Data Engineering - ETL, Web Scraping ,Big Data,SQL,Power BI

BY
Udemy

Gain a thorough understanding of the various data engineering concepts, such as web scraping, big data, SQL, Power BI, and more.

Mode

Online

Fees

₹ 449 1999

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Data engineering is the practice of developing large-scale data collection, storage, and analysis systems. Applications for data engineering can be found in almost every industry. Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI certification course is developed by Bluelime Learning Solutions and is made available by Udemy for learners who want to acquire the skills and expertise to interact with various types of data.

Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI online training is a self-paced program that involves more than 12.5 hours of video-based lessons, 11 downloadable learning resources, and articles to assist students in understanding the concepts related to web-scraping, big data, Power BI, SQL, and ETL. Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI online courses evolve around topics like data modeling, data transformation, data visualization, data extraction, data cleaning, database interaction, and more.

The highlights

  • Certificate of completion
  • Self-paced course
  • 12.5 hours of pre-recorded video content
  • 1 article
  • 11 downloadable resources

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 449  ₹1,999
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Knowledge of big data Sql knowledge Knowledge of crud operations Knowledge of data visualization

After completing the Data Engineering - ETL, Web Scraping, Big Data, SQL, and Power BI online certification, learners will acquire an in-depth understanding of various data engineering operations involving web scraping, SQL, Power BI, ETL, and big data. In this data engineering course, learners will explore the fundamentals associated with SSIS packages, CRUD operations, and visual studio. In this data engineering certification, learners will also study various data operations including data cleaning, data transformation, database interaction, data extraction, data modeling, and data visualization.

The syllabus

ETL (Extract, Transform ,Load) environment setup

  • Introduction
  • What is ETL
  • What is Visual Studio
  • Visual Studio system requirements
  • Download and install visual studio
  • Visual Studio Workload
  • What is SQL Server
  • SQL Server Installation Requirements
  • SQL Server Editions
  • Download Microsoft SQL Server
  • Install SQL Server
  • Install SSMS
  • Connecting to SQL Server with SSMS
  • SQL Server Configuration Manager
  • Download Adventureworks sample database
  • Attach sample adventureworks database
  • Download adventureworksDW database
  • Download and install SSDT
  • Installing SSDT Designer Templates

Implementing ETL Process with SSIS

  • What is SSIS
  • Create a new SSIS Project via vs 2019
  • Create a new ssis project via vs 2015
  • Add a flat File Connection Manager
  • Remap Column Data Types
  • Add and configure OLE DB Connection Manager
  • Add a Data Flow Task
  • Add and configure Flat File Source
  • Add and configure Lookup Transformation
  • Add and Configure Lookup For DateKey Transformation
  • Add and configure OLE DB Destination
  • Test and Run Package

Data Interaction with SQL (Transact-SQL)

  • What is SQL
  • What is T-SQL
  • Basic Database Concepts
  • SQL Server Data Types
  • CRUD Operations
  • Creating a new database
  • Creating a new table
  • Inserting records into table
  • Reading data from tables
  • Views
  • Stored Procedures
  • Updating Records
  • Deleting records
  • Truncating Tables
  • Dropping Tables
  • Dropping Databases

Web Scraping

  • What is web Scraping
  • Tools for web scrapping
  • How the internet works
  • What is HTTP
  • What we will scrape
  • Inspecting Elements

Installing Required Software for Web Scraping

  • Installing Text Editor (Visual Studio Code)
  • What is Python
  • Installing Python on Windows
  • Installing Python on Mac
  • Installing Virtual Environment Tool
  • Creating and activating virtual environment
  • Installing Beautiful Soup
  • Installing Scrapy

Web Scraping with Python and Beautiful Soup

  • Building the web scraping script : Part 1
  • Building the web scraping script : Part 2
  • Prototyping the script: Part 1
  • Prototyping the script: Part 2
  • Prototyping the script: Part 3
  • Prototyping the script: Part 4
  • Prototyping the script: Part 5
  • Testing and saving scrapped data

Web Scraping with Python and Scrapy

  • Creating a Scrapy project
  • Components of a scrapy project
  • Scrapy Architecture
  • Creating a spider; Part 1
  • Creating a spider; Part 2
  • Scraping data with scrapy shell: Part 1
  • Scraping data with scrapy shell: Part 2
  • Testing Spider and saving scrapped data

Introduction to Big Data

  • What is Big Data
  • Big Data High Volume
  • Big Data High Velocity
  • Big Data High Variety
  • Google Big Data Approach
  • Google Big Data Cluster
  • Google Big Data Node
  • Google Big Data File System
  • Google Big Data Table
  • MapReduce
  • Apache Hadoop

Data Interaction with Power BI

  • What is Power BI
  • What is Power BI Desktop
  • Setting Up Office365
  • Installing Power BI Desktop
  • Power BI Desktop Tour
  • Power BI Overview: Part 1
  • Power BI Overview: Part 2
  • Power BI Overview: Part 3
  • Components of Power BI
  • Building Blocks of Power BI
  • Exploring Power BI Desktop Interface
  • Exploring Power BI Service
  • Power BI Apps

Connecting to Web Data with Power BI

  • Connecting to Web Based Data
  • Clean and transform data: Part 1
  • Clean and transform data: Part 2
  • Combining Data Sources
  • Creating Data Visuals: Part 1
  • Creating Data Visuals: Part 2
  • Publishing to Power BI Service

Connecting and transforming database data with Power BI

  • Importing and transforming Data from Access database
  • Changing Locale
  • Connecting to Microsoft Access Database File
  • Power Query Editor and Queries
  • Creating and managing query groups
  • Renaming Queries
  • Splitting Columns
  • Changing Data Types
  • Removing and Reordering Columns
  • Duplicating and adding columns
  • Creating Conditional Columns
  • Connecting to files in a folders
  • Appending Queries
  • Merge Queries
  • Query Dependency View
  • Transforming Less structured data: Part 1
  • Transforming Less structured data: Part 2
  • Creating Tables
  • Query Parameters

Data Modelling with Power BI

  • What is Data Modelling
  • Creating and managing data relationships
  • Creating calculated columns
  • Optimizing Models for reporting
  • Time Intelligence
  • Applying Filters on Visuals
  • Thank You

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