Data Analyst (Batch-08) Certification Program – Zero to Hero in Excel, SQL, Power BI, Tableau and Python

Categories: MS Excel, Power BI, Python, SQL, Tableau
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About Course

Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

 

Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education.

 

The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data, but be able to provide insight and analysis through clear visual, written and verbal communication.

 

Some responsibilities of a data analyst includes:

  • Developing records management processes and policies
  • identify areas to increase efficiency and automation of processes
  • set up and maintain automated data processes
  • identify, evaluate and implement external services and tools to support data validation and cleansing
  • produce and track key performance indicators
  • develop and support reporting processes
  • monitor and audit data quality
  • liaise with internal and external clients to fully understand data content
  • gather, understand and document detailed business requirements using appropriate tools and techniques
  • design and carry out surveys and analyse survey data
  • manipulate, analyse and interpret complex data sets relating to the employer’s business
  • prepare reports for internal and external audiences using business analytics reporting tools
  • create data dashboards, graphs and visualisations
  • provide sector and competitor benchmarking
  • mine and analyse large datasets, draw valid inferences and present them successfully to management using a reporting tool

 

In this course we will perform some task of a Data Analyst  using Python ,Excel, Tableau, SQL, and  Power BI.  We will connect to a variety of data sources, perform  data transformation ,cleaning and  exploration . We will create dashboards to visual data

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Course Content

Class 01 – Introduction to Power BI | Data Sourcing & Warehousing | Data Mart vs Data Lake vs Data Warehouse | Installing Power BI | Excel vs Power BI | Exploring Data Sources & Types | Introduction to Power Query

  • Data Analyst (Batch-08) – Session 01
    02:36:12

Class 02 – Data Sources | Text Tools | Duplicate & Replace | Parsing (XML, JSON) | Data Views | Numeric Tools | Error Handling

Class 03 – Change Type with Locale | Date Tools | Conditional & Index Columns | Merge & Append Queries | Grouping Data | Line Chart Features

Class 04 – Database Management Systems | Tables | Primary & Foreign Keys | Relationship Cardinality | One-to-Many Relationships | Star & Snowflake Schemas | E-Commerce Sample Database (Data Types)

Class 05 – Data Modeling Basics | Primary Keys | Table Relationships | Star & Snowflake Schema Layouts | Bi-Directional Flows | Active/Inactive Relationships | Multiple Fact Tables via Dimensions | Hiding Columns | Creating Hierarchies

Class 06 – DAX Overview | Difference Between DAX & M-Code | Conditional Columns | DAX Measures (SUM, AVERAGE, COUNT, DISTINCTCOUNT, DIVIDE) | Logical Functions (IF, SWITCH)

Class 07 – Power BI DAX: Context Modification (ALL, FILTER) | Iterator Functions (SUMX, MAXX, MINX) | Time Intelligence (DATESYTD, DATEADD, DATEINPERIOD) | Dynamic Measures | Conditional Logic | Periodic Analysis & Comparisons

Class 08 – Power BI Dashboard: Map, Table, Donut Charts | Top N Filtering | Real-Life Use Cases | Designing Interactive, Insightful Dashboards

Class 09 – Power BI: Gauge Charts | Slicers | Visual Filters | Line Charts | Bookmarks & Buttons | Edit Interactions | Enhancing Interactivity and Navigation in Dashboards

Class 10 – Power BI: Navigation Buttons | Slicer Panel | Role-Based Security | Field Parameters | Creating Interactive Navigation, Managing Filters, Setting Up Roles, and Building Dynamic Visuals

Class 11 – Power BI: AI Visuals | Key Influencers | Decomposition Tree | Q&A | Narrative | Anomalies | Leveraging AI Visuals for Deeper Insights, Natural Language Queries, Automated Narratives, and Anomaly Detection

Class 12 – Career Guidance: Q&A with Students | Job Description Analysis | Freelancing Tips | Self-Motivation for Independent Work

Class 13 – Market Mindz – Power BI Project: Creating New Tables from Existing Data | Data Pre-Processing Techniques (Cleaning, Transforming) | Visualizations for Campaign Analysis (Key Metrics, Trends, Insights)

Class 14 – Market Mindz – Power BI Project: Visualizations for Buyer Analysis (Charts, Graphs, Insights) | Power BI Themes (Default and Custom) | Creating Custom Themes Using Images | Enhancing Report Aesthetics and User Experience

Class 15 – Power BI Revision | SQL – Introduction to Databases | SQL Basics | Schema Understanding | Basic Query Syntax | SELECT Statement

