Data Analytics Course Syllabus
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With our syllabus of data analytics, you will acquire the fundamentals of Java programming, hone your practical programming skills, and build a solid basis for creating scalable and reliable Java applications. Classes, objects, inheritance, polymorphism, and abstraction are among the core ideas of object-oriented programming (OOP) that are covered in our course outline for data analytics. In addition to gaining practical experience developing, compiling, and running Java programs, they will build a strong basis for future Java programming coursework.
Course Syllabus
Download SyllabusCORE PYTHON
- Python Introduction & history
- Color coding schemes
- Salient features & flavors
- Application types
- Language components
- String handling management
- String operations – indexing, slicing, ranging
- String methods – concatenation, repetition, formatting
- Supporting functions
- Native data types
- List
- Tuple
- Set
- Dictionary
- Decision making statements
- If
- If…else
- If…elif…else
- Looping statements
- For loop
- While loop
- Function types
- Built-in functions
- Math functions
- User defined functions
- Recursive functions
- Lambda functions
- OOPs
- Classes and objects
- init constructor
- Self-keyword
- Data abstraction
- Data encapsulation
- Polymorphism
- Inheritance
- Exception handling
- Error vs exception
- Types of error
- User defined exception handling
- Exception handler components
- Try block, except block, finally block
POWER BI INTRODUCTION
- Data Visualization
- Reporting Business Intelligence (BI)
- Traditional BI
- Self-Serviced BI Cloud Based BI
- On Premise BI
- Power BI Products
- Power BI Desktop (Power Query, Power Pivot, Power View)
- Flow of Work in Power BI Desktop
- Power BI Report Server
- Power BI Service, Power BI Mobile
- Power BI Architecture
- A Brief History of Power BI
POWER QUERY
- Data Transformation
- Benefits of Data Transformation
- Shape or Transform Data using Power Query
- Overview of Power Query / Query Editor
- Query Editor User Interface
- The Ribbon (Home, Transform, Add Column, View Tabs)
- The Queries Pane
- The Data View / Results Pane
- The Query Settings Pane, Formula
- Bar Saving the Work
- Data types
- Changing the Data type of a Column Filters in Power Query
- Auto Filter / Basic Filtering Filter a Column using
- Text Filters Filter a Column using Number Filters
- Filter a Column using Date Filters Filter Multiple Columns
- Remove Columns / Remove Other Columns Name
- Rename a Column Reorder Columns or Sort Columns
- Add Column / Custom Column Split Columns Merge
- Columns PIVOT, UNPIVOT Columns Transpose Columns
- Header Row or Use First Row as Headers Keep Top Rows
- Keep Bottom Rows Keep Range of Rows Keep Duplicates
- Keep Errors Remove Top Rows
- Remove Bottom Rows
- Remove Alternative Rows
- Remove Duplicates, Remove Blank Rows
- Remove Errors Group Rows / Group By
M LANGUAGE
- IF..ELSE Conditions
- TransformColumn()
- RemoveColumns()
- SplitColumns()
- ReplaceValue()
- Table.Distinct() Options and GROUP BY Options
- Table.Group()
- Table.Sort() with Type Conversions
- PIVOT Operation and Table.Pivot ().
