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所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-data-analyst-associate-practice-exams/
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课程名称:Databricks 数据分析师助理认证实践测试 - 简易/中级 概述:Databricks 认证数据分析师助理认证是一个备受推崇的证书,验证个人在数据分析领域的专业知识和能力。该认证旨在评估候选人在使用 Databricks 这一领先的数据分析平台进行有效数据分析所需的知识和技能。Databricks 认证数据分析师助理认证的一个关键特点是实践考试,紧密跟随最新大纲,是候选人评估自己是否准备好参加实际认证考试的重要工具。此实践考试通过模拟真实考试的格式和内容,帮助候选人熟悉考试中的问题类型,并识别需要集中精力复习的领域。 认证考试涵盖了使用 Databricks 进行数据分析的广泛主题,包括数据准备、数据探索、数据可视化和数据解读。候选人需要展示他们分析数据集、创建可视化及从数据中提取有意义见解的能力。考试还考核候选人对数据分析最佳实践的理解以及他们使用 Databricks 工具和功能的熟练程度。 为了获得 Databricks 认证数据分析师助理认证,候选人必须在考试中获得最低及格分数。该认证对希望提升职业生涯的数据显示分析师来说是一项宝贵资产,认证人员因其在数据分析和数据驱动决策方面的专业性而受到认可,这可以为他们带来新的职业机会和提高收入潜力。 首次获得认证后,该证书有效期为两年,需定期再认证。考试的长度为90分钟,考试费用为200美元,加上当地法律要求的适用税费。考试以在线监考的方式进行,考试中不允许使用任何辅助材料。 课程内容包括: 1. Databricks SQL 2. 数据管理 3. 数据湖中的 SQL 4. 数据可视化和仪表板 5. 分析应用程序 总结:Databricks 认证数据分析师助理认证是一个高度受尊重的证书,证明个人在数据分析领域的专业能力。凭借其基于最新大纲的实践考试和对数据分析主题的全面覆盖,该认证成为希望提升技能和职业发展的数据分析师的宝贵资产。获得认证的个人在利用 Databricks 有效分析数据和基于数据做出驱动企业成功的决策方面得到了认可。
Databricks Certified Data Analyst Associate Certification is a highly esteemed credential that validates the expertise and proficiency of individuals in the field of data analysis. This certification is designed to assess the knowledge and skills required to effectively analyze data using Databricks, a leading data analytics platform.One of the key features of the Databricks Certified Data Analyst Associate Certification is the practice exam that closely follows the latest syllabus. This practice exam is an essential tool for candidates to assess their readiness for the actual certification exam. By simulating the format and content of the real exam, the practice exam helps candidates familiarize themselves with the types of questions they can expect and identify areas where they may need to focus their study efforts.The certification exam covers a wide range of topics related to data analysis using Databricks, including data preparation, data exploration, data visualization, and data interpretation. Candidates are required to demonstrate their ability to analyze data sets, create visualizations, and draw meaningful insights from the data. The exam also tests candidates' knowledge of best practices for data analysis, as well as their proficiency in using Databricks tools and features.To earn the Databricks Certified Data Analyst Associate Certification, candidates must pass the certification exam with a minimum passing score. This certification is a valuable asset for data analysts looking to advance their careers and demonstrate their expertise in data analysis using Databricks. Certified individuals are recognized for their proficiency in analyzing data and making data-driven decisions, which can lead to new career opportunities and increased earning potential.Databricks Certified Data Analyst Associate Certification is recognized by industry leaders and employers as a mark of excellence in data analysis. Certified individuals have demonstrated their commitment to continuous learning and professional development, as well as their ability to apply their knowledge and skills in real-world scenarios. Employers value certified professionals for their expertise in data analysis and their ability to drive business success through data-driven decision-making.Databricks Certified Data Analyst Associate Certification is a highly respected credential that validates the expertise and proficiency of individuals in the field of data analysis. With its practice exam based on the latest syllabus and comprehensive coverage of data analysis topics, this certification is a valuable asset for data analysts looking to enhance their skills and advance their careers. Certified individuals are recognized for their ability to analyze data effectively using Databricks and make data-driven decisions that drive business success.Databricks Certified Data Analyst Associate Exam Summary:Exam Name: Databricks Certified Data Analyst AssociateExam voucher cost: USD 200, plus applicable taxes as required per local lawDelivery method: Online ProctoredTest aides: none allowed.Length of exam: 90 minutesPrerequisite: None required; course attendance and six months of hands-on experience inDatabricks is highly recommendedValidity: 2 yearsRecertification: Recertification is required to maintain your certification status. To recertify,you must take the full exam.Unscored Content: Exams may include unscored items to gather statistical information forfuture use. These items are not identified on the form and do not impact your score, andadditional time is factored into account for this contentDatabricks Certified Data Analyst Associate Exam Syllabus Topics:Databricks SQLData ManagementSQL in the LakehouseData Visualization and DashboardingAnalytics applicationsDatabricks SQLDescribe the key audience and side audiences for Databricks SQL.Describe that a variety of users can view and run Databricks SQL dashboards as stakeholders.Describe the benefits of using Databricks SQL for in-Lakehouse platform data processing.Describe how to complete a basic Databricks SQL query.Identify Databricks SQL queries as a place to write and run SQL code.Identify the information displayed in the schema browser from the Query Editor page.Identify Databricks SQL dashboards as a place to display the results of multiple queries at once.Describe how to complete a basic Databricks SQL dashboard.Describe how dashboards can be configured to automatically refresh.Describe the purpose of Databricks SQL endpoints/warehouses.Identify Serverless Databricks SQL endpoint/warehouses as a quick-starting option.Describe the trade-off between cluster size and cost for Databricks SQL endpoints/warehouses.Identify