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

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 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:

データ アナリストは、SQL エンドポイントで 4 時間ごとに SQL クエリを実行するように設定しましたが、実行のたびに SQL エンドポイントの起動に時間がかかりすぎています。
データ アナリストは、コストを管理しながらエンドポイントの起動時間を短縮するために、次のどの変更を行うことができますか。

  • A. サーバーレスSQLエンドポイントを使用する
  • B. 最小スケーリング値を増やす
  • C. 自動停止機能をオフにする
  • D. SQLエンドポイントのクラスタサイズを縮小する
  • E. SQLエンドポイントのクラスタサイズを増やす
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

DESCRIBE EXTENDED accounts.customers; を実行すると、次の結果が返されました。

ここで、データ アナリストは次のコマンドを実行します。
DROP アカウント。顧客。
このコマンドを実行した結果を説明するものはどれですか?

  • A. メタストアから accounts.customers テーブルが削除され、基になるデータ ファイルが削除されます。
  • B. SELECT * FROM accounts.customers を実行すると、テーブル内のすべての行が返されます。
  • C. accounts.customers テーブルはメタストアから削除されますが、基になるデータ ファイルはそのまま残ります。
  • D. SELECT * FROM delta. `dbfs:/stakeholders/customers` を実行するとエラーが発生します。
  • E. .customers 拡張子を持つすべてのファイルが削除されます。
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

データアナリストは、my_table という次のテーブルを扱っています。
顧客名 支出額
六角スプロケット [125.34、100.15、9003.99]
へこんだフェンダー [16.99、200.85、33.49、88.17]
アナリストは、次のコードブロックを使用して、dollars_spent配列の各値を100で割って、支出額を100ドル単位で取得したいと考えています。
選択
顧客名、
_______
my_table から;
上記のコードブロックがタスクを正常に完了するように、空欄を埋めるにはどのコード行を使用すればよいでしょうか?

  • A. TRANSFORM(dollars_spent, value -> value / 100) AS hundreds_spent
  • B. TRANSFORM(dollars_spent, value / 100) AS hundreds_spent
  • C. TRANSFORM(dollars_spent, dollars_spent / 100) AS hundreds_spent
  • D. TRANSFORM(hundreds_spent, dollars_spent / 100)
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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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  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

データアナリストは、データベース database_name 内に、特定のスキーマを持つ空のマネージドテーブル table_name を作成する必要があります。テーブルは、既に存在するかどうかにかかわらず、再作成され、空である必要があります。
アナリストはどのコマンドを使ってタスクを完了できますか?

  • A. CREATE OR REPLACE TABLE table_name FROM database_name USING (width INT, length INT, height INT);
  • B. CREATE OR REPLACE TABLE database_name.table_name USING (width INT, length INT, height INT);
  • C. CREATE OR REPLACE TABLE database_name.table_name (width INT, length INT, height INT);
  • D. CREATE TABLE database_name.table_name USING (width INT, length INT, height INT);
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

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