Data Engineering - ETL, Web Scraping ,Big Data,SQL,Power BI
- Description
- Curriculum
- FAQ
- Reviews
A common problem that organizations face is how to gathering data from multiple sources, in multiple formats, and move it to one or more data stores. The destination may not be the same type of data store as the source, and often the format is different, or the data needs to be shaped or cleaned before loading it into its final destination.
Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store.
SQL Server Integration Services (SSIS) is a useful and powerful Business Intelligence Tool . It is best suited to work with SQL Server Database . It is added to SQL Server Database when you install SQL Server Data Tools (SSDT)which adds the Business Intelligence Templates to Visual studio that is used to create Integration projects.
SSIS can be used for:
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Data Integration
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Data Transformation
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Providing solutions to complex Business problems
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Updating data warehouses
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Cleaning data
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Mining data
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Managing SQL Server objects and data
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Extracting data from a variety of sources
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Loading data into one or several destinations
Web scraping is the process of automatically downloading a web page’s data and extracting specific information from it. The extracted information can be stored in a database or as various file types.
Web scraping software tools may access the World Wide Web directly using the Hypertext Transfer Protocol, or through a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a bot or web crawler. It is a form of copying, in which specific data is gathered and copied from the web, typically into a central local database or spreadsheet, for later retrieval or analysis.
Scraping a web page involves fetching it and extracting from it. Fetching is the downloading of a page (which a browser does when you view the page). to fetch pages for later processing. Once fetched, then extraction can take place. The content of a page may be parsed, searched, reformatted, its data copied into a spreadsheet, and so on. Web scrapers typically take something out of a page, to make use of it for another purpose somewhere else. An example would be to find and copy names and phone numbers, or companies and their URLs, to a list (contact scraping).
Big data can be characterised as data that has high volume, high variety and high velocity. Data includes numbers, text, images, audio, video, or any other kind of information you might store on your computer. Volume, velocity, and variety are sometimes called “the 3 V’s of big data.”
What kind of datasets are considered big data?
Examples includes social media network analysing their members’ data to learn more about them and connect them with content and advertising relevant to their interests, or search engines looking at the relationship between queries and results to give better answers to users’ questions.
SQL is a standard language for accessing and manipulating databases.
SQL stands for Structured Query Language
What Can SQL do?
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SQL can execute queries against a database
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SQL can retrieve data from a database
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SQL can insert records in a database
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SQL can update records in a database
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SQL can delete records from a database
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SQL can create new databases
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SQL can create new tables in a database
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SQL can create stored procedures in a database
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SQL can create views in a database
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SQL can set permissions on tables, procedures, and views
Power BI is a business analytics solution that lets you visualize your data and share insights across your organization, or embed them in your app or website. Connect to hundreds of data sources and bring your data to life with live dashboards and reports.
Discover how to quickly glean insights from your data using Power BI. This formidable set of business analytics tools—which includes the Power BI service, Power BI Desktop, and Power BI Mobile—can help you more effectively create and share impactful visualizations with others in your organization.
In this beginners course you will learn how to get started with this powerful toolset. We will cover topics like connecting to and transforming web based data sources. You will learn how to publish and share your reports and visuals on the Power BI service.
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1IntroductionVideo lesson
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2What is ETLVideo lesson
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3What is Visual StudioVideo lesson
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4Visual Studio system requirementsVideo lesson
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5Download and install visual studioVideo lesson
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6Visual Studio WorkloadVideo lesson
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7What is SQL ServerVideo lesson
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8SQL Server Installation RequirementsVideo lesson
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9SQL Server EditionsVideo lesson
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10Download Microsoft SQL ServerVideo lesson
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11Install SQL ServerVideo lesson
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12Install SSMSVideo lesson
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13Connecting to SQL Server with SSMSVideo lesson
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14SQL Server Configuration ManagerVideo lesson
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15Download Adventureworks sample databaseVideo lesson
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16Attach sample adventureworks databaseVideo lesson
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17Download adventureworksDW databaseVideo lesson
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18Download and install SSDTVideo lesson
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19Installing SSDT Designer TemplatesVideo lesson
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20What is SSISVideo lesson
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21Create a new SSIS Project via vs 2019Video lesson
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22Create a new ssis project via vs 2015Video lesson
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23Add a flat File Connection ManagerVideo lesson
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24Remap Column Data TypesVideo lesson
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25Add and configure OLE DB Connection ManagerVideo lesson
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26Add a Data Flow TaskVideo lesson
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27Add and configure Flat File SourceVideo lesson
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28Add and configure Lookup TransformationVideo lesson
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29Add and Configure Lookup For DateKey TransformationVideo lesson
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30Add and configure OLE DB DestinationVideo lesson
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31Test and Run PackageVideo lesson
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32What is SQLVideo lesson
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33What is T-SQLVideo lesson
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34Basic Database ConceptsVideo lesson
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35SQL Server Data TypesVideo lesson
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36CRUD OperationsVideo lesson
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37Creating a new databaseVideo lesson
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38Creating a new tableVideo lesson
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39Inserting records into tableVideo lesson
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40Reading data from tablesVideo lesson
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41ViewsVideo lesson
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42Stored ProceduresVideo lesson
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43Updating RecordsVideo lesson
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44Deleting recordsVideo lesson
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45Truncating TablesVideo lesson
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46Dropping TablesVideo lesson
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47Dropping DatabasesVideo lesson
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54Installing Text Editor (Visual Studio Code)Video lesson
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55What is PythonVideo lesson
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56Installing Python on WindowsVideo lesson
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57Installing Python on MacVideo lesson
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58Installing Virtual Environment ToolVideo lesson
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59Creating and activating virtual environmentVideo lesson
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60Installing Beautiful SoupVideo lesson
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61Installing ScrapyVideo lesson
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62Building the web scraping script : Part 1Video lesson
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63Building the web scraping script : Part 2Video lesson
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64Prototyping the script: Part 1Video lesson
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65Prototyping the script: Part 2Video lesson
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66Prototyping the script: Part 3Video lesson
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67Prototyping the script: Part 4Video lesson
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68Prototyping the script: Part 5Video lesson
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69Testing and saving scrapped dataVideo lesson
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70Creating a Scrapy projectVideo lesson
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71Components of a scrapy projectVideo lesson
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72Scrapy ArchitectureVideo lesson
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73Creating a spider; Part 1Video lesson
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74Creating a spider; Part 2Video lesson
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75Scraping data with scrapy shell: Part 1Video lesson
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76Scraping data with scrapy shell: Part 2Video lesson
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77Testing Spider and saving scrapped dataVideo lesson
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78What is Big DataVideo lesson
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79Big Data High VolumeVideo lesson
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80Big Data High VelocityVideo lesson
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81Big Data High VarietyVideo lesson
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82Google Big Data ApproachVideo lesson
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83Google Big Data ClusterVideo lesson
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84Google Big Data NodeVideo lesson
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85Google Big Data File SystemVideo lesson
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86Google Big Data TableVideo lesson
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87MapReduceVideo lesson
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88Apache HadoopVideo lesson
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