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Kostenlose gültige Prüfung Snowflake ADA-C01 Sammlung - Examcollection

Mit Fast2test können Sie ganz leicht die Snowflake ADA-C01 Prüfung bestehen. Wenn Sie die Snowflake ADA-C01 Schulungsunterlagen im Fast2test wählen und Snowflake ADA-C01 die Prüfungsfragen und Anworten zur Zertifizierungsprüfung herunterladen, werden Sie sicher selbstbewusster sein, dass Sie die Prüfung ganz leicht bestehen können. Obwohl es auch andere Prüfungsunterlagen zur Snowflake ADA-C01 Zertifizierungsprüfung auf andere Websites gibt, versprechen wir Ihnen, dass unsere Produkte am besten sind. Unsere Übungsfragen-und antworten sind sehr präzis. Sue umfassen viele Wissensgebiete. Sie sind immer erneuert und ergänzt. Deshalb steht unser Fast2test Ihnen eine genauige Prüfungsvorbereitung zur Verfügung. Wenn Sie Fast2test wählen, können Sie viel Zeit ersparen, ganz leicht und schnell die Snowflake ADA-C01 Zertifizierungsprüfung bestehen und so schnell wie möglich ein IT-Fachmann in der Snowflake IT-Branche werden.

Snowflake ADA-C01 Prüfungsplan:

Thema
Einzelheiten

Thema 1

Given a scenario, create and manage access control
Given a scenario, implement resource monitors

Thema 2

Interpret and make recommendations for data clustering
Manage DML locking and concurrency in Snowflake

Thema 3

Given a scenario, manage databases, tables, and views
Manage organizations and access control

Thema 4

Manage and implement data sharing
Given a set of business requirements, establish access control architecture

Thema 5

Given a scenario, configure access controls
Set up and manage security administration and authorization

Thema 6

Set up and manage network and private connectivity
Given a scenario, manage Snowflake Time Travel and Fail-safe

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ADA-C01 Übungsmaterialien - ADA-C01 Antworten

Möchten Sie die Snowflake ADA-C01 Zertifizierungsprüfung beim ersten Versuch bestehen? Auf der Webseite Fast2test werden wir alle Ihrer Wünsche erfüllen und Ihnen versprechen, dass Sie die ADA-C01 Zertifizierungsprüfung in begrenzter Zeit einmalig bestehen. Denn Fast2test verfügt über die Fragenkataloge zur Snowflake ADA-C01 Zertifizierungsprüfung, die von erfahrenen IT-Experten entworfen werden und aus Fragen und Antworten kombiniert sind. Sie werden niemals bereuen, dass Sie Fast2test gewählt haben. bearbeitet

Snowflake SnowPro Advanced Administrator ADA-C01 Prüfungsfragen mit Lösungen (Q78-Q83):

78. Frage
A retailer uses a TRANSACTIONS table (100M rows, 1.2 TB) that has been clustered by the STORE_ID column (varchar(50)). The vast majority of analyses on this table are grouped by STORE_ID to look at store performance.
There are 1000 stores operated by the retailer but most sales come from only 20 stores. The Administrator notes that most queries are currently experiencing poor pruning, with large amounts of bytes processed by even simple queries.
Why is this occurring?

A. The STORE_ID should be numeric.
B. The table is not big enough to take advantage of the clustering key.
C. The cardinality of the stores to transaction count ratio is too low to use the STORE_ID as a clustering key.
D. Sales across stores are not uniformly distributed.

Antwort: D

Begründung:
According to the Snowflake documentation1, clustering keys are most effective when the data is evenly distributed across the key values. If the data is skewed, such as in this case where most sales come from only 20 stores out of 1000, then the micro-partitions will not be well-clustered and the pruning will be poor. This means that more bytes will be scanned by queries, even if they filter by STORE_ID. Option A is incorrect because the data type of the clustering key does not affect the pruning. Option B is incorrect because the table is large enough to benefit from clustering, if the data was more balanced. Option D is incorrect because the cardinality of the clustering key is not relevant for pruning, as long as the key values are distinct.
1: Considerations for Choosing Clustering for a Table | Snowflake Documentation

79. Frage
An Administrator receives data from a Snowflake partner. The partner is sharing a dataset that contains multiple secure views. The Administrator would like to configure the data so that only certain roles can see certain secure views.
How can this be accomplished?

