Cloudera CDP Data Analyst (CDP-4001) Certification Exam Sample Questions

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Cloudera CDP-4001 Sample Questions:

01. A compliance reviewer at Ridgeline Sports needs a complete list of every table and column across the cluster that has been classified as containing sensitive personal information, ahead of an upcoming audit.
Which approach is best suited to producing that list?
a) Search Apache Atlas by the classification label to retrieve every asset tagged with it across the cluster
b) Review Ranger audit logs to see which tables were queried most frequently by any user over the past quarter
c) Check the business glossary for terms whose names happen to include the word sensitive somewhere in the title
d) Ask each team individually to self-report which of their tables they believe might contain sensitive data, then compile the responses into one list
 
02. Foxglove Analytics needs to query raw log files that already exist in an HDFS directory owned and maintained by another team, without Hive taking over the lifecycle of those underlying files.
Which statement correctly defines a table over this data?
a) CREATE TABLE raw_logs (event_id STRING, event_ts STRING) LOCATION '/data/foxglove/raw_logs';, since a managed table also leaves existing files untouched when the table is dropped.
b) CREATE EXTERNAL VIEW raw_logs AS SELECT * FROM raw_logs_source;, since only a view can reference files owned by another team.
c) CREATE EXTERNAL TABLE raw_logs (event_id STRING, event_ts STRING) LOCATION '/data/foxglove/raw_logs';
d) CREATE TEMPORARY TABLE raw_logs (event_id STRING, event_ts STRING) LOCATION '/data/foxglove/raw_logs';, since temporary tables never take ownership of any file data.
 
03. Thistledown Media needs a new Hive table named viewer_logs to store a numeric viewer identifier, the number of minutes watched, and the date watched recorded as text.
Which statement correctly creates this table?
a) CREATE VIEW viewer_logs (viewer_id INT, watch_minutes INT, watched_on STRING);, since a view can define its own column list and store new rows directly.
b) CREATE TABLE viewer_logs (viewer_id INT, watch_minutes INT, watched_on STRING);
c) ALTER TABLE viewer_logs ADD COLUMNS (viewer_id INT, watch_minutes INT, watched_on STRING);, which creates the table with these columns the first time it is referenced.
d) INSERT TABLE viewer_logs (viewer_id INT, watch_minutes INT, watched_on STRING);, which both defines and populates the table in a single step.
 
04. A data engineer at Palisade Media Group runs a DDL statement in Impala that adds a new column to a shared table. Moments later, colleagues querying the same table from other Impala daemons across the cluster see the new column reflected in their sessions.
Which Impala service is primarily responsible for propagating that schema change across the cluster?
a) HDFS NameNode, which tracks all schema metadata for tables stored in the Hadoop filesystem and notifies query engines of changes.
b) The individual impalad process that executed the DDL statement, which pushes the change directly to every other daemon's local cache without any intermediary service.
c) The statestore, which is responsible for propagating schema and DDL metadata changes to every daemon in the cluster.
d) The catalog service (catalogd), which distributes metadata changes such as DDL updates to the Impala daemons cluster-wide.
 
05. Ironwood Manufacturing frequently joins a very large orders table to a customers table on a customer identifier that has millions of distinct values, and the join is a major bottleneck in nightly reporting.
Which design choice is most appropriate for improving this join's performance?
a) Storing the orders table as uncompressed text so the join can scan its rows more quickly during the join operation itself
b) Partitioning the orders table on the customer identifier so each distinct value gets its own directory
c) Removing the customer identifier column from the orders table so the join has fewer columns left to compare
d) Bucketing the orders table on the customer identifier so matching rows are grouped into a fixed number of files
 
06. Driftwood Freight has a shipment_cost column that is entirely NULL for every row belonging to one particular carrier, because that carrier's invoices have not yet been processed.
When an analyst runs SUM(shipment_cost) grouped by carrier, what does that carrier's group return?
a) SUM(shipment_cost) returns NULL for that carrier's group, since there are no non-NULL values to add together.
b) SUM(shipment_cost) returns the row count of that carrier's group instead of a monetary total.
c) The query raises an error and returns no rows at all when a group's shipment_cost values are entirely NULL.
d) SUM(shipment_cost) returns 0 for that carrier's group, since SQL treats every NULL value as zero when summing a column.
 
07. Northfield Utilities stores meter-billing amounts in a column with several decimal places of precision, for example 128.457812. For a customer-facing summary, the report needs each amount displayed rounded to exactly two decimal places, matching standard currency formatting.
Which expression achieves this in the query?
a) Store the amount as a STRING and manually cut off everything after the second decimal point using text functions.
b) Leave the column as-is and rely on the reporting tool's display settings to hide the extra digits without changing the underlying value.
c) Apply CAST(amount AS DECIMAL(10,2)) so the value is rounded to two decimal places at query time.
d) Multiply the amount by 100, truncate any remaining decimal digits, and divide by 100 again in a separate downstream reporting tool.
 
08. An engineer at Sterling Distribution is deciding whether to apply compression to a large analytical table. Storage cost and scan I/O would clearly improve, but a colleague raises a concern about the trade-off involved.
Which statement best describes the genuine trade-off of adding compression to this table?
a) Compression increases the amount of data read from disk because compressed blocks must be read alongside an uncompressed index copy of the same data.
b) Compression reduces the data volume read from and stored on disk, but it adds CPU overhead to decompress the data during every scan.
c) Compression only reduces storage footprint and has no effect whatsoever on scan performance in either direction.
d) Compression carries no real downside and should be applied to every table as a default step, regardless of its query pattern or the cluster's available CPU capacity.
 
09. Willowbrook University keeps an enrollments table listing one row per student per course. An analyst needs the number of students enrolled in each course_id.
Which query is correct?
a) SELECT course_id, COUNT(*) FROM enrollments GROUP BY course_id;
b) SELECT course_id, COUNT(*) FROM enrollments;, since a single COUNT(*) without GROUP BY still breaks the total out separately by course_id.
c) SELECT course_id, COUNT(course_id) FROM enrollments GROUP BY student_id;, since grouping by student_id still produces one row per course showing its enrollment count.
d) SELECT student_id, COUNT(*) FROM enrollments GROUP BY course_id;, since selecting student_id instead of course_id still labels each count with its correct course.
 
10. Amberlight Retail wants a single visual that lets viewers quickly compare total sales across six product categories for the current month, with no need to show any trend over time.
Which visual type best fits this requirement?
a) A line chart, which is generally built to emphasize how a measure changes continuously across a time axis
b) A scatter plot, which is generally built to reveal the relationship between two independent numeric measures
c) A bar chart, which compares a measure across a small set of discrete categories clearly
d) A single KPI tile, which is generally built to display one overall total rather than a per-category breakdown

Answers:

Question: 1 Answer: a Question: 2 Answer: c
Question: 3 Answer: b Question: 4 Answer: d
Question: 5 Answer: d Question: 6 Answer: a
Question: 7 Answer: c Question: 8 Answer: b
Question: 9 Answer: a Question: 10 Answer: c

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