A data scientist is using Vertex AI Workbench and needs to share a notebook with a team member who only needs read access. What is the most secure way to do this?
Your team wants to visualize BigQuery data in Looker Studio. What is the most efficient way to ensure the dashboard reflects fresh data without manual refreshes?
You are writing a Python script in Vertex AI Workbench. You want to query BigQuery and load the result into a pandas DataFrame. Which library should you use?
Your team maintains a Looker Studio report connected to a BigQuery table that stores web session events. Analysts frequently filter the report by 'session_date' and 'country', but the report takes over 30 seconds to render. The underlying table is 5 TB and is partitioned by 'event_timestamp' and clustered by 'country'. You want to reduce the report's query time without changing the report's filters. What should you do?
A financial analyst needs to create a chart in Looker Studio that shows the cumulative revenue over time, where each point includes all previous revenue. Which chart type and configuration should they use?
You need to create a Looker Studio report that shows a time series of daily active users. The data source is a BigQuery table that is updated with new rows throughout the day, and you want the report to always show the most recent data without manual refresh. You also want to minimize query costs. Which combination of settings should you use?
A data analyst needs to present a summary of last quarter's sales performance to executives. They have a BigQuery table with sales data and want to create a simple, interactive chart that updates automatically. Which Google Cloud tool should they use?
Your team maintains a Looker Studio report connected to a BigQuery dataset. A stakeholder wants to see month-over-month revenue growth as a percentage, but the raw data only contains daily revenue values. You need to add a calculated field to the report. Which approach should you use?
A data analyst has a Looker Studio report connected to a BigQuery table that contains millions of rows. The report has a chart that shows total sales by country. The analyst notices that the chart takes a long time to load. They want to improve performance. What should they do first?
An analyst is building a Looker Studio report connected to a BigQuery table. The report contains a scorecard showing total revenue and a time series chart showing daily revenue. A stakeholder reports that the scorecard total does not match the sum of the daily values in the time series. Both charts use the same data source and no filters are applied. What is the most likely cause?
A data analyst is creating a Looker Studio report that connects to a BigQuery dataset. They want to ensure the report performs well and displays data efficiently. Which two actions should they take to optimize the report's performance? (Choose two.)
You are analyzing daily sales data stored in BigQuery. Your Looker Studio report currently shows total revenue by product category. The product manager now wants to see the percentage contribution of each category to total revenue, displayed as a pie chart. What should you do?
You are building a Looker Studio report that pulls data from BigQuery. The report will be used by executives who need to see key metrics updated near real-time. You want to optimize query performance and reduce cost. Which two actions should you take? (Choose two.)
A data analyst needs to create a report in Looker Studio that combines data from BigQuery and Google Sheets. The BigQuery table contains sales transactions, and the Google Sheets file contains a mapping of product IDs to product names. What is the recommended way to join these two data sources in Looker Studio?
A data analyst runs a query in BigQuery that joins a large fact table with a small dimension table. The query is slow and scans a large amount of data. The dimension table is only a few megabytes. What is the most efficient way to improve the query performance?
You have a Looker Studio report that uses a BigQuery data source. The report contains a time series chart showing daily active users. You notice that the chart is missing data for the last two days, even though the BigQuery table is updated in near real-time. What is the most likely cause?
You are building a Looker Studio report that includes a scorecard showing total revenue. The data source is a BigQuery table with millions of rows. You want the scorecard to display the total revenue for the current month, and you want it to update automatically as new data arrives. What should you do?
You need to create a Looker Studio report that shows a time series of daily active users (DAU) from a BigQuery table. The table contains one row per user session with a timestamp. You want the report to be interactive and allow users to filter by country. Which combination of Looker Studio features should you use?
A financial analyst uses Looker Studio to monitor daily transaction volumes from a BigQuery table. The report contains a time series chart showing total transactions per day for the last 90 days. The analyst notices that the chart is slow to load and sometimes shows stale data because the underlying BigQuery table is updated multiple times per day. The analyst wants to improve performance and ensure the chart reflects the latest data. What should they do?
You are building a Looker dashboard and need to calculate the year-over-year growth rate. Which feature should you use to perform this without modifying the underlying SQL?
A marketing manager needs to see daily sales trends in Looker. The underlying data is in BigQuery and is updated every 6 hours. What is the best way to visualize this?
You are using Vertex AI Workbench and want to ensure your notebook environment persists after the instance is stopped. Where should you save your work?
You need to analyze a petabyte-scale dataset in BigQuery. To optimize cost, you must ensure that users only query relevant partitions. How should you enforce this?