Class 16 – SQL – Command Types (DDL, DML, DQL) | SQL Main Clauses (SELECT, FROM, WHERE, GROUP BY, HAVING) | SQL Numeric Functions | SQL Date Functions

Class 17 – SQL – Comparison & Logical Operators | String Functions | Logical Functions

Class 18 – SQL – DATE Functions | CASE Statements | Date Calculations and Formatting | Extracting Date Parts | Conditional Logic

Class 19 – SQL – Numeric Functions | CAST Function | Unicode ‘N’ Prefix | Execution Plan | Subqueries (Intro) | Normalization (1NF, 2NF, 3NF) | Math Operations | Type Conversion | Query Performance | Database Design Principles

Class 20 – SQL – Entity Relationship Diagram | SQL Joins | One-to-One, One-to-Many, Many-to-Many | Joining Tables for Related Data | Real-World Join Use Cases

Class 21 – SQL – Data Control Language (DCL) | Transaction Control Language (TCL) – COMMIT and ROLLBACK | BEGIN TRANSACTION | SQL Discussion | All Topics Revision in Detail | Managing Permissions and Access with DCL | Ensuring Data Integrity with TCL Commands | Using Transactions to Control Multiple SQL Operations | Comprehensive Recap of All Key SQL Concepts

Class 22 – SQL – Views | UNION ALL | UNION | INTERSECTION | LIKE Command | GROUP BY Clause (Revision) | Creating and Using Views as Virtual Tables | Merging Results with UNION Variants | Filtering with LIKE Patterns | Revisiting GROUP BY for Data Aggregation

Class 23 – SQL – Self Join | Common Table Expression (CTE) | Using Self Join to Compare Rows in the Same Table | Building Virtual Tables with CTE | Simplifying Complex Queries | Applying CTEs in Hierarchical Data Scenarios

Class 24 – SQL – Window Functions | Aggregate Functions with PARTITION BY (SUM, MAX, MIN, COUNT) | Ranking Within Groups | Group-Wise Aggregations Without GROUP BY | Use Cases in Analytics and Reporting

Class 25 – SQL – Analytical Window Functions (LEAD, LAG, FIRST_VALUE, LAST_VALUE) | Row-Wise Calculations Without Aggregation | Practical Use Cases for Trend and Comparative Analysis | Applications in Business Intelligence and Reporting

Class 26 – SQL Server – Triggers (Part 1) | AFTER INSERT, BEFORE UPDATE, AFTER DELETE | Trigger-Based Automation in SQL | Intro Discussion on AI and Cloud Computing Concepts

Class 27 – SQL Server – Triggers (Part 2) | Stored Procedures with IN, OUT, INOUT Parameters | System-Defined and User-Defined Functions | Advanced SQL Logic and Reusability Concepts

Class 28 – Python Introduction | Installed Anaconda | Wrote First Program | Learned Python Basics | Core Data Types | Variable Assignment | String Functions

Class 29 – Python Data Structures | Lists, Sets, Tuples, Dictionaries | Boolean Types | Indexing & Slicing | Built-in Functions | Comparison Operators

Class 30 – Python Control Flow | Chained Comparisons | Conditional Statements | for & while Loops | Built “Guess the Number” Game | Lambda vs User-Defined Functions

Class 31 – Python Essential Libraries | Installing and Using Libraries | NumPy Arrays (1D, 2D, 3D, Indexing, Slicing) | Pandas Core Functions | Importing CSV, Excel, and Other Formats | Practical Use Cases

Class 32 – EDA with Python | Analyzed Roller Coaster Dataset (Project 1) | Used Pandas for Data Handling | Visualized Data with Matplotlib and Seaborn (Scatter, Bar, KDE, Histogram, Heatmap) | Connected to Databases Using Python

Class 33 – EDA with Python | Analyzed Laptop Price Dataset (Project 2) | Used Pandas for Data Manipulation | Created Visuals with Matplotlib and Seaborn | Demonstrated Advanced Python Techniques with GPT

Class 34 – Introduction to Excel | Interface, Navigation | Cell Referencing | Basic & Text Functions | 3D Referencing | Practical Examples

Power BI Project: Oodles of Noodles

Class 35 – Text Functions | Logical Functions | Nested IFs | Practical Applications of Text Extraction and Conditional Logic

Class 36 – Conditional Functions | Syntax and Use | Practical Applications for Conditional Calculations and Aggregations

Class 37 – Lookup Functions | Syntax and Use | Handling Errors | Practical Tips for Efficient Data Lookup

Class 38 – INDEX MATCH | XLOOKUP | Power Query

Class 39 – Pivot Tables | Power Pivot

Class 40 –

Class 41 –