source) and Import Mode (loading data into Power BI), and when to use each mode for optimal performance.

Module 3

  • Advanced Sorting and Filtering Techniques
  • Data Validation & Drop-Down Lists
  • Conditional Formatting with Custom Rules
  • Working with Large Datasets: Splitting, Merging, and Cleaning Data
  • Removing Duplicates & Data Sanitization
  • Lookup Functions: VLOOKUP(), HLOOKUP(), XLOOKUP(), INDEX() & MATCH()
  • Logical Functions: IF(), IFS(), AND(), OR(), IFERROR()
  • Statistical Functions: SUMIFS(), COUNTIFS(), AVERAGEIFS()
  • Text Functions: TEXT(), CONCATENATE(), LEFT(), RIGHT(), LEN(), TRIM()
  • Date & Time Functions: TODAY(), NOW(), DATEDIF(), NETWORKDAYS()
  • Building and Customizing Pivot Tables
  • Calculated Fields and Pivot Table Summaries
  • Grouping Data in Pivot Tables (Dates, Numbers)
  • PivotTable Slicers and Timelines for Interactive Reports
  • Power Pivot for Large Data Models and Advanced Analytics
  • Creating Interactive Dashboards with PivotTables, Slicers, and Charts
  • Using Named Ranges and Dynamic Data
  • Integrating Advanced Excel Tools into Dashboards (Charts, Pivot Tables)
  • Creating & Customizing Charts (Bar, Line, Pie, Waterfall, etc.)
  • Pivot Charts and Advanced Chart Types (Histogram, Sparklines)
  • Conditional Charts with Dynamic Ranges
  • Heatmaps & Data Visualization Best Practices

Module 4

  • Comprehensive Business Intelligence Tool: Power BI is a powerful tool for data visualization and business intelligence, allowing users to connect, transform, and visualize data from multiple sources.
  • Interactive Dashboards & Reports: Power BI provides interactive dashboards and real-time data reporting, making it easier for users to gain insights and make data-driven decisions.
  • Wide Range of Data Sources: It supports a wide variety of data sources, including Excel, SQL databases, cloud services, and even web-based data, enabling seamless integration across platforms.
  • User-Friendly Interface: With its drag-and-drop interface and customizable visuals, Power BI allows users of all skill levels to create sophisticated reports without needing advanced technical knowledge.
  • Effective Use of Visualizations: Learn to choose the right visuals (charts, graphs, tables) to represent different types of data, ensuring clarity and insight-driven storytelling.
  • Layout & Formatting Best Practices: Explore techniques for organizing report elements, such as consistent font sizes, color schemes, alignment, and spacing to create professional and user-friendly reports.
  • Interactivity & Filtering: Understand how to use slicers, filters, and drill-through features to make reports interactive, allowing users to explore data dynamically.
  • Optimizing Report Performance: Learn strategies for improving report performance, including data modeling optimization, reducing visual overload, and managing large datasets efficiently.
  • Branding & Custom Themes: Discover how to apply custom themes, company branding, and design principles to create visually consistent and impactful reports.
  • Visual Sync Across Pages: Learn how to synchronize slicers and filters across multiple report pages to maintain consistency in filtering and interactivity throughout the report.
  • Visual Grouping: Understand how to group visuals together in Power BI, allowing for easier management, alignment, and movement of multiple elements as a single unit.
  • Slicer Synchronization: Explore the use of synchronized slicers to apply the same filter conditions across different visuals or pages, providing a cohesive user experience.
  • Managing Grouped Elements: Gain insights into managing grouped visuals, adjusting layouts, and ensuring that grouped elements maintain their design integrity when resized or repositioned.
  • Bookmarks for Navigation: Learn how to create and use bookmarks to capture specific report views, allowing users to easily switch between different visuals, filters, and report layouts with a single click.
  • Dynamic Report Filters: Understand how to apply filters across visuals and pages in Power BI, enabling users to focus on specific data points and create more targeted insights.
  • Bookmark Interaction with Filters: Explore how bookmarks can save and restore filter states, enabling dynamic reporting scenarios such as toggling between different data perspectives or predefined report views.
  • Enhancing User Experience: Utilize bookmarks and filters to create interactive reports, such as custom navigation, storytelling, and report tours, enhancing the overall user experience.
  • Data Transformation: Learn how to use Power Query to clean, reshape, and transform raw data into a structured format ready for analysis. This includes filtering, merging, and appending data from multiple sources.
  • Automating Data Prep: Understand how Power Query automates data preparation by recording transformation steps, making it easier to update datasets without manual intervention.
  • Data Import and Connection: Explore the ability to connect to various data sources (Excel, SQL, web, etc.) and manage data import processes efficiently using Power Query’s robust ETL capabilities.
  • M Code for Custom Logic: Get introduced to Power Query’s formula language, M, to apply advanced data transformations and automate complex processes.
  • Advanced Data Calculations: Learn to use DAX functions like SUMX, CALCULATE, FILTER, and RELATED to perform advanced calculations and aggregations across multiple tables in your data model.
  • Creating Custom Measures: Understand how to create dynamic measures and calculated columns using DAX, allowing for deeper insights and more flexible reporting.
  • Time Intelligence Functions: Explore time-based analysis using DAX time intelligence functions like TOTALYTD, SAMEPERIODLASTYEAR, and DATESBETWEEN to analyze data trends over time.
  • Optimizing Performance: Discover how to optimize the performance of DAX queries by writing efficient formulas and leveraging context to improve report speed and accuracy.
  • Requirement Gathering: Identify and document the data analysis needs, business requirements, and key performance indicators (KPIs) for the Power BI reports or dashboards.
  • Data Modeling & Design: Design the data model and schema required for Power BI, focusing on data sources, relationships between tables, and data flow to ensure optimal reporting structure.
  • Development: Create Power BI reports, dashboards, and data visualizations using Power BI Desktop. Implement data connections, DAX functions, and Power Query transformations during this phase.
  • Testing: Validate data accuracy, report functionality, and performance by performing quality checks on the Power BI dashboards. Ensure that filters, calculations, and visuals align with business requirements.
  • Deployment: Publish and deploy the Power BI reports and dashboards to Power BI Service or Power BI Report Server for end-users to access.
  • Maintenance & Support: Monitor reports and dashboards for issues, ensure the data is up-to-date, and provide ongoing support and enhancements based on user feedback.