A. Create views over the incoming shared database and apply the desired RBAC onto these views.
B. Clone the data and insert it into a company-owned share and apply the desired RBAC on the new tables.
C. Apply RBAC directly onto the partner's shared secure views.
D. Individually grant imported privileges onto the schema in the share.

Antwort: A

Begründung:
According to the Snowflake documentation1, secure views are only exposed to authorized users who have been granted the role that owns the view. Therefore, applying RBAC directly onto the partner's shared secure views (option A) is not possible, as the administrator does not own those views. Individually granting imported privileges onto the schema in the share (option B) is also not feasible, as the privileges granted on the schema do not apply to existing secure views, only to future ones2. Cloning the data and inserting it into a company-owned share (option C) is not recommended, as it would create unnecessary duplication of data and increase storage costs. The best option is to create views over the incoming shared database and apply the desired RBAC onto these views (option D). This way, the administrator can control the access to the data based on the roles in their account, without modifying the original data or views from the partner.

80. Frage
When a role is dropped, which role inherits ownership of objects owned by the dropped role?

A. The role executing the command
B. The SYSADMIN role
C. The SECURITYADMIN role
D. The role above the dropped role in the RBAC hierarchy

Antwort: D

Begründung:
According to the Snowflake documentation1, when a role is dropped, ownership of all objects owned by the dropped role is transferred to the role that is directly above the dropped role in the role hierarchy. This is to ensure that there is always a single owner for each object in the system.
1: Drop Role | Snowflake Documentation

81. Frage
A Snowflake user runs a complex SQL query on a dedicated virtual warehouse that reads a large amount of data from micro-partitions. The same user wants to run another query that uses the same data set.
Which action would provide optimal performance for the second SQL query?

A. Prevent the virtual warehouse from suspending between the running of the first and secondqueries.
B. Increase the STATEMENT_TIMEOUT_IN_SECONDS parameter in the session.
C. Use the RESULT_SCAN function to post-process the output of the first query.
D. Assign additional clusters to the virtual warehouse.

Antwort: C

Begründung:
Explanation
According to the Using Persisted Query Results documentation, the RESULT_SCAN function allows you to query the result set of a previous command as if it were a table. This can improve the performance of the second query by avoiding reading the same data from micro-partitions again. The other actions do not provide optimal performance for the second query because:
*Assigning additional clusters to the virtual warehouse does not affect the data access speed, but only the query execution speed. It also increases the cost of the warehouse.
*Increasing the STATEMENT_TIMEOUT_IN_SECONDS parameter in the session does not improve the performance of the query, but only allows it to run longer before timing out. It also increases the risk of resource contention and deadlock.
*Preventing the virtual warehouse from suspending between the running of the first and second queries does not guarantee that the data will be cached in memory, as Snowflake uses a least recently used (LRU) cache eviction policy. It also increases the cost of the warehouse.
https://docs.snowflake.com/en/user-guide/querying-persisted-results

82. Frage
An organization's sales team leverages this Snowflake query a few times a day:
SELECT CUSTOMER ID, CUSTOMER_NAME, ADDRESS, PHONE NO
FROM CUSTOMERS
WHERE LAST UPDATED BETWEEN TO_DATE (CURRENT_TIMESTAMP) AND (TO_DATE
(CURRENT_TIMESTAMP) -7);
What can the Snowflake Administrator do to optimize the use of persisted query results whenever possible?

A. Wrap the query in a User-Defined Function (UDF) to match syntax execution.
B. Assign everyone on the sales team to the same security role.
C. Assign everyone on the sales team to the same virtual warehouse.
D. Leverage the CURRENT_DATE function for date calculations.

Antwort: D

Begründung:
Explanation
According to the web search results from my predefined tool search_web, one of the factors that affects the reuse of persisted query results is the exact match of the query syntax1. If the query contains functions that return different values for successive runs, such as CURRENT_TIMESTAMP, then the query will not match the previous query and will not benefit from the cache. To avoid this, the query should use functions that return consistent values for the same day, such as CURRENT_DATE, which returns the current date without the time component2. Option A is incorrect because wrapping the query in a UDF does not guarantee the syntax match, as the UDF may also contain dynamic functions. Option B is incorrect because the virtual warehouse does not affect the persisted query results, which are stored at the account level1. Option C is incorrect because the security role does not affect the persisted query results, as long as the role has the necessary privileges to access the tables and views used in the query1.
1: Using Persisted Query Results | Snowflake Documentation 2: Date and Time Functions | Snowflake Documentation

83. Frage
......

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