Professional Diploma in Data Analytics
Curriculum
-
Introduction to Oracle Database :
-
List the features of Oracle Database 11g
-
Save queries to files and use script files in SQL Developer
-
Retrieve Data using the SQL SELECT Statement
-
List the capabilities of SQL SELECT statements
-
Generate a report of data from the output of a basic SELECT statement
-
Select All Columns
-
Select Specific Columns
-
Use Arithmetic Operators
-
Understand Operator Precedence
-
Learn the DESCRIBE command to display the table structure
-
Learn to Restrict and Sort Data
-
Write queries that contain a WHERE clause to limit the output retrieved
-
Describe the rules of precedence for comparison and logical operators
-
Sort output in descending and ascending order
-
Manipulate numbers with the ROUND, TRUNC, and MOD functions
-
Perform arithmetic with date data
-
Manipulate dates with the DATE functions
-
Invoke Conversion Functions and Conditional Expressions
-
Describe implicit and explicit data type conversion
-
Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions
-
Aggregate Data Using the Group Functions
-
Use the aggregation functions in SELECT statements to produce meaningful reports
-
Divide the data in groups by using the GROUP BY clause
-
Exclude groups of date by using the HAVING clause
-
Display Data From Multiple Tables Using Joins
-
Write SELECT statements to access data from more than one table
-
View data that generally does not meet a join condition by using outer joins
-
Cross Join
-
Equi Join
-
Non Equi Join
-
Outer Join
-
Left outer Join
-
Right Outer Join
-
Data Manipulation Statements
-
Describe each DML statement
-
Insert rows into a table
-
Change rows in a table by the UPDATE statement
-
Delete rows from a table with the DELETE statement
-
Save and discard changes with the COMMIT and ROLLBACK statements
-
Explain read consistency
-
Categorize the main database objects
-
Review the table structure
-
List the data types available for columns
-
Create a simple table
-
Decipher how constraints can be created at table creation
-
Describe how schema objects work
-
Use of DDL Statements to Create and Manage Tables
-
Control User Access
-
Differentiate system privileges from object privileges
-
Create Users
-
Create and Grant Privileges to a Role
-
Change Your Password
-
Grant Object Privileges
-
How to pass on privileges?
-
Revoke Object Privileges
-
Microsoft Excel Basics
-
Python Training Modules
-
Introduction
-
Data Types & Variables
-
Python Operators
-
Python Strings
-
Python Lists
-
Python Tuples
-
Python Sets
-
Python Dictionary
-
If Else Statement
-
While Loop
-
For Loop
-
Functions
-
Recursions
-
Lambda
-
Object Oriented Programming
-
Inheritance(OOP)
-
Math Functions
-
Python Modules
-
Python Modules
-
File Handling
-
JSON
-
Pandas
-
Numpy
-
Advance OOPS Concept
-
Abstract
-
Polymorphism
-
Encapsulation
-
Database Connectivity Using(Pandas)&(Psycopg)
-
Server side scripting
-
Data Frame
-
Matplotlib
-
SciPy
-
JupyterNote
-
Microsoft Power BI Desktop Visualisation
-
Business Intelligence Basics
-
What is BI ?
-
Different BI Tools
-
Advantages of BI
-
Applications and Future of BI
-
Overview of BI and Data Integration Products
-
Opportunities/ Scope of BI
-
What is a Data Warehouse?
-
Data Warehousing Schemas
-
Dimensions and Fact Table types
-
Modeling Types
-
Star and Snow Flake Examples and differences
-
PBI Architecture Overview
-
Microsoft Power BI Desktop
-
Overview of Power BI
-
Introduction to Tools and Terminology.
