Eligibility: IT Professionals / Exposure to Information Technology
Diploma In Data Analytics
About Profound Data Analytics Course
Data Analytics analyses historical data to provide actionable insights for immediate decision-making. It deals with descriptive analysis, summarizing past events and explaining why they occurred. It typically addresses welldefined and tactical problems related to operational efficiency and immediate decision-making.
Data analysts should be proficient in data manipulation using tools like SQL for database querying and data extraction and tools like Excel for data cleaning and transformation.
Duration: 2.5 Months
- What is Data Analytics?
- Difference between Data Science and Data Analytics
- Predictive Analytics
- Prescriptive Analytics
- Diagnostic Analytics
- Descriptive Analytics
- Perform basic spreadsheet tasks
- ◦ viewing, entering and editing data, and moving, copying
- Cleaning & wranggling data
- ◦ remove duplicate and inaccurate data, Remove empty rows, manipulate and standardize data using Text to Coumn feature, use the Flash Fill
- Conditional Formatting
- Functions
- ◦ CONCATINATE, LEN, TRIM, COUNTA, AGGREGATEIFS,
- ◦ SUMIF, COUNTIF
- Fundamentals of analyzing data using filter and sort data.
- Pivot Tables
- HLOOKUP, VLOOKUP
- What-if analysis
- Charts
- Descriptive Statistics
- ◦ Annova, Regression
- Create DB, Drop DB
- Create Table, Drop Table, Alter Table
- Data Types
- Constraints, Not Null, Unique
- Primary Key, Foreign Key
- Create Index
- Auto Increment
- Dates
- Views
- SQL -SELECT, WHERE, AND, OR, NOT, ORDER BY, INSERT INTO, NULL Values, UPDATE, DELETE, LIMIT, MIN and MAX, COUNT, AVG, SUM, LIKE, Wildcards IN BETWEEN, Aliases Joins - INNER JOIN, LEFT JOIN, RIGHT JOIN, CROSS JOIN, Self Join, UNION, GROUP BY HAVING EXISTS ANY ALL INSERT SELECT CASE Null Functions, Comments, Operators, Functions
- Introduction to Python Programming
- Installation & working
- Basic Operators, Data types, Variables
- Control Statements & Conditional Looping
- Functions
- Collections in Python
- Object Oriented Programming
- Modules and Packages
- String
- File Handling
- Exception Handling
- Multi-threading
- Regular Expressions
- NumPy
- Introduction, installation
- 1D & 2D arrays
- Array indexing – slicing & advance
- Operations – Arithmetic, Logical, Math, String, Statistical, Set, Broadcasting
- Pandas
- Introduction, installation
- Series – Creation, indexing, slicing, attributes & functions
- Dataframes – Creation, operations, merging dataframes, Concatenate dataframes, binary operations
- Data input and output
- Matplotlib
- Introduction, installation
- Data Visualization
- Plots – single line, multiple line
- Grid axes
- Labels, color line markers
- Various different Data sources and Connections in Power BI
- Query editor in Power BI
- Transform data in Query editor
- Joining data
- Data interpretations
- Manage data relationship
- Change data source connectivity
- Create calculated measures and filter at data level
- Modeling data
- Why DAX
- DAX Syntax
- Data types in DAX
- Types of calculations
- DAX tables and Filtering
- DAX queries
- DAX Parameters
- Analytics calculations
- Chart types in Power BI
- Map Visualizations
- Color palettes in Charts
- Loading Shapes, text boxes, and images
- Custom visuals
- Z-Order
Batch Schedule
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Why Full Stack Web Developer Course at Profound is Different than other Classes in Pune ?
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