Partner Connect as a tool for implementing simple integrations with a number of other data products.Describe how to connect Databricks SQL to ingestion tools like Fivetran.Identify the need to be set up with a partner to use it for Partner Connect.Identify small-file upload as a solution for importing small text files like lookup tables and quick data integrations.Import from object storage using Databricks SQL.Identify that Databricks SQL can ingest directories of files of the files are the same type.Describe how to connect Databricks SQL to visualization tools like Tableau, Power BI, and Looker.Identify Databricks SQL as a complementary tool for BI partner tool workflows.Describe the medallion architecture as a sequential data organization and pipeline system of progressively cleaner data.Identify the gold layer as the most common layer for data analysts using Databricks SQL.Describe the cautions and benefits of working with streaming data.Identify that the Lakehouse allows the mixing of batch and streaming workloads.Data ManagementDescribe Delta Lake as a tool for managing data files.Describe that Delta Lake manages table metadata.Identify that Delta Lake tables maintain history for a period of time.Describe the benefits of Delta Lake within the Lakehouse.Describe persistence and scope of tables on Databricks.Compare and contrast the behavior of managed and unmanaged tables.Identify whether a table is managed or unmanaged.Explain how the LOCATION keyword changes the default location of database contents.Use Databricks to create, use, and drop databases, tables, and views.Describe the persistence of data in a view and a temp viewCompare and contrast views and temp views.Explore, preview, and secure data using Data Explorer.Use Databricks to create, drop, and rename tables.Identify the table owner using Data Explorer.Change access rights to a table using Data Explorer.Describe the responsibilities of a table owner.Identify organization-specific considerations of PII dataSQL in the LakehouseIdentify a query that retrieves data from the database with specific conditionsIdentify the output of a SELECT queryCompare and contrast MERGE INTO, INSERT TABLE, and COPY INTO.Simplify queries using subqueries.Compare and contrast different types of JOINs.Aggregate data to achieve a desired output.Manage nested data formats and sources within tables.Use cube and roll-up to aggregate a data table.Compare and contrast roll-up and cube.Use windowing to aggregate time data.Identify a benefit of having ANSI SQL as the standard in the Lakehouse.Identify, access, and clean silver-level data.Utilize query history and caching to reduce development time and query latency.Optimize performance using higher-order Spark SQL functions.Create and apply UDFs in common scaling scenarios.Data Visualization and DashboardingCreate basic, schema-specific visualizations using Databricks SQL.Identify which types of visualizations can be developed in Databricks SQL (table, details, counter, pivot).Explain how visualization formatting changes the reception of a visualizationDescribe how to add visual appeal through formattingIdentify that customizable tables can be used as visualizations within Databricks SQL.Describe how different visualizations tell different stories.Create customized data visualizations to aid in data storytelling.Create a dashboard using multiple existing visualizations from Databricks SQL Queries.Describe how to change the colors of all of the visualizations in a dashboard.Describe how query parameters change the output of underlying queries within a dashboardIdentify the behavior of a dashboard parameterIdentify the use of the "Query Based Dropdown List" as a way to create a query parameter from the distinct output of a different query.Identify the method for sharing a dashboard with up-to-date results.Describe the pros and cons of sharing dashboards in different waysIdentify that users without permission to all queries, databases, and endpoints can easily refresh a dashboard using the owner's credentials.Describe how to configure a refresh scheduleIdentify what happens if a refresh rate is less than the Warehouse's "Auto Stop"Describe how to configure and troubleshoot a basic alertDescribe how notifications are sent when alerts are set up based on the configurationAnalytics applicationsCompare and contrast discrete and continuous statistics.Describe descriptive statistics.Describe key moments of statistical distributions.Compare and contrast key statistical measures.Describe data enhancement as a common analytics application.Enhance data in a common analytics application.Identify a scenario in which data enhancement would be beneficial.Describe the blending of data between two source applications.Identify a scenario in which data blending would be beneficial.Perform last-mile ETL as project-specific data enhancementIn conclusion, the Databricks Certified Data Analyst Associate Certification is a highly respected credential that validates the expertise and proficiency of individuals in the field of data analysis. With its practice exam based on the latest syllabus and comprehensive coverage of data analysis topics, this certification is a valuable asset for data analysts looking to enhance their skills and advance their careers. Certified individuals are recognized for their ability to analyze data effectively using Databricks and make data-driven decisions that drive business success.DISCLAIMER: These questions are designed to, give you a feel of the level of questions asked in the actual exam. We are not affiliated with Databricks or Apache. All the screenshots added to the answer explanation are not owned by us. Those are added just for reference to the context.