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所在平台: Udemy |
课程主页: https://www.udemy.com/course/comptia-data-plus-certification-preparation-crash-course/
课程评论：没有评论
课程名称：CompTIA Data Plus 认证准备速成课程 课程概述：随着数据专业人员的需求逐年增长，获得CompTIA Data Plus (DAO-001)认证可以显著提升在数据和商业分析领域的职业机会。数据是众多组织的基础，几乎在任何行业中都有增长潜力。数据分析师负责数据的收集、存储、转化、维护、分析和安全，为组织提供价值，帮助其实现目标并做出复杂的商业决策。CompTIA Data Plus认证的专业人士在数据收集、分析和可视化方面具备熟练技能。根据Glassdoor的数据显示，2023年10月美国数据分析师的平均薪水为74,753美元，初级商业分析师的年薪起点为64,026美元，而需求旺盛的解决方案架构师年薪可超过154,000美元。完成本课程后，您将为在组织中成为高需求数据专业人士做好充分准备。 关于课程：本课程旨在帮助您顺利参加具有挑战性的CompTIA Data Plus DAO-001考试。课程内容涵盖了全部的考试大纲，包括数据概念和环境、数据挖掘、数据分析、数据可视化、数据治理、质量和控制等方面。您将学习到数据采集、分析和报告的基本技能，并通过实践题和学习资料获得充分准备。 您将在课程中学到： - CompTIA Data Plus考试的重要性及其目标。 - 如何收集、分析和报告常用数据类型。 - 将原始数据转化为可用信息的方法。 - 数据库类型、数据结构、数据模式等重要数据管理基础知识。 - JSON、HTML和XML等数据的应用。 - ETL和ELT过程的工作原理及API的连接作用。 - 数据操作技术及重要的转置和规范化概念。 - 描述性统计和推论统计及各种分析技术。 - 常用的分析工具和结构化查询语言（SQL）的重要性。 - 报告和仪表板设计的多种可视化类型。 课程内容包括：课程介绍、CompTIA Data Plus考试目标、数据概念与环境、数据挖掘、数据分析、数据可视化、数据治理及质量控制、考试准备与练习等。 适合人群：该课程面向希望进入数据领域的初学者，以及已有一定数据经验的数据工程师和数据分析师，和希望提升知识和技能的软件专业人员和数据库专业人员。 课程预需求：本课程没有前置要求。
The demand for data professionals has been exponentially growing year over year and becoming CompTIA Data Plus (DAO-001) Certified can really elevate your career opportunities in the world of data and business analytics.Data is the foundation for many organizations and offers the potential for growth in almost any industry. Data analysts collect, store, transform, maintain, analyze, and secure data for use in their organizations.A CompTIA Data Plus certified professional is proficient at the collection, analysis, and visualization of data that provides value so that their organizations achieve goals and can make complex business decisions.The Data+ exam is designed to be a vendor-neutral certification for data professionals and those seeking to enter the data fields.Did you know in Oct 2023, the average salary for a Data Analyst is $74,753 dollars per year in United States according to Glassdoor.Entry level business analysts in the United States can start at $64,026 per year while the most sought-after solutions architects can make over $154,000 per year.Once you complete this CompTIA Data Plus Certification Crash Course you will truly be prepared to take your place amongst the highly sought-after data professionals in your organization.About the CourseIn this course we focus on preparing you for a successful sitting for the challenging CompTIA Data Plus DA0-001 exam.This course provides full content, free practice questions and study eBook as well optional demonstration and exercises.An important aspect that data professional must know is focused on data mining, data manipulation as well as visualizing and reporting data to stakeholders.So, whether applying basic statistical methods or analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle a data professional is an important role to enterprises.All of the exam objectives are covered as specified by CompTIA for the exam in these domains.Data Concepts and EnvironmentsData MiningData AnalysisData VisualizationData Governance, Quality, and ControlsABOUT THE COMPTIA DATA+ CERTIFICATIONCompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. The certification validates the data analytics skills and competencies that are needed to organize, understand, and act on relevant data.This course covers 100% of the DA0-001 objective domains and also provides exam test tips, topic focused demonstrations and over 100 practice questions along with a free downloadable study guide.What will you learn in the course?Understand the importance of the CompTIA Data Plus exam and its objectives.You'll learn to how to collect, analyze, and report on various types of commonly used data.You'll learn about how to transform raw data into usable information for your stakeholders.Learn about database types, data structures, data schemes and other important aspects of data management.Understand how JSON data, HTML data, and XML data is used with data professionals.Understand how ETL and ELT processes