Databricks : Databricks-Certified-Data-Analyst-Associate日本語 Questions & Answers

Updated: Oct 18, 2026

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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
  • 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.
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
  • 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.

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

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

Question #1

データ アナリストは次のコマンドを実行します。
年齢、国を選択
my_tableから
年齢 >= 75 かつ国 = 'カナダ' の場合;
上記のコマンドの出力を表す表は次のどれですか?

  • A.
  • B.
  • C.
  • D.
  • E.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

データエンジニアは、2つのテーブルからデータを取得してリレーショナルオブジェクトを作成したいと考えています。このリレーショナルオブジェクトは、他のセッションで他のデータエンジニアが使用する必要はありません。ストレージコストを削減するため、データエンジニアは物理データのコピーと保存を避けたいと考えています。
データエンジニアは、次のうちどのリレーショナルオブジェクトを作成すべきでしょうか?

  • A. Spark SQLテーブル
  • B. 表示
  • C. デルタ表
  • D. 一時的な表示
  • E. データベース
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #3

データサイエンティストが機械学習モデルのハイパーパラメータを調整したいと考えています。彼らはSpark MLモデルを目的関数objective_functionにラップし、探索空間search_spaceを定義しました。
その結果、彼らは以下のコードブロックを持っています。
num_evals = 100
トライアル = SparkTrials()
best_hyperparam = fmin(
fn=目的関数、
スペース=検索スペース、
algo=tpe.suggest、
max_evals=num_evals、
試行=試行
)
タスクを完了するために、上記のコードブロックに対して以下のどの変更を行う必要がありますか?

  • A. SparkTrials() を Trials() に変更します
  • B. trials=trials 引数を削除します
  • C. num_evalを10未満に減らす
  • D. fmin() を fmax() に変更します
  • E. algo=tpe.suggest 引数を削除します
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

データアナリストが、テーブル内に個人識別情報(PII)を含む列を発見しました。データアナリストは、このようなPIIデータにアクセスすべきではありません。
データアナリストはどのように進めるべきでしょうか?

  • A. 個人情報を含む列を削除し、誰にも通知せずにプロジェクトを続行します。
  • B. データの操作を停止し、テーブルと既存のメタデータまたはデータファイルをすべて削除します。
  • C. データの取り扱いを中止し、上司に報告して、組織および法律上のベストプラクティスに従ってデータが処理されるようにします。
  • D. データを使った作業を中止し、別のデータを使ってプロジェクトを進めてください。
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #5

データアナリストは、データベース database_name 内に管理テーブル table_name を所有しています。このテーブルと、このテーブルに関連付けられたすべてのデータファイルをデータベースから削除したいと考えています。データベース内の残りのテーブルは引き続き存在する必要があります。
アナリストがエラーを出さずにタスクを完了するために使用できるコマンドはどれですか?

  • A. テーブル database_name.table_name を削除します。
  • B. テーブル database_name.table_name を削除します。
  • C. データベース名からテーブル table_name を削除します。
  • D. データベースデータベース名を削除します。
  • E. データベース名からテーブル table_name を削除します。
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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