You are developing a dashboard in Looker. You notice that the 'Explore' menu is missing a specific set of fields. What should you check in the LookML model?
In BigQuery, you want to improve query performance for a table that is frequently filtered by a `customer_id` column. What is the recommended strategy?
You have a dashboard in Looker Studio and you want to allow users to dynamically change the date range without editing the report. What should you add?
When designing a Looker dashboard, you need to display a value that is the average of a specific metric across the entire dashboard. What is the best method?
You need to perform a time-series analysis in BigQuery. Your data contains timestamps at a millisecond level, but you need to aggregate by hour. What is the most performant way to truncate the timestamp?
You are using Vertex AI Workbench. You want to install a new Python library, `seaborn`, for visualization. What is the correct way to install it in the notebook instance?
You are creating a Looker report with a 'measure' that calculates the total revenue. You notice it is summing correctly but the format is wrong. Where do you change the format?
You have a Looker Studio report connected to a BigQuery table that contains millions of rows. The report takes a long time to load and often times out. You need to improve performance without changing the underlying data. What should you do?
A data analyst needs to create a Looker Studio report that shows sales data filtered by region. The report must allow users to select one or more regions from a drop-down menu, and the selection should update all charts on the page. Which control should be added to the report?
You need to create a visualization in Looker Studio that shows the proportion of total sales by product category. Which chart type is most appropriate?
You are building a Looker Studio report and need to display a calculated field that shows the profit margin as a percentage. The data source contains fields for revenue and cost. Which expression should you use for the calculated field?
Your team stores customer feedback in a BigQuery table with a column `feedback_text`. You need to count how many times each of the words 'fast', 'slow', and 'broken' appears across all feedback rows. You want to run this as a single SQL query in BigQuery. Which approach should you use?
You are creating a Looker Studio report that must allow users to interactively explore sales data. The report should include controls that let users filter data by product category and date range. Which two controls should you add? (Choose two.)
A data analyst has a BigQuery table named `sales` with columns `order_date` (DATE), `product_id` (STRING), and `revenue` (NUMERIC). They need to create a report that shows total revenue per product for the last 30 days, but only for products that generated more than $10,000 in that period. They want the result sorted by revenue descending. Which SQL query should they use?
A data analyst is building a Looker Studio report connected to a BigQuery table. The report needs to display data for the last 30 days, but the underlying table is updated daily at midnight. Which approach ensures the report always shows the most recent 30 days without manual intervention?
A data engineer is building a Looker Studio report connected to a BigQuery table. The report must allow viewers to dynamically change the date range and filter data by region without editing the report. The engineer wants to add interactive controls. Which two components should be added to the report to meet these requirements? (Choose two.)
A data engineer needs to create a visualization in Looker Studio that shows the relationship between advertising spend and revenue for each marketing campaign. They want to quickly identify which campaigns have high spend but low revenue. Which chart type is most appropriate?
A data analyst is working in BigQuery and needs to create a visualization that shows the relationship between advertising spend and revenue for each day over the past month. The data is in a table with columns `date`, `ad_spend`, and `revenue`. They want to quickly identify if there is a correlation. Which type of chart should they use in Looker Studio?
A retail analytics team stores transaction data in a BigQuery table named `sales.transactions` with columns `order_id`, `customer_id`, `order_ts`, and `amount`. A Looker Studio report uses this table as its data source. The team wants every report viewer to see only rows where `amount` is greater than 0, without modifying the underlying BigQuery table. Where should they enforce this filter so it applies to the entire report regardless of which chart a viewer interacts with?
You are analyzing a BigQuery table of e-commerce orders and want to identify the top 5 product categories by total revenue for each month in 2024. You need to produce a result set with columns `order_month`, `category`, and `total_revenue`. Which SQL technique should you use?
A data analyst is using Looker Studio to create a dashboard for a sales team. They want to enable users to interact with the data and explore different dimensions without leaving the dashboard. Which two features should they add to the report? (Choose two.)
A retail analytics team stores point-of-sale transactions in a BigQuery table named `sales.transactions` that is partitioned by a DATE column called `transaction_date`. An analyst must produce a report showing only the transactions from the previous calendar month, and the report will be refreshed on the first day of every month. Which query pattern most efficiently retrieves the required data while minimizing bytes processed?
You are building a Looker Studio report connected to a BigQuery table that contains billions of rows. The report includes several charts and filters. Users report that the report is slow to load and that changing a filter takes a long time. Which TWO actions should you take to improve performance? (Choose two.)
