RELIABLE ARA-R01 DUMPS | ARA-R01 RELIABLE CRAM MATERIALS

Reliable ARA-R01 Dumps | ARA-R01 Reliable Cram Materials

Reliable ARA-R01 Dumps | ARA-R01 Reliable Cram Materials

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Snowflake ARA-R01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Performance Optimization: This section is about summarizing performance tools, recommended practices, and their ideal application scenarios, addressing performance challenges within current architectures, and resolving them.
Topic 2
  • Accounts and Security: This section relates to creating a Snowflake account and a database strategy aligned with business needs. Users are tested for developing an architecture that satisfies data security, privacy, compliance, and governance standards.
Topic 3
  • Data Engineering: This section is about identifying the optimal data loading or unloading method to fulfill business requirements. Examine the primary tools within Snowflake's ecosystem and their integration with the platform.
Topic 4
  • Snowflake Architecture: This section assesses examining the advantages and constraints of different data models, devises data-sharing strategies, and developing architectural solutions that accommodate Development Lifecycles and workload needs.

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Snowflake ARA-R01 Reliable Cram Materials & Exam ARA-R01 Material

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Snowflake SnowPro Advanced: Architect Recertification Exam Sample Questions (Q76-Q81):

NEW QUESTION # 76
What is the MOST efficient way to design an environment where data retention is not considered critical, and customization needs are to be kept to a minimum?

  • A. Use a transient table.
  • B. Use a temporary table.
  • C. Use a transient schema.
  • D. Use a transient database.

Answer: D

Explanation:
Transient databases in Snowflake are designed for situations where data retention is not critical, and they do not have the fail-safe period that regular databases have. This means that data in a transient database is not recoverable after the Time Travel retention period. Using a transient database is efficient because it minimizes storage costs while still providing most functionalities of a standard database without the overhead of data protection features that are not needed when data retention is not a concern.


NEW QUESTION # 77
The Business Intelligence team reports that when some team members run queries for their dashboards in parallel with others, the query response time is getting significantly slower What can a Snowflake Architect do to identify what is occurring and troubleshoot this issue?

  • A. A close up of text Description automatically generated
  • B. A computer error message Description automatically generated
  • C. A black text on a white background Description automatically generated
  • D. A screen shot of a computer Description automatically generated

Answer: B

Explanation:
The image shows a SQL query that can be used to identify which queries are spilled to remote storage and suggests changing the warehouse parameters to address this issue. Spilling to remote storage occurs when the memory allocated to a warehouse is insufficient to process a query, and Snowflake uses disk or cloud storage as a temporary cache. This can significantly slow down the query performance and increase the cost. To troubleshoot this issue, a Snowflake Architect can run the query shown in the image to find out which queries are spilling, how much data they are spilling, and which warehouses they are using. Then, the architect can adjust the warehouse size, type, or scaling policy to provide enough memory for the queries and avoid spilling12. References:
Recognizing Disk Spilling
Managing the Kafka Connector


NEW QUESTION # 78
Which technique will efficiently ingest and consume semi-structured data for Snowflake data lake workloads?

  • A. Schema-on-write
  • B. Information schema
  • C. IDEF1X
  • D. Schema-on-read

Answer: D

Explanation:
Option C is the correct answer because schema-on-read is a technique that allows Snowflake to ingest and consume semi-structured data without requiring a predefined schema. Snowflake supports various semi-structured data formats such as JSON, Avro, ORC, Parquet, and XML, and provides native data types (ARRAY, OBJECT, and VARIANT) for storing them. Snowflake also provides native support for querying semi-structured data using SQL and dot notation. Schema-on-read enables Snowflake to query semi-structured data at the same speed as performing relational queries while preserving theflexibility of schema-on-read.
Snowflake's near-instant elasticity rightsizes compute resources, and consumption-based pricing ensures you only pay for what you use.
Option A is incorrect because IDEF1X is a data modeling technique that defines the structure and constraints of relational data using diagrams and notations. IDEF1X is not suitable for ingesting and consuming semi-structured data, which does not have a fixed schema or structure.
Option B is incorrect because schema-on-write is a technique that requires defining a schema before loading and processing data. Schema-on-write is not efficient for ingesting and consuming semi-structured data, which may have varying or complex structures that are difficult to fit into a predefined schema. Schema-on-write also introduces additional overhead and complexity for data transformation and validation.
Option D is incorrect because information schema is a set of metadata views that provide information about the objects and privileges in a Snowflake database. Information schema is not a technique for ingesting and consuming semi-structured data, but rather a way of accessing metadata about the data.
References:
Semi-structured Data
Snowflake for Data Lake


