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Databricks Databricks-Certified-Data-Analyst-Associate日本語 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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.
Topic 3
  • 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.
Topic 4
  • 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.
Topic 5
  • 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.

Reference: https://www.databricks.com/learn/certification/data-analyst-associate

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Databricks Certified Data Analyst Associate Exam (Databricks-Certified-Data-Analyst-Associate日本語版) Sample Questions:

Databricks SQL のコンピューティング リソースとして何が使用されますか?

  • A. 単一ノードクラスタ
  • B. 標準クラスター
  • C. SQLウェアハウス
  • D. Databricks SQL と統合されたダウンストリーム BI ツール
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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データレイクアーキテクチャに組織性、信頼性、パフォーマンス、データガバナンスを追加することで、データレイクハウスの実現を支援するオープンソースプロジェクトはどれですか?

  • A. Delta Lake
  • B. MLflow
  • C. Apache Spark
  • D. Databricks SQL
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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データアナリストが、大規模なデータセットや複雑な結合操作を処理する際に失敗するDatabricks SQLのクエリのトラブルシューティングを行っています。ログによると、クラスターのリソース制約エラーが原因でジョブが常に中断されていることが示されています。
アナリストは、リソースの過剰使用を引き起こしているオペレーターを特定するために、どのクエリプロファイルメトリックを使用すべきでしょうか?

  • A. オペレーター1人あたりの作業時間
  • B. オペレーターごとにディスクに書き込まれたバイト数
  • C. オペレーターごとのシャッフル読み取りサイズ
  • D. 演算子あたりのメモリピーク
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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データアナリストがemployees_dfというデータフレームを扱っており、給与に10%の税金が加算された値を表示する新しい列を追加する必要があります。なお、このデータフレームには不要なage列が含まれています。
どのコード断片が税金列を追加し、年齢列を削除しますか?

  • A. employees_df = employees_df.withColumn( " tax " , employees_df.salary * 10).drop( " age " )
  • B. employees_df = employees_df.withColumn( " tax " , employees_df.salary * 0.1).drop( " age " )
  • C. employees_df = employees_df.withColumn( " tax " , employees_df.salary * 10).dropField( " age " )
  • D. employees_df = employees_df.withColumn( " tax " , lit(0.1) * col( " salary " )).dropField( " age " )
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Visualization Editor で視覚効果を追加することに関する次の記述のうち、誤っているものはどれですか。

  • A. 視覚化スケールを変更できます。
  • B. 色を変更できます。
  • C. データ ラベルをフォーマットできます。
  • D. ツールチップをフォーマットできます。
  • E. 境界線を追加できます。
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

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