Data Analysis and Business Intelligence with Python & SQL

Name: Data Analysis and Business Intelligence with Python & SQL
Rating: 3.8 (77 reviews)

Practical Data Analytics & Business Intelligence with: SQL Matplotlib Python Excel Power BI Pandas

Created byAkhil Vydyula

Last updated 7/2024

English

What you'll learn

Core SQL - the INTO statement for creating new tables and using the CASE statement to compute new columns based on conditions
Intermediate SQL - using window functions such as ROW_NUMBER, RANK, PARTITION, and learning running totals to increase the functionality of datasets
Perform Data Analysis with Microsoft SQL
Intermediate SQL - understanding the importance of subquerying, views, and variables in SQL data analysis as well as the importance of stored procedures
Core SQL - the SQL interface, navigation, importing data for analysis

Course content

6 sections • 26 lectures • 10h 25m total length

Course Content - Became a Data Analyst or Business Analyst4:24
Become a data analyst or business analyst by mastering Python & SQL, Power BI, Excel, and statistics to derive insights from raw data and inform business decisions.
How Not to Learn Data Analytics Tools5:54
avoid common mistakes when learning data analytics tools, from biased samples and vague goals to misinterpreting correlation and causation; explore descriptive, predictive, and prescriptive analytics with Excel, SQL, and Python.

Introduction to SQL - SQL Syntax and Download MySQL8:17
RDBMS - Data Integrity, Database Normalization22:15
Data Definition Language (DDL)22:15
Explore data definition language (DDL) concepts in SQL, including creating and altering tables, constraints, primary keys, data types, and referential integrity. Learn practical basics of relational design.
Data Manipulation language (DML)19:32
Data Control Languages (DCL) and Domain Constraints23:10
Explore data control languages and domain constraints, detailing commit, rollback, savepoint, and grant or revoke permissions, plus domain, key, and check constraints to preserve data integrity.
Filtering Data and SET Operators in SQL21:31
Explore primary keys and foreign keys, including composite keys, and learn how to join tables, enforce constraints, and use set operators such as union, intersect, truncate, and delete in SQL.
Conditional Expressions in SQL23:45
Grouping Data29:21
Joining Multiple Tables (JOINS)16:43
SQL RANK Functions18:47
Explore sql rank functions, including rank, dense_rank, and row_number, and how partition by and order by affect rankings. Learn to create and manage views and briefly cover triggers.
SQL Triggers and Stored Procedures31:16
Explore sql triggers and stored procedures to automate queries, log salary changes with triggers, and manage before or after events on tables; learn subqueries, indexing basics, and procedural reuse.

Python - Data Structures (Lists, Tuple, Dictionary) and String Manipulations51:51
Explore core Python data structures: lists, tuples, dictionaries, and sets, and master string manipulations, including indexing, slicing, searching, and tokenization for data analysis tasks.
Python - Implementation Of Lambda, Recursion, Functions.50:47
Python - Understand Of Libraries,Exploratory Data Analysis,Descriptive Analysis44:38

Installation Power BI Desktop and Applications of Power BI26:27
Understand the Concepts of Maps using Power BI14:11
Power BI - Tables and Matrix27:31
Learn to build and format Power BI tables and matrix visuals to summarize orders data with sales, profit, and quantity, using filters, aggregations, drill-downs, and conditional formatting.
Different Types of Power BI Slicers22:26
Learn to build and tailor Power BI slicers by region, city, and date hierarchies, including single or multiple select and orientation options, to enhance dashboards.
Introduction to Power Query21:49
Hands on with Power Query Operations19:05
Manipulations with Power Query Operations14:52
Build a Super Store Sales Data Analysis Dashboard24:17

Requirements

Computer and internet access required
Basic knowledge of excel advised but not mandatory
No need to even have SQL Server downloaded in advance, as we'll show you how to get it installed for free!
None - we will walk you through from an absolute beginner level! No prior knowledge of SQL or PowerBI required

Description

In business, being able to understand, harness, and use data is no longer a skill reserved for a handful of well-paid analysts. It's becoming an essential part of many roles.

If that sounds daunting, don't worry. There is a growing set of tools designed to make data analysis accessible to everyone, in this huge-value, four-course Data Analysts Toolbox bundle we look in detail at three of those tools: Excel, Python, and Power BI.

In isolation Excel, Python, and Power BI are useful and powerful. Learn all three and you are well on your way to gaining a much deeper understanding of how to perform complex data analysis.

This Data Analysts Toolbox bundle is aimed at intermediate Excel users who are new to Python and Power BI. All courses include practice exercises so you can put into practice exactly what you learn.

What Can SQL do?

SQL can execute queries against a database
SQL can retrieve data from a database
SQL can insert records into a database
SQL can update records in a database
SQL can delete records from a database
SQL can create new databases
SQL can create new tables in a database
SQL can create stored procedures in a database
SQL can create views in a database
SQL can set permissions on tables, procedures, and views

Power BI

What is Power BI and why you should be using it?
To import CSV and Excel files into Power BI Desktop.
How to use Merge Queries to fetch data from other queries.
How to create relationships between the different tables of the data model.
All about DAX including using the COUTROWS, CALCULATE, and SAMEPERIODLASTYEAR functions.
All about using the card visual to create summary information.
How to use other visuals such as clustered column charts, maps, and trend graphs.
How to use Slicers to filter your reports.
How to use themes to format your reports quickly and consistently.
How to edit the interactions between your visualizations and filter at visualization, page, and report level.

Who this course is for:

For those who are interested in Data Analytics and a gateway into Data Science
Beginner Business Intelligence Analyst
Students who are willing to put in a couple of hours to learn about analytics
For those who are new and curious about SQL & Power BI
Beginner Data Scientist

Data Analysis and Business Intelligence with Python & SQL

What you'll learn

Explore related topics

Course content

Introduction to Data Analytics - BI and SQL Tools2 lectures • 10min

Structured Query Language (SQL)11 lectures • 3hr 57min

Capstone Project : Data Analytics on Movie Reviews in SQL1 lecture • 38min

PYTHON - Introduction to Basics of Python for Beginners3 lectures • 2hr 27min

Microsoft Power BI (Business Intelligence Tool)8 lectures • 2hr 51min

Capstone Project - Sales and Production Analysis1 lecture • 22min

Requirements

Description

Who this course is for: