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Autor Tópico: Data Engineer/Data Scientist - Power BI/ Python/ ETL/SSIS  (Lida 68 vezes)

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Data Engineer/Data Scientist - Power BI/ Python/ ETL/SSIS
« em: 25 de Maio de 2021, 04:35 »
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 123 lectures (13 hour, 16 mins) | Size: 3.56 GB
Hands-on Data Interaction and Manipulation.

What you'll learn

Connecting to various data sources
Extracting Data
Cleaning Data
Transforming Data
Loading Data
Data Visualization
Exploring Pandas DataFrame
Creating SSIS Package
Debugging SSIS Package
Creating and publishing reports
Data Modeling

Requirements

A Computer with Internet access is required.

Description

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:

Data Integration

Data Transformation

Providing solutions to complex Business problems

Updating data warehouses

Cleaning data

Mining data

Managing SQL Server objects and data

Extracting data from a variety of sources

Loading data into one or several destinations

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.

Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information

Data is a fundamental part of our everyday work, whether it be in the form of valuable insights about our customers, or information to guide product,policy or systems development. Big business, social media, finance and the public sector all rely on data scientists to analyse their data and draw out business-boosting insights.

Python is a dynamic modern object -oriented programming language that is easy to learn and can be used to do a lot of things both big and small. Python is what is referred to as a high level language. That means it is a language that is closer to humans than computer.It is also known as a general purpose programming language due to it's flexibility. Python is used a lot in data science.

This course is a beginners course that will introduce you to some basics of data science using Python.

What You Will Learn

How to set up environment to explore using Jupyter Notebook

How to import Python Libraries into your environment

How to work with Tabular data

How to explore a Pandas DataFrame

How to explore a Pandas Series

How to Manipulate a Pandas DataFrame

How to clean data

How to visualize data

Who this course is for:

Beginners to Data Science
Beginners to Data Engineering
Beginner Data Analyst
Beginner Data Engineer

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