Databricks Databricks-Certified-Data-Analyst-Associate 考試概覽:

認證廠商:	Databricks
考試名稱:	Databricks Certified Data Analyst Associate 認證考試
考試代碼:	Databricks-Certified-Data-Analyst-Associate
相關認證:	Databricks Certified Data Engineer Associate 認證 Databricks Certified Machine Learning Associate 認證
考試時間:	90 minutes
考試形式:	單選題, 多選題
實際考試題數:	45–60
及格分數:	70%
支援語言:	英文
考試費用:	$200 USD
證照有效期限:	2 年
推薦課程:	Databricks SQL 培訓課程 Databricks Academy - 資料分析師學習路徑
考試報名:	Databricks 認證入口網站 Kryterion Webassessor 註冊
範例考題:	Databricks Databricks-Certified-Data-Analyst-Associate 範例考題
考試方式:	透過遠端監考進行線上監考考試 (Kryterion Webassessor 平台)
必備條件:	無強制先決條件，但建議熟悉 SQL 及基本資料分析概念。
官方大綱網址:	https://www.databricks.com/learn/certification

Databricks Databricks-Certified-Data-Analyst-Associate 考試大綱：

主題	簡介
主題 1	Analytics applications: It describes key moments of statistical distributions, data enhancement, and the blending of data between two source applications. Moroever, the topic also explains last-mile ETL, a scenario in which data blending would be beneficial, key statistical measures, descriptive statistics, and discrete and continuous statistics.
主題 2	Databricks SQL: This topic discusses key and side audiences, users, Databricks SQL benefits, complementing a basic Databricks SQL query, schema browser, Databricks SQL dashboards, and the purpose of Databricks SQL endpoints warehouses. Furthermore, the delves into Serverless Databricks SQL endpoint warehouses, trade-off between cluster size and cost for Databricks SQL endpoints warehouses, and Partner Connect. Lastly it discusses small-file upload, connecting Databricks SQL to visualization tools, the medallion architecture, the gold layer, and the benefits of working with streaming data.
主題 3	Data Management: The topic describes Delta Lake as a tool for managing data files, Delta Lake manages table metadata, benefits of Delta Lake within the Lakehouse, tables on Databricks, a table owner’s responsibilities, and the persistence of data. It also identifies management of a table, usage of Data Explorer by a table owner, and organization-specific considerations of PII data. Lastly, the topic it explains how the LOCATION keyword changes, usage of Data Explorer to secure data.
主題 4	Data Visualization and Dashboarding: Sub-topics of this topic are about of describing how notifications are sent, how to configure and troubleshoot a basic alert, how to configure a refresh schedule, the pros and cons of sharing dashboards, how query parameters change the output, and how to change the colors of all of the visualizations. It also discusses customized data visualizations, visualization formatting, Query Based Dropdown List, and the method for sharing a dashboard.
主題 5	SQL in the Lakehouse: It identifies a query that retrieves data from the database, the output of a SELECT query, a benefit of having ANSI SQL, access, and clean silver-level data. It also compares and contrasts MERGE INTO, INSERT TABLE, and COPY INTO. Lastly, this topic focuses on creating and applying UDFs in common scaling scenarios.