Report on Student Survey
A survey was conducted among many stores, in which data based on students, i.e., how much they are spending on different kinds of purchases, such as video games, indoor games, toys, books, gadgets, etc., was collected. You have to create a Full Stack Power BI report. You will get hands-on experience in Tabular visualization, matrix visualization, funnel chart, pie chart, scatter plot, SandDance plot, etc.
Case Study 1 - Full Stack Power BI Desktop, Cloud Service, and End-to-end Workflow
The case study deals with ways to design a dashboard with a basic set of visualizations and deploy it on the Full Stack Power BI cloud service. Further, a brief top-level overview of Transport Corp Data is shown using aggregated key performance indicators (KPIs), trends, Gio distributions, and filters.
Case Study 2 - Visualizations, Configuring Extended Properties, and Data Calculations DAX - Introduction
This case study explains the way to design a dashboard and perform calculations by making use of Full Stack Power BI DAX formulas. The scheduled deliveries of loads are analyzed
using correlation across measures. Moreover, drill-up/drill-down capabilities and reference lines are implemented.
Case Study 3 - Combination Visualizations for Correlated Value Columns
Here, the dashboard is designed by making use of Full Stack Power BI DAX formulas to perform calculations. Bucketed categories are created to represent value measures on the categories axis. Furthermore, a scatter plot is used to identify outliers or outperformers.
Case Study 4 - Data Transformations
The case study involves designing an audit dashboard by making use of Power Query and using Query Editor to perform data modeling by applying data transformations, in turn, by managing relationships.
Case Study 5 - Data Transformations (Cont.)
Here, the dashboard is designed to analyze the trend of admissions into a State University. Query Editor is used to perform data modeling by applying transformations, such as append data, split data, column formatting, transpose table, pivot/unpivot, fill columns, merge join, conditional columns, index columns, and summary tables.
DDL (Data Definitions Language) Commands
Goal: Data Definition Commands define the syntax of a database and manipulate database objects.
Module Objectives:
- RDBMS (Relational Database Management System) Introduction
- Normalization in RDBMS
- Create database objects i.e. Create Table
- Delete database objects i. e. Delete Database
- Alter database objects i.e. Change Column Name
- Create, alter and delete constraints
Topics :
Relation Database Management System (RDBMS)
- Normalization
- Create Database objects
- Data Types in SQL
- Alter Table Statements
- Drop-Table Statements
- Various Constraints
- Creating Views
Hands-on/Demo/Use-case:
- Create Table With Predefine Columns
- Add New Column to Existing Table
- Check the constraints on a table
- Add Primary key and Foreign Key on Table
- Remove Unique Constraint
- ODML (Data Manipulation Language) Commands
- Retrieve data from multiple tables
- Inbuilt Functions in SQL
- Create Advance database objects
What is BI?
- Introduction to Business Intelligence
- understanding the concept of Data Modeling
- Data Cleaning
- learning about Data Analysis
- Data Representation
- Data Transformation
ETL Overview
- Introduction to ETL
- The various steps involved Extract, Transform, Load
- Using a user's email ID to read a flat file
- Extracting the user ID from the email ID
- Loading the data into a database table.
Working with Connection Managers
- Introduction to Connection Managers
- Logical representation of a connection
- The various types of Connection Managers
- Flat file, database, understanding how to load faster with OLE DB
- Comparing the performance of OLE DB and ADO.net
- Learning about Bulk Insert
- Working with Excel Connection Managers and identifying the problems
Working with Connection Managers
- Introduction to Connection Managers
- Logical representation of a connection
- The various types of Connection Managers
- Flat file, database, understanding how to load faster with OLE DB
- Comparing the performance of OLE DB and ADO.net
- Learning about Bulk Insert
- Working with Excel Connection Managers and identifying the problems