Internship Program

This internship is a part of the course curriculum to help you gain real experience in the Data Science domain.During this internship, you will go through various challenges which you allow to explore new skills and push your limits while learning something new during the projects.

Topics Covered :

Integration of python & SQL

Web Scrapping

Data Cleaning with Python

Model Evaluation

Git / Github Integration

End to End Projects

Interview Preparation

Datadrix offers top-notch placement opportunities. With strong industry ties and modern training, we excel in placing our candidates. Our results speak to our commitment to shaping successful careers. Our approach ensures to open pathway for learners to achieve good growth in the domain

Activities Covered :

Interview Pattern Preparation

Mock Interview Practice Sessions

Preparation as per Job Description

Placement Ready Session for Working Professionals

Technical Screening for technical strengthening

Screening for effective communication check

Placement

Datadrix offers top-notch placement opportunities. With strong industry ties and modern training, we excel in placing our candidates. Our results speak to our commitment to shaping successful careers. Our approach ensures to open pathway for learners to achieve good growth in the domain

Request Information Chat with DATADRIX

Duration

Our 150+ hour data science course offers in-depth training and hands-on experience, covering everything from data collection to advanced analysis and visualization, preparing you to excel in the data-driven world.

Assignments

Our data science course includes assignments that offer hands-on training and cover data collection, analysis, and visualization, equipping you with essential skills for real-world professional success.

Projects

Our data science course features projects that offer practical, hands-on training in data collection, analysis, and visualization, equipping you with essential skills and real-world experience for success.

Live Classes

Our data science course includes live classes offering hands-on training and real-time guidance. From data collection to advanced analysis and visualization, you’ll gain essential skills to excel in today’s tech-driven world.

Classnotes

Our data science course includes detailed class notes that cover data collection, analysis, and visualization, providing the essential skills and practical knowledge needed to excel in the tech-driven world.

Interview Preparation

Our data science course includes targeted interview preparation, covering data collection, analysis, and visualization. This training equips you with the essential skills needed to excel in interviews and succeed in the tech-driven world.

Placements

Our data science course offers dedicated placement support, focusing on data collection, analysis, and visualization. This training equips you with the skills needed to succeed in the tech-driven world and secure your ideal job.

An Awesome Community

Our students, instructors and mentors come from different colleges, companies, and walks of life.

Meet our team & students

Joining DATADRIX means you’ll create an amazing network, make new connections, and Leverage Diverse Opportunities

“Validate Your Expertise and Propel Your Career”

  • Expand Opportunities: Certifications to unlock new career opportunities, gain credibility with employers, and open doors to higher-level positions.
  • Continuous Growth: Certifications not only validate your current skills but also encourage continuous learning and professional development, allowing you to stay updated with the latest industry trends and advancements.
  • Certification: A testament to your skills and knowledge, certifications demonstrate your proficiency in specific areas of expertise, giving you a competitive edge in the job market.
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Data Analyst

Translating Raw Numbers into Actionable Intelligence

Our Data Analyst course is your gateway to unlocking the power of data in the digital age. In an era where data is at the heart of decision-making in businesses and organizations, being proficient in data analysis is a valuable skill. Our comprehensive program offers a deep dive into the world of data, equipping you with the knowledge and practical expertise required to extract insights from raw information. Whether you’re just starting your career or seeking to enhance your analytical skills, our course caters to learners at all levels. From mastering data visualization to advanced statistical analysis, you’ll gain the tools and confidence to make data-driven decisions that impact the success of any enterprise.

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Deepak Chahal
Devansh Goel
Ishty Malhotra
Taneesha Agrawal
Mayank Rana
Shubham Naithani
Kartik Sharma
Upvansh Thakur
Naveen Negi
Amita Dwivedi
Abhinav Bishnoi
Himanshu Pal
Jay Verma
Neha Sharma
Rishabh Upadhyay

Key Features & Benefits

  • Practice problems of varying difficulty
  • Over more than 5000+ Questions
  • 1:1 Expert Doubt support
  • Mock interviews with career guidance
  • 12 + Years of exprienced Faculty
  • Deep Explaination of coding
  • Practical & Project Based Learning
  • Structured feedback to make you better
  • Resume Profile Building
  • Offline / Online Modes
  • Interview Preparation
  • Production Workflow
  • Secure Certification
  • Git Github Integration
  • 24/7 Support Team
  • Projects from the scratch

Frequently Asked Questions

What do you understand by Data Analysis Course

Data Analysis Course typically teaches the techniques and tools for collecting, cleaning and interpreting data

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What are the roles and responsibilities in data analytics course

Responsibilities include collecting, cleaning and transforming data, performing statistical analysis & presenting actionable insights

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What are the Best five steps in data analysis course

Course emphasizes effective communication of findings, teaching students how to present their results concisely

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What does Data Analysis and Reporting do in India

Data Analysis and Reporting play a crucial role in various industries, aiding organizations in making informed decisions

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