work, how APIs connect us to the cloud and learn about profiling datasets.Learn about data manipulation techniques and important concepts around data transposition and normalization.Learn about descriptive statistics, inferential statistics, and various analytic techniques.Identify common analytics tools used in data analysis.Learn about the importance of Structured Query Language (SQL) and its main components.Learn about reporting, reporting dashboards and the various visualization types.Describe the importance of data governance, data stewardship and quality controls to ensure compliance and data consistency.Identify the compliance requirements, security controls and privacy.Course Content CoveredCourse WelcomeCourse OverviewInstructor IntroductionWhat is the CompTIA Data Plus ExamExam ObjectivesExam Acronym ListData Roles to KnowThe Importance of DataDownload Course ResourcesData Concepts and EnvironmentsData SchemesData DimensionsDatabasesDemonstration - Google Cloud SQLData Warehouses and Data LakesOnline transactional processing (OLTP)Demonstration - AWS RedshiftOnline Analytical Processing (OLAP)What is a Schema?Importance of DimensionsDemonstration - Google Cloud Big Query (OLAP)Data TypesDemonstration - File TypesDemonstration - Deploy SQL Demo BenchData StructuresWhat is a Data StructureStructuredUnstructuredSemi StructuredData File FormatsBig Data File FormatsWhat is Columnar FormatData CompressionModule Summary ReviewModule Review QuestionsData MiningUnderstanding Data AcquisitionIntegration ConceptsWhat is An API?Demonstration - APIsData Collection Method OptionsDemonstration - Google Big Query Sample DataWhiteboard Discussion - Data CollectionData Cleansing and ProfilingWhiteboard Discussion - Data Cleansing/ProfilingDemonstration - Excel Data Cleansing and ProfilingData OutliersUnderstanding Data Manipulation TechniquesRecoding DataMerge DataEliminate RedundancyData NormalizationETLScenario - Data ManipulationCommon techniques for data manipulation and query optimizationData Manipulation WorkflowData Manipulation TechniquesQuery OptimizationDemonstration - Query OptimizationModule Summary ReviewModule Review QuestionsData AnalysisUnderstanding Descriptive Statistical MethodsMeasures of TendencyMeasures of DispersionUnderstanding PercentagesUnderstanding Inferential Statistical MethodsHypothesis TestingLinear Regression and CorrelationSummarize types of analysis and key analysis techniquesDefine Exploratory Data AnalysisPerformance AnalysisLink AnalysisCommon Data Tool SetsDemonstration - MS ExcelDemonstration - Power BIDemonstration - AWS QuicksightModule Summary ReviewModule Review QuestionsData VisualizationModule OverviewTranslate Business Requirements to ReportsDesign ComponentsDemonstration - Reports and ComponentsDashboard DesignDashboard ComponentsDemonstration - Dashboard ComponentsData Sources and AttributesConsumersDelivery and DevelopmentVisualization TypesUnderstanding Chart TypesUnderstanding Plot TypesUnderstanding MappingDemonstration - VisualizationCompare and Contrast ReportsReports Type OverviewRecurring Report TypesStatic and Dynamic ReportsDemonstration - ComplianceModule Summary ReviewModule Review QuestionsData Governance, Quality and ControlsModule OverviewData GovernanceRequirementsData ClassificationData PrivacyData BreachesData Quality ControlData ChecksData TransformationData ValidationData QualityData Quality DimensionsRules and MetricsMaster Data Management (MDM)Module Summary ReviewModule Review QuestionsExam Preparation and Practice ExamsExam ExperienceCertification CPE RequirementsCourse Content ReviewTop Ten Things to Know for the ExamPractice Questions Pool 1Practice Questions Pool 2Additional ResourcesCourse CloseoutWho should take this course (Target Audience)?Beginners looking for an entry point into the data world.Data Engineers, Data Analysts with some experience working with data.Software professionals, Database professionals looking to boost their knowledge and skillsetsWhat are the Couse Pre Requirements?There are no course pre-requirements.
