Google ADPクラムメディア & ADP試験番号

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Analysis and Presentation	27%	- Data visualization 1. Looker / Looker Studio reporting - Querying and analyzing data 1. Data aggregation and transformation 2. BigQuery SQL usage
Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Streaming ingestion with Pub/Sub concepts 2. Cloud Storage ingestion patterns
Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Dataflow pipelines 2. Workflow orchestration concepts (e.g., Cloud Composer)
Data Management	25%	- Storage and data organization 1. Cloud Storage lifecycle policies 2. BigQuery datasets and tables management - Data governance and security 1. IAM and access control 2. Data lifecycle management

>> Google ADPクラムメディア <<

ADP試験番号、ADP受験資料更新版

私たちのADP練習問題は実際に自分の魅力を持っているため、世界中のユーザーを引き付けました。ADP練習問題のように、あらゆる面でユーザーのニーズを真剣に検討する練習問題がないです。ADP練習問題を利用すれば、ADP試験に合格することは夢ではないです。従って、ためらわなくて、ADP練習問題を購入し、勉強し始めましょう！

Google Associate Data Practitioner 認定 ADP 試験問題 (Q54-Q59):

質問 # 54
Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

A. Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
B. Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.
C. Create a custom quota for each analyst in BigQuery.
D. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.

正解：A

質問 # 55
Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?

A. Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
B. Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
C. Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.
D. Create a single Explore with all sales metrics. Build the dashboard using this Explore.

正解：D

質問 # 56
Your retail company wants to analyze customer reviews to understand sentiment and identify areas for improvement. Your company has a large dataset of customer feedback text stored in BigQuery that includes diverse language patterns, emojis, and slang. You want to build a solution to classify customer sentiment from the feedback text. What should you do?

A. Use Dataproc to create a Spark cluster, perform text preprocessing using Spark NLP, and build a sentiment analysis model with Spark MLlib.
B. Preprocess the text data in BigQuery using SQL functions. Export the processed data to AutoML Natural Language for model training and deployment.
C. Export the raw data from BigQuery. Use AutoML Natural Language to train a custom sentiment analysis model.
D. Develop a custom sentiment analysis model using TensorFlow. Deploy it on a Compute Engine instance.

正解：C

質問 # 57
Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

A. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.
B. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
C. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables. Use the row_number() window function to query the new materialized view.
D. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.

正解：B

質問 # 58
You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?

A. Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
B. Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
C. Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
D. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.

正解：D

質問 # 59
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GoogleのADP認定試験を受けることを決めたら、PassTestがそばにいて差し上げますよ。PassTestはあなたが自分の目標を達成することにヘルプを差し上げられます。あなたがGoogleのADP「Associate Data Practitioner」認定試験に合格する需要を我々はよく知っていますから、あなたに高品質の問題集と科学的なテストを提供して、あなたが気楽に認定試験に受かることにヘルプを提供するのは我々の約束です。

ADP試験番号: https://www.passtest.jp/Google/ADP-shiken.html