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所在平台: Udemy |
课程主页: https://www.udemy.com/course/new-dp-500-exam-questions-and-answers-preparation-course/
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课程名称：新DP-500考试问题与答案 - 完整课程学习 概述： DP-500课程专注于设计和实施基于Microsoft Azure和Microsoft Power BI的企业级分析解决方案。该课程涵盖在大规模下执行高级数据分析的方法和实践。学员将基于已有的分析经验，学习如何实施和管理数据分析环境，包括数据查询与转换、数据模型的实施与管理，以及数据的探索与可视化。学员将在此DP-500实践课程中使用Microsoft Purview、Azure Synapse Analytics和Power BI构建分析解决方案。 受众画像： 本课程面向具有设计、创建和部署企业级数据分析解决方案专业知识的候选人。特别是，候选人应具备高级Power BI技能，包括在云端和本地管理数据存储库和数据处理，以及使用Power Query和数据分析表达式（DAX）。同时，候选人应熟悉从Azure Synapse Analytics获取数据，并具有使用Transact-SQL (T-SQL)查询关系数据库和进行数据可视化的经验。 衡量的技能： 请下载前面"提示"框中的学习指南以获取更多关于考试中衡量技能的细节。DP-500考试包含的技能主要包括： - 实施和管理数据分析环境（占25-30%） - 查询和转换数据（占20-25%） - 实施和管理数据模型（占25-30%） - 探索和可视化数据（占20-25%） Azure企业数据分析师认证的候选人应具备在企业级数据分析解决方案设计、创建和部署上的专业知识。该角色的责任包括以大规模执行高级数据分析，例如清理和转换数据、设计和构建企业数据模型、融入高级分析能力、与IT基础设施集成以及应用开发生命周期实践。这些专业人士帮助收集企业级的数据分析解决方案需求，包括Azure和Microsoft Power BI，并就数据治理和Power BI管理配置设置提供建议，监控数据使用情况，优化数据分析解决方案的性能。 Azure企业数据分析师需与其他角色合作，例如解决方案架构师、数据工程师、数据科学家、AI工程师、数据库管理员和Power BI数据分析师。候选人应具备高级Power BI技能，包括管理数据存储库和数据处理的能力，精通常用的Power Query和DAX，能够处理来自Azure Synapse Analytics的数据，并具备使用T-SQL查询关系数据库和进行数据可视化的经验。
DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BIThis course covers methods and practices for performing advanced data analytics at scale. Students will build on existing analytics experience and will learn to implement and manage a data analytics environment, query and transform data, implement and manage data models, and explore and visualize data. In this DP-500 Practice course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.Audience ProfileCandidates for this DP-500 Questions course should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. Specifically, candidates should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.Skills measuredDownload the study guide in the preceding "Tip" box for more details about the skills measured on this exam.This DP-500 exam list contains the skills measured on the exam associated with this certification. For detailed information, see the associated exam details page and download the study guide.· Implement and manage a data analytics environment (25-30%)· Query and transform data (20-25%)· Implement and manage data models (25-30%)· Explore and visualize data (20-25%)Candidates for the Azure Enterprise Data Analyst Associate certification should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions.Responsibilities for this role include performing advanced data analytics at scale, such as cleaning and transforming data, designing and building enterprise data models, incorporating advanced analytics capabilities, integrating with IT infrastructure, and applying development lifecycle practices. These professionals help collect enterprise-level requirements for data analytics solutions that include Azure and Microsoft Power BI. They also advise on data governance and configuration settings for Power BI administration, monitor data usage, and optimize performance of the data analytics solutions.Azure enterprise data analysts collaborate with other roles, such as solution architects, data engineers, data scientists, AI engineers, database administrators, and Power BI data analysts.Candidates for this certification should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.