- List Functions Using Parameters with M Language
DATA MODELING
- Data Modeling Introduction Relationship
- Need of Relationship Relationship Types
- Cardinality in General
- One-to-One
- One-to-Many
- Many-to-One
- Many-to-Many
- AutoDetect the relationship
- Create a new relationship
- Edit existing relationships
- Make Relationship Active or Inactive
- Delete a relationship
DAX
- What is DAX
- Calculated Column, Measures
- DAX Table and Column Name Syntax
- Creating Calculated Columns
- Creating Measures
- Calculated Columns Vs Measures
- DAX Syntax & Operators
- Types of Operators
- Arithmetic Operators
- Comparison Operators
- Text Concatenation Operator
- Logical Operators
DAX FUNCTIONS TYPES
- Date and Time Functions
- YEAR, MONTH,DAY
- WEEKDAY, WEEKNUM FORMAT (Text Function)
- Month Name, Weekday Name
- IF
- TRUE, FALSE NOT,
- OR, IN, AND
- Text Function
- LEN, CONCATENATE
- LEFT, RIGHT, MID UPPER
- LOWER TRIM, SUBSTITUTE, BLANK
- Logical Functions
- IF TRUE, FALSE NOT
- OR, IN, AND IF ERROR SWITCH
- Math & Statistical Functions
- INT ROUND, ROUNDUP
- ROUNDDOWN
- DIVIDE EVEN, ODD
- POWER, SIGN SQRT
- FACT SUM, SUMX MIN, MINX MAX
- MAXX COUNT,
- COUNTX AVERAGE
- AVERAGEX COUNTROWS
- COUNTBLANK
REPORT VIEW
- Report View User Interface
- Fields Pane
- Visualizations pane
- Ribbon, Views, Pages Tab
- Canvas Visual Interactions Interaction Type (Filter, Highlight, None)
- Visual Interactions Default Behavior, Changing the Interaction
- Grouping and Binning Introduction
- Using grouping, Creating Groups on Text Columns
- Using binning, Creating Bins on Number Column and Date Columns
- Sorting Data in Visuals
- Changing the Sort Column
- Changing the Sort Order
- Sort using column that is not used in the Visualization
- Sort using the Sort by Column button
- Hierarchy Introduction
- Default Date Hierarchy
- Creating Hierarchy
- Creating Custom Date Hierarchy
- REPORT VIEW
- Change Hierarchy Levels
- Drill-Up and Drill-Down Reports
- Data Actions, Drill Down, Drill Up, Show Next Level
- Expand Next Level Drilling filters other visuals option
VISUALIZATIONS
- Visualizing Data
- Why Visualizations
- Visualization types
- Create and Format Bar and Column Charts
- Create and Format Stacked Bar Chart
- Stacked Column Chart
- Create and Format Clustered Bar Chart
- Clustered Column Chart
- Create and Format 100% Stacked Bar Chart 100% Stacked Column Chart
- Create and Format Pie and Donut Charts
- Create and Format Scatter Charts
- Create and Format Table Visual
- Matrix Visualization
- Line and Area Charts
- Create and Format Line Chart, Area Chart
- Stacked Area Chart Combo Charts
- VISUALIZATIONS
- Create and Format Line and Stacked Column Chart
- Line and Clustered Column Chart
- Create and Format Ribbon Chart
- Waterfall Chart, Funnel Chart
POWER BI SERVICE
- Power BI Service Introduction
- Power BI Cloud Architecture
- Creating Power BI Service Account
- SIGN IN to Power BI Service Account
- Publishing Reports to the Power BI service
- Import / Getting the Report to PBI Service
- My Workspace / App Workspaces Tabs
- DATASETS, WORKBOOKS, REPORTS & DASHBOARDS
- Working with Datasets Creating Reports in Cloud using Published
- Datasets
- Creating Dashboards Pin Visuals and Pin LIVE
- Report Pages to Dashboard
- Advantages of Dashboards Interacting with
- Dashboards
- Formatting Dashboard, Sharing Dashboard
ADVANCED PANDAS FUNCTIONS
- Group by()
- Pivot tables()
- Multi-indexing()
- merge()
- concatenate()
- join()
- data transformation using apply()
- map()
- query()
- Resampling time series functionality
- excel writer()
- pipe()
- creating dataframes
- reading CSV files with intrinsic index
- converting CSV files to dataframes
- converting dataframes to CSV files
- converting dataframes to excel file
ADVANCED SQL FUNCTIONS
- Common Table Expressions (CTE)
- Recursive CTE’s
- temporary functions
- pivoting data with sum() and CASE WHEN
- Except vs Not in
- self joins, rank vs dense_rank vs row number
- ranking data
- calculating delta values,
- multiple groupings using rollup
- calculating running totals
- computing a moving average
- date time manipulations
- Formatting strings, stored methods
- JOINS
- Sub Queries
- Manipulation of date and time
- procedural data storage
- Connecting SQL to Python or R language, window Functions
PROJECT
- Project1 – Product Sales Analysis – Power BI Project and review
- Project2 – Financial Performance Analysis – Power BI Project and review
- Project3 – Health care sales Analysis –
- Intermediate Power BI project and review
- Project4 – Anamoly detection in Credit card transactions – Intermediate Power BI project and review
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