-
Different components of PBI
-
Downloading and installation of PBI Desktop
-
An overview of the interface
-
Introducing 3 views of PBI
-
Different connection options
-
Connecting to Microsoft Excel
-
Connecting to Oracle Database
-
Connecting to CSV files
-
Different method of extracting data
-
Power Query Editor (ETL Tool)
-
Overview of Power Query Editor (cleaning up messy data)
-
Transform Data
-
Pivot and Unpivot tables
-
Adding columns
-
Text functions
-
Number functions
-
Date and Time functions
-
Grouping Data
-
Data Profiling
-
Create custom date table using MCode Method
-
Combining schemas for modeling
-
Refreshing Option
-
Visualization and report
-
Overview: Visualizations
-
Using visualizations
-
Overview: Power BI data sources
-
Upload Power BI data sources
-
Basic charts in Power BI
-
Creating basic visuals
-
Formatting visuals and pages
-
Using Themes and Import Custom Themes from Gallery.
-
Inserting images to our report
-
How to set up your data model – Setup and Manage relationships
-
Sort, copy, and paste visualizations
-
Creating hierarchy
-
Grouping data
-
Setting interactions between visuals
-
Using Various types of graphs
-
Using Slicers to filter the data.
-
Using Filters
-
Using Tool Tips at Page Level and Field Level
-
Conditional Formatting in Tables and Graphs.
-
Parameter settings
-
Using Buttons and Actions
-
Creating Bookmarks with Various actions
-
Selection option
-
Ask a Questions to create Custom visuals by Using Q&A
-
Familiarizing different AI visuals
-
Using Market Place to add Custom visuals to Visualizations
-
Use Scrollers and Hierarchy Slicers from Market Place
-
Download and use different custom visuals from the gallery
-
Sample Reports using Database Tables
-
DAX
-
What is DAX?
-
Why we use DAX?
-
Basic DAX functions :- SUM, SUMX, CALCULATE…..
-
Time intelligence functions :- SAMEPERIODLASTYEAR, DATEADD
-
Text functions :- CONTAINS, STARTSWITH, ENDSWITH…
-
Mathematical functions :- DIFF, DIVIDE…
-
Aggregate functions :- MIN, MAX, AVG
-
Logical functions :- IF, OR, AND, NOT
-
Count functions :- COUNT, DISTINCTCOUNT
-
Information functions :-ODD, EVEN, RANKX
-
Filter functions :- FILTER, ALL, ALLSELECTED
-
Inter and Intra column operation :- RELATED,SUMMARIZE,SUMMRIZECOULMN
-
Data handling with tables
-
Variables
-
Conditional operation
-
Visualizing DAX Calculations.
-
Difference between Measures and Quick Measures
-
How to organize all the measures
-
Reports and Dashboards
-
How to save a report
-
Modify and Print a Report
-
Rename, hide and delete report pages
-
Send a report to PowerPoint
-
Introducing Power BI Service
-
Publish reports to Power BI Service
-
Creating Dashboards
-
Create and manage dashboards
-
Pin a report tile to a dashboard
-
Pin a live report page to a dashboard
-
Pin a tile from another dashboard
-
Build a dashboard with Quick Insights
-
Interacting with your Dashboards
-
Sharing Dashboards and Reports.
-
Manage published reports
-
Updating report options
-
Advanced Topics
-
Calculated Columns
-
Calculated Tables
-
Variables
-
KPI visual
-
ArcGIS maps
-
AI Visuals
-
Analytics Pane
-
Performance Analyser
-
RLS / Data Level Security and OLS (Overview Tabular)
-
Integration with Python and R – Overview
-
Data Science Essentials
-
JIRA Essentials
-
Introduction to Oracle Database :
- List the features of Oracle Database 11g
- Save queries to files and use script files in SQL Developer
- Retrieve Data using the SQL SELECT Statement
- List the capabilities of SQL SELECT statements
- Generate a report of data from the output of a basic SELECT statement
- Select All Columns
- Select Specific Columns
- Use Arithmetic Operators
- Understand Operator Precedence
- Learn the DESCRIBE command to display the table structure
- Learn to Restrict and Sort Data
- Write queries that contain a WHERE clause to limit the output retrieved
- Describe the rules of precedence for comparison and logical operators
- Sort output in descending and ascending order
- Manipulate numbers with the ROUND, TRUNC, and MOD functions
- Perform arithmetic with date data
- Manipulate dates with the DATE functions
- Invoke Conversion Functions and Conditional Expressions
- Describe implicit and explicit data type conversion
- Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions
- Aggregate Data Using the Group Functions
- Use the aggregation functions in SELECT statements to produce meaningful reports
- Divide the data in groups by using the GROUP BY clause
- Exclude groups of date by using the HAVING clause
- Display Data From Multiple Tables Using Joins
- Write SELECT statements to access data from more than one table
- View data that generally does not meet a join condition by using outer joins
- Cross Join
- Equi Join
- Non Equi Join
- Outer Join
- Left outer Join
- Right Outer Join
- Data Manipulation Statements
- Describe each DML statement
- Insert rows into a table
- Change rows in a table by the UPDATE statement
- Delete rows from a table with the DELETE statement
- Save and discard changes with the COMMIT and ROLLBACK statements
- Explain read consistency
- Categorize the main database objects
- Review the table structure
- List the data types available for columns
- Create a simple table
- Decipher how constraints can be created at table creation
- Describe how schema objects work
- Use of DDL Statements to Create and Manage Tables
- Control User Access
- Differentiate system privileges from object privileges
- Create Users
- Create and Grant Privileges to a Role
- Change Your Password
- Grant Object Privileges
- How to pass on privileges?
