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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-engineerdata-scientist-power-bi-python-etlssis/
课程评论：没有评论
课程名称：数据工程师/数据科学家 - Power BI/Python/ETL/SSIS 课程概述： 本课程旨在解决组织在从多个来源收集数据时面临的常见问题，包括数据格式的多样性和数据清洗需求。课程涵盖了提取、转换和加载（ETL）的数据管道，强调如何从各种来源收集数据，按照业务规则转换数据，并将其加载到目标数据存储中。我们将探讨 SQL Server 集成服务（SSIS），这一强大的商业智能工具，适合与 SQL Server 数据库一起使用，能够进行数据集成、转换、解决复杂商业问题、更新数据仓库等多种操作。 此外，课程还将介绍 Power BI，这一商业分析解决方案可以帮助您可视化数据并在组织内部分享洞见。您将学习如何连接到多个数据源，利用实时仪表板和报告将数据生动呈现，并快速从数据中获取洞察。 数据科学是一门关于数据的学科，涉及记录、存储和分析数据的方法，以有效提取有用信息。无论是客户洞见还是为产品、政策和系统开发提供的信息，数据在日常工作中都是至关重要的。大企业、社交媒体、金融和公共部门都依赖数据科学家来分析数据并提取商业洞见。 课程中还将介绍 Python，这种现代面向对象的编程语言，易于学习且灵活多用，广泛应用于数据科学。作为初学者课程，您将学习Python环境的设置、如何使用 Jupyter Notebook、导入库、处理表格数据、探索 Pandas 数据框和序列、数据清洗及数据可视化等基本知识。 您将学到的内容包括： - 设置 Jupyter Notebook 的环境 - 导入 Python 库 - 处理表格数据 - 探索 Pandas 数据框和序列 - 操作和清洗数据 - 数据可视化 在本课程结束时，您将掌握使用 Power BI 和 Python 进行数据分析的基础知识，为进一步的学习和应用打下坚实基础。
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 destinationsPower 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 informationData 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 NotebookHow to import Python Libraries into your environmentHow to work with Tabular dataHow to explore a Pandas DataFrameHow to explore a Pandas SeriesHow to Manipulate a Pandas DataFrameHow to clean dataHow to visualize data