NEW QUESTION # 79
Files arrive in an external stage every 10 seconds from a proprietary system. The files range in size from 500 K to 3 MB. The data must be accessible by dashboards as soon as it arrives.
How can a Snowflake Architect meet this requirement with the LEAST amount of coding? (Choose two.)

  • A. Use a materialized view on an external table.
  • B. Use a combination of a task and a stream.
  • C. Use a COPY command with a task.
  • D. Use the COPY INTO command.
  • E. Use Snowpipe with auto-ingest.

Answer: A,E

Explanation:
These two options are the best ways to meet the requirement of loading data from an external stage and making it accessible by dashboards with the least amount of coding.
Snowpipe with auto-ingest is a feature that enables continuous and automated data loading from an external stage into a Snowflake table. Snowpipe uses event notifications from the cloud storage service to detect new or modified files in the stage and triggers a COPY INTO command to load the data into the table. Snowpipe is efficient, scalable, and serverless, meaning it does not require any infrastructure or maintenance from the user. Snowpipe also supports loading data from files of any size, as long as they are in a supported format1.
A materialized view on an external table is a feature that enables creating a pre-computed result set from an external table and storing it in Snowflake. A materialized view can improve the performance and efficiency of querying data from an external table, especially for complex queries or dashboards. A materialized view can also support aggregations, joins, and filters on the external table data. A materialized view on an external table is automatically refreshed when the underlying data in the external stage changes, as long as the AUTO_REFRESH parameter is set to true2.
References:
Snowpipe Overview | Snowflake Documentation
Materialized Views on External Tables | Snowflake Documentation


NEW QUESTION # 80
The data share exists between a data provider account and a data consumer account. Five tables from the provider account are being shared with the consumer account. The consumer role has been granted the imported privileges privilege.
What will happen to the consumer account if a new table (table_6) is added to the provider schema?

  • A. The consumer role will automatically see the new table and no additional grants are needed.
  • B. The consumer role will see the table only after this grant is given on the consumer side:
    grant imported privileges on database PSHARE_EDW_4TEST_DB to DEV_ROLE;
  • C. The consumer role will see the table only after this grant is given on the provider side:
    use role accountadmin;
    grant usage on database EDW to share PSHARE_EDW_4TEST ;
    grant usage on schema EDW.ACCOUNTING to share PSHARE_EDW_4TEST ;
    Grant select on table EDW.ACCOUNTING.Table_6 to database PSHARE_EDW_4TEST_DB ;
  • D. The consumer role will see the table only after this grant is given on the provider side:
    use role accountadmin;
    Grant select on table EDW.ACCOUNTING.Table_6 to share PSHARE_EDW_4TEST;

Answer: C

Explanation:
When a new table (table_6) is added to a schema in the provider's account that is part of a data share, the consumer will not automatically see the new table. The consumer will only be able to access the new table once the appropriate privileges are granted by the provider. The correct process, as outlined in option D, involves using the provider's ACCOUNTADMIN role to grant USAGE privileges on the database and schema, followed by SELECT privileges on the new table, specifically to the share that includes the consumer's database. This ensures that the consumer account can access the new table under the established data sharing setup.References:
* Snowflake Documentation on Managing Access Control
* Snowflake Documentation on Data Sharing


NEW QUESTION # 81
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