- Revoke Object Privileges
-
Microsoft Excel Basics
-
Python Training Modules
- Introduction
- Data Types & Variables
- Python Operators
- Python Strings
- Python Lists
- Python Tuples
- Python Sets
- Python Dictionary
- If Else Statement
- While Loop
- For Loop
- Functions
- Recursions
- Lambda
- Object Oriented Programming
- Inheritance(OOP)
- Math Functions
- Python Modules
- Python Modules
- File Handling
- JSON
- Pandas
- Numpy
- Advance OOPS Concept
- Abstract
- Polymorphism
- Encapsulation
- Database Connectivity Using(Pandas)&(Psycopg)
- Server side scripting
- Data Frame
- Matplotlib
- SciPy
- JupyterNote
-
Microsoft Power BI Desktop Visualisation
- Business Intelligence Basics
- What is BI ?
- Different BI Tools
- Advantages of BI
- Applications and Future of BI
- Overview of BI and Data Integration Products
- Opportunities/ Scope of BI
- What is a Data Warehouse?
- Data Warehousing Schemas
- Dimensions and Fact Table types
- Modeling Types
- Star and Snow Flake Examples and differences
- PBI Architecture Overview
- Microsoft Power BI Desktop
- Overview of Power BI
- Introduction to Tools and Terminology.
- Different components of PBI
- Downloading and installation of PBI Desktop
- An overview of the interface
- Introducing 3 views of PBI
- Different connection options
- Connecting to Microsoft Excel
- Connecting to Oracle Database
- Connecting to CSV files
- Different method of extracting data
- Power Query Editor (ETL Tool)
- Overview of Power Query Editor (cleaning up messy data)
- Transform Data
- Pivot and Unpivot tables
- Adding columns
- Text functions
- Number functions
- Date and Time functions
- Grouping Data
- Data Profiling
- Create custom date table using MCode Method
- Combining schemas for modeling
- Refreshing Option
- Visualization and report
- Overview: Visualizations
- Using visualizations
- Overview: Power BI data sources
- Upload Power BI data sources
- Basic charts in Power BI
- Creating basic visuals
- Formatting visuals and pages
- Using Themes and Import Custom Themes from Gallery.
- Inserting images to our report
- How to set up your data model – Setup and Manage relationships
- Sort, copy, and paste visualizations
- Creating hierarchy
- Grouping data
- Setting interactions between visuals
- Using Various types of graphs
- Using Slicers to filter the data.
- Using Filters
- Using Tool Tips at Page Level and Field Level
- Conditional Formatting in Tables and Graphs.
- Parameter settings
- Using Buttons and Actions
- Creating Bookmarks with Various actions
- Selection option
- Ask a Questions to create Custom visuals by Using Q&A
- Familiarizing different AI visuals
- Using Market Place to add Custom visuals to Visualizations
- Use Scrollers and Hierarchy Slicers from Market Place
- Download and use different custom visuals from the gallery
- Sample Reports using Database Tables
- DAX
- What is DAX?
