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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analyst-pythonetlssisssrsssasmicrosoft-sqlpowerbi/
课程评论:没有评论
课程名称:数据分析师- Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI 课程概述: 数据无处不在。我们在线和日常生活中的每一个行为都产生数据,这些数据是宝贵的商业资源。实际上,94%的公司认为数据和分析对其增长至关重要。随着数字化进程的加快,专业能够将信息转化为可操作洞察的人员的需求日益增加。数据分析师的工作是收集和解释数据,以解决特定问题。这个角色不仅需要大量接触数据,还包括与他人沟通发现的结果。 数据分析的日常工作通常包括以下几个方面: 1. **收集数据**:分析师通常会亲自收集数据,这可能涉及进行调查、跟踪公司网站的访客特征,或从数据收集专家那里购买数据集。 2. **清洗数据**:原始数据可能包含重复项、错误或异常值。清洗数据的过程是维护电子表格或编程语言中数据质量,以确保解释结果的准确性。 3. **建模数据**:这涉及到创建和设计数据库的结构,包括选择存储和收集的数据类型、建立数据类别之间的关系,以及处理数据的实际呈现方式。 4. **解释数据**:在这一过程中,分析师需要识别数据中的模式或趋势,以回答特定问题。 5. **呈现结果**:沟通研究结果是工作的重要组成部分,通常通过制作图表、撰写报告并向相关方展示信息来完成。 在数据分析过程中,分析师通常会使用多种工具来提高工作准确性和效率,常见工具包括:Microsoft Excel、Google Sheets、SQL、Tableau、R或Python、SSAS、SSRS、SSIS、ETL、Microsoft Power BI、Jupyter Notebooks等。 本课程旨在培养学员的数据分析能力,使他们能够有效使用现代工具和技术,完成数据分析的各个环节。
Data is everywhere. Everything you do online and in your daily life generates data-and it's a valuable business resource. In fact, 94% of companies say data and analytics are essential to their growth. As we move toward greater digitization, there is an ever-increasing demand for professionals who can turn information into actionable insights. A data analyst is a person whose job is to gather and interpret data in order to solve a specific problem. The role includes plenty of time spent with data but entails communicating findings too. Here's what many data analysts do on a day-to-day basis:Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining the quality of data in a spreadsheet or through a programming language so that your interpretations won't be wrong or skewed. Model data: This entails creating and designing the structures of a database. You might choose what types of data to store and collect, establish how data categories are related to each other, and work through how the data actually appears.Interpret data: Interpreting data will involve finding patterns or trends in data that could answer the question at hand.Present: Communicating the results of your findings will be a key part of your job. You do this by putting together visualizations like charts and graphs, writing reports, and presenting information to interested partiesDuring the process of data analysis, analysts often use a wide variety of tools to make their work more accurate and efficient. Some of the most common tools in the data analytics industry include:Microsoft ExcelGoogle SheetsSQLTableauR or PythonSSASSSRSSSISETLMicrosoft Power BIJupyter Notebooks