Store and Process Project Data and Big Data. From Excel to MySQL and Spark. 📚 8 Lessons

Distributed Data Storage. Quick start guide to MySQL and Spark.

Enrolment validity: 0 day

~~€119.00~~ €59.00

Description

In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic “Big data and machine learning”.

🎓 In this part we will consider the main options for storing big data.

✔️ In practical lesson we will install the MySQL server on computer and learn how to work and edit MySQL databases.
In the fifth lesson we will take one regular exel table and transfer the information from this table to the MySql server.

✔️ Then we will install the spark in order to work with datasets in a distributed manner.Then, to process the distributed data, we export the data from MySQL into spark. And with the help of Jupiter Notebook, we prepare the data for visualization of this data.

✏️ In this course, you will be guided through the basics of using:

Spark
MySQL
Jupyter Notebook
Spark

🔎 Topics covered in this course:

📝 Lecture 2. Big Data Storage. Three ways to store digital data.

What is big data?
What storage options we have today?
Public Cloud and Private Cloud.
Distribute you data

📝 Lecture 3. MySql. SQL. Introduction. How it works?

What is MySQL?
How Does MySQL Work?
Why is MySQL so Popular?

📝 Lecture 4. Installing and Launching MySQL Workbench. How to Get Started with MySQL Workbench

MySQL server setup
Initial settings
Getting Started with MySQL

📝 Lecture 5. Practice. Excel table into MySql. Import Excel data into a MySQL database.

Import Excel data into a MySQL
Create a new MySQL table.
Most Common Queries.
SELECT, DROP, UPDATE query mysql

📝 Lecture 6. Spark. Hadoop. Data’s Distribution. A Storage System for Big Data.

What is Hadoop?
Spark vs MySql
Spark. Analytics engine for big data processing

📝 Lecture 7. Installing and Launching Apache Spark. Download and Get Started.

Installing Apache Spark
updating PATH environment
Getting Started with Spark
Launching Apache Spark

📝 Lecture 8. Practice. Connecting Python To The Spark. Get Started with PySpark and Jupyter Notebook

Installing Anaconda On Windows
Running the Jupyter Notebook
Connecting Jupyter notebook to Spark

📝 Lecture 9. Practice. Connecting MySQL with Spark. Export Data from Mysql to Spark.

Connecting Jupyter notebook to Spark
How to set up PySpark for your Jupyter Notebook
Export Data from Mysql to Spark
Importing Spark Dataframes from MySQL on Jupyter notebooks

What Will I Learn?

What is big data?
What storage options we have today?
Public Cloud and Private Cloud.
Distribute you data
What is MySQL?
How Does MySQL Work?
Why is MySQL so Popular?
MySQL server setup
MySQL initial settings
Getting Started with MySQL
Import Excel data into a MySQL
Create a new MySQL table
Most Common Queries
SELECT, DROP, UPDATE query mysql
What is Hadoop?
Spark vs MySql
Spark. Analytics engine for big data processing
Installing Apache Spark
updating PATH environment
Getting Started with Spark
Launching Apache Spark
Installing Anaconda On Windows
Running the Jupyter Notebook
Connecting Jupyter notebook to Spark
Connecting Jupyter notebook to Spark
How to set up PySpark for your Jupyter Notebook
Export Data from Mysql to Spark
Importing Spark Dataframes from MySQL on Jupyter notebooks

Topics for this course

9 Lessons01h 11m

Introduction

Big Data Storage and MySQL.

Practice. Export Excel worksheet data to a MySQL table

A Storage System for Big Data. Hadoop.

Practice. How Apache Spark makes your slow MySQL queries 10x faster.

Course Details

Level: Beginner
Categories: Big Data Machine Learning
Total Hour: 01h 11m
Total Lessons: 9
Last Update: August 11, 2021

Requirements

You need only the installed Windows System
You do not need any special programming knowledge or theoretical knowledge of Python

Target Audience

Beginners who are interested in Big Data and Machine Learning using Python.
Who already have Python programming skills but want to practice with a hands-on, real-world data project.
This course can be opted by anyone (students, developer, manager) who is interested to learn big data.