- Why we use DAX?
- Basic DAX functions :- SUM, SUMX, CALCULATE…..
- Time intelligence functions :- SAMEPERIODLASTYEAR, DATEADD
- Text functions :- CONTAINS, STARTSWITH, ENDSWITH…
- Mathematical functions :- DIFF, DIVIDE…
- Aggregate functions :- MIN, MAX, AVG
- Logical functions :- IF, OR, AND, NOT
- Count functions :- COUNT, DISTINCTCOUNT
- Information functions :-ODD, EVEN, RANKX
- Filter functions :- FILTER, ALL, ALLSELECTED
- Inter and Intra column operation :- RELATED,SUMMARIZE,SUMMRIZECOULMN
- Data handling with tables
- Variables
- Conditional operation
- Visualizing DAX Calculations.
- Difference between Measures and Quick Measures
- How to organize all the measures
- Reports and Dashboards
- How to save a report
- Modify and Print a Report
- Rename, hide and delete report pages
- Send a report to PowerPoint
- Introducing Power BI Service
- Publish reports to Power BI Service
- Creating Dashboards
- Create and manage dashboards
- Pin a report tile to a dashboard
- Pin a live report page to a dashboard
- Pin a tile from another dashboard
- Build a dashboard with Quick Insights
- Interacting with your Dashboards
- Sharing Dashboards and Reports.
- Manage published reports
- Updating report options
- Advanced Topics
- Calculated Columns
- Calculated Tables
- Variables
- KPI visual
- ArcGIS maps
- AI Visuals
- Analytics Pane
- Performance Analyser
- RLS / Data Level Security and OLS (Overview Tabular)
- Integration with Python and R – Overview
-
Data Science Essentials
-
JIRA Essentials
Overview
Tools Covered
Are you ready to dive into the world of Data Analytics and unlock new career opportunities? Asquare Technologies offers a meticulously designed Data Analytics course that equips you with the essential skills to thrive in today’s data-driven world. This course covers key tools and techniques that are highly sought after in the industry.
What You’ll Learn:
⦁ Database Management: Master the fundamentals of databases, including SQL, to efficiently store, retrieve, and manipulate data. You’ll learn how to structure and query databases, an essential skill for any data analyst.
⦁ Excel for Data Analysis: Gain proficiency in Excel, the go-to tool for data analysis in many industries. Learn advanced functions, data manipulation techniques, and how to create dynamic dashboards to visualize your data.
⦁ Power BI: Develop your data visualization skills with Power BI. You’ll learn how to transform raw data into actionable insights, create interactive reports, and share them with your team to drive better decision-making.
⦁ Python Programming: Python is the backbone of many data analytics and data science projects. This course covers Python basics, data manipulation with libraries like Pandas, and how to leverage Python for data analysis tasks.
Certification
LET'S TALKFeel Free to Speak With Our Executive
Tools Covered
Are you ready to dive into the world of Data Analytics and unlock new career opportunities? Asquare Technologies offers a meticulously designed Data Analytics course that equips you with the essential skills to thrive in today’s data-driven world. This course covers key tools and techniques that are highly sought after in the industry.
What You’ll Learn:
⦁ Database Management: Master the fundamentals of databases, including SQL, to efficiently store, retrieve, and manipulate data. You’ll learn how to structure and query databases, an essential skill for any data analyst.
⦁ Excel for Data Analysis: Gain proficiency in Excel, the go-to tool for data analysis in many industries. Learn advanced functions, data manipulation techniques, and how to create dynamic dashboards to visualize your data.
⦁ Power BI: Develop your data visualization skills with Power BI. You’ll learn how to transform raw data into actionable insights, create interactive reports, and share them with your team to drive better decision-making.
⦁ Python Programming: Python is the backbone of many data analytics and data science projects. This course covers Python basics, data manipulation with libraries like Pandas, and how to leverage Python for data analysis tasks.
Certification
LET'S TALK
Feel Free to Speak With Our Executive
Instructor
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