A data analyst has a Looker Studio report connected to a BigQuery table containing millions of rows. The report includes a table chart that shows aggregated sales by product category. Users complain that the report takes a long time to load. Which action should the analyst take to improve performance without changing the report's layout?
A financial analyst needs a Looker Studio report that displays the same revenue chart but filtered by a different region on each of four pages, without duplicating the underlying BigQuery data source. The report currently uses one chart that reads from a BigQuery view. What should the analyst do to reuse the chart across pages with different region filters?
You have a Looker Studio report that uses a BigQuery data source. You need to add a chart that shows the total number of orders per day for the last 30 days. The date field is named `order_date`. Which chart type and dimension setup should you use?
A junior analyst has written a BigQuery SQL statement that joins an orders table to a customers table and then aggregates total spend per customer. Before running it against production data, the analyst wants to confirm the query is syntactically valid and to see estimated bytes processed without incurring charges for scanning the full tables. What should the analyst do?
A data analyst is using BigQuery ML to create a linear regression model to predict customer lifetime value based on historical data. After training the model, they want to evaluate its performance. Which BigQuery ML function should they use to get evaluation metrics such as R-squared and mean absolute error?
A team wants to display a BigQuery query result inside a Google Sheets spreadsheet so non-technical staff can view the latest figures. The data must refresh automatically each morning without anyone opening the sheet and clicking a refresh button. What should the team configure?
A product team uses Looker Studio to visualize metrics from a BigQuery table that is updated by an hourly ETL job. Users report that the dashboard shows data that is several hours stale even though the ETL completes successfully. The data source was configured with a custom query rather than a direct table reference. What is the most likely cause of the staleness?
A retail analytics team runs a Looker Explore against a BigQuery table containing order line items. Analysts need a single visual that shows the average order value per country, but the underlying table stores one row per line item, so multiple rows share the same order_id. Which approach produces a correct average order value per country?
A data analyst must present BigQuery results to executives in a way that lets them explore trends by region and product without writing SQL. The team is standardizing on Google Cloud tools and wants the presentation layer to query BigQuery directly. Which two Google Cloud components should the analyst combine to meet these requirements? (Choose two.)
You have a BigQuery table containing millions of rows of web server logs. You need to run a query that filters on a timestamp column and returns only the last 24 hours of data. The table is not partitioned. What should you do to improve query performance and reduce cost for this and future similar queries?
A data practitioner is building a Looker Studio report connected to a BigQuery table that contains millions of rows. The report currently returns an error indicating the query result exceeds the row limit, and stakeholders also complain that the charts take too long to render. Which two actions should the practitioner take to address these issues? (Choose two.)
An analyst has a BigQuery table `events.clicks` with columns `event_ts`, `country`, and `clicks`. They want a Looker Studio time series that shows a rolling 7-day average of clicks per country, updating as new data lands. The analyst wants the rolling calculation to happen in the database rather than in the visualization. What is the most appropriate approach?
An analyst has a BigQuery table of website events partitioned by event_date. A stakeholder asks for a quick chart of daily active users for the last 30 days, and cost must stay minimal. Which query pattern best satisfies this request?
A financial analyst needs a Looker dashboard tile that shows month-over-month revenue growth as a percentage. The underlying BigQuery table stores completed transactions, and the analyst wants the tile to update without manual intervention each month. Which approach should the analyst use in Looker?
A team maintains a Looker dashboard fed by a BigQuery table that receives streaming inserts throughout the day. Users report that totals on the dashboard sometimes disagree with a report generated directly in BigQuery a few minutes later. What is the most likely explanation for the discrepancy?
A data team is building a BigQuery ML model to predict customer churn directly from a BigQuery table. They want to evaluate the model's quality and understand which input features influenced its predictions. Which two BigQuery ML capabilities should they use to accomplish these goals? (Choose two.)
You are designing a Looker Studio report for a sales team. The report must allow users to filter data by region and product category, and also drill down from country to city. Which two features should you implement to meet these requirements? (Choose two.)
A data team stores raw event data in a BigQuery table called `events` with columns `event_time` (TIMESTAMP), `user_id` (STRING), and `event_type` (STRING). The table is partitioned by DATE(event_time). Analysts frequently run queries that filter on `event_type` and also restrict `event_time` to the last 7 days. These queries scan the entire 7-day partition range, causing higher-than-expected costs. The team wants to reduce bytes scanned without changing the table's partitioning scheme. What should they do?