Exam: ARA-C01
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Description
Unveil the secrets of becoming a certified Snowflake Advanced Architect by
immersing yourself in this comprehensive mock exam course. Specifically tailored
for professionals striving to validate and deepen their expertise, this course
provides an authentic exam environment designed around the rigorous standards
set by Snowflake.
Each mock test meticulously mirrors the real examination, spanning across the
intricacies of Snowflake's platform. Dive deep into design, performance,
security, and best-practice nuances, empowering you to tackle challenging
real-world scenarios. By meticulously replicating the weightage, pattern, and
difficulty of the original test, candidates emerge better prepared, confident,
and familiar with the examination structure.
Understand your weaknesses, fortify your strengths, and demystify the challenges
posed by the actual certification exam. Additionally, this dynamic question bank
is frequently updated, reflecting the most recent advancements and trends in
Snowflake's ecosystem.
Equip yourself with the confidence and expertise to not only crack the Snowflake
SnowPro Advanced Architect examination but also to excel in real-world
architectural challenges. Your journey to becoming a recognized Snowflake
specialist begins here!
Is it possible to take the practice test more than once?
Certainly, you are allowed to attempt each practice test multiple times.
Upon completion of the practice test, your final outcome will be displayed. With
every attempt, the sequence of questions and answers will be randomized.
Is there a time restriction for the practice tests?
Indeed, each test comes with a time constraint of 120 seconds for each
question.
What score is required?
The target achievement threshold for each practice test is to achieve at
least 75% correct answers.
Do the questions have explanations?
Yes, all questions have explanations for each answer.
Am I granted access to my responses?
Absolutely, you have the opportunity to review all the answers you submitted
and ascertain which ones were correct and which ones were not.
Are the questions updated regularly?
Indeed, the questions are routinely updated to ensure the best learning
experience.
Additional Note: It is strongly recommended that you take these exams multiple
times until you consistently score 90% or higher on each test. Take the
challenge without hesitation and start your journey today.
Who this course is for:
Professionals Preparing for Certification: Specifically, individuals who are
preparing to take the "Snowflake SnowPro Advanced Architect" certification exam
and wish to test their knowledge before the actual examination.
Snowflake Users: Individuals who are already familiar with Snowflake's basic and
intermediate features and functionalities, and are now looking to advance their
skills, especially in the architectural aspects of the
platform.
Data Architects and Engineers: Professionals who are responsible for designing,
building, and managing scalable, secure, and efficient solutions in Snowflake.
They might take this course to ensure their knowledge aligns with Snowflake's
best practices.
Database Administrators and IT Specialists: Individuals who manage and monitor
Snowflake or other database environments and are considering expanding or
validating their architectural skills specific to Snowflake.
Consultants and Solution Architects: Professionals who recommend, design, or
implement data solutions for various clients and want to ensure they are
up-to-date with Snowflake's advanced architectural practices.
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QUESTION 1
What built-in Snowflake features make use of the change tracking metadata
for a table? (Choose two.)
A. The MERGE command
B. The UPSERT command
C. The CHANGES clause
D. A STREAM object
E. The CHANGE_DATA_CAPTURE command
Answer: A, D
Explanation:
In Snowflake, the change tracking metadata for a table is utilized by the MERGE
command and the
STREAM object. The MERGE command uses change tracking to determine how to apply
updates and
inserts efficiently based on differences between source and target tables.
STREAM objects, on the
other hand, specifically capture and store change data, enabling incremental
processing based on
changes made to a table since the last stream offset was committed.
Reference: Snowflake Documentation on MERGE and STREAM Objects.
QUESTION 2
When using the Snowflake Connector for Kafka, what data formats are
supported for the messages?
(Choose two.)
A. CSV
B. XML
C. Avro
D. JSON
E. Parquet
Answer: C, D
Explanation:
The data formats that are supported for the messages when using the Snowflake
Connector for Kafka
are Avro and JSON. These are the two formats that the connector can parse and
convert into
Snowflake table rows. The connector supports both schemaless and schematized
JSON, as well as
Avro with or without a schema registry1. The other options are incorrect because
they are not
supported data formats for the messages. CSV, XML, and Parquet are not formats
that the connector
can parse and convert into Snowflake table rows. If the messages are in these
formats, the connector
will load them as VARIANT data type and store them as raw strings in the
table2. Reference: Snowflake Connector for Kafka | Snowflake Documentation,
Loading Protobuf
Data using the Snowflake Connector for Kafka | Snowflake Documentation
QUESTION 3
At which object type level can the APPLY MASKING POLICY, APPLY ROW ACCESS
POLICY and APPLY
SESSION POLICY privileges be granted?
A. Global
B. Database
C. Schema
D. Table
Answer: A
Explanation:
The object type level at which the APPLY MASKING POLICY, APPLY ROW ACCESS POLICY
and APPLY
SESSION POLICY privileges can be granted is global. These are account-level
privileges that control
who can apply or unset these policies on objects such as columns, tables, views,
accounts, or users.
These privileges are granted to the ACCOUNTADMIN role by default, and can be
granted to other
roles as needed. The other options are incorrect because they are not the object
type level at which
these privileges can be granted. Database, schema, and table are lower-level
object types that do not
support these privileges. Reference: Access Control Privileges | Snowflake
Documentation, Using
Dynamic Data Masking | Snowflake Documentation, Using Row Access Policies |
Snowflake
Documentation, Using Session Policies | Snowflake Documentation
QUESTION 4
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV
files into a table
called TABLEA, using its table stage. One file named file5.csv fails to load.
The Architect fixes the file
and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the
stage? (Choose two.)
A. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
B. COPY INTO tablea FROM @%tablea;
C. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');
D. COPY INTO tablea FROM @%tablea FORCE = TRUE;
E. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
F. COPY INTO tablea FROM @%tablea MERGE = TRUE;
Answer: BC
Explanation:
Option A (RETURN_FAILED_ONLY) will only load files that previously failed to
load. Since file5.csv
already exists in the stage with the same name, it will not be considered a new
file and will not be loaded.
Option D (FORCE) will overwrite any existing data in the table. This is not
desired as we only want to load the data from file5.csv.
Option E (NEW_FILES_ONLY) will only load files that have been added to the stage
since the last
COPY command. This will not work because file5.csv was already in the stage
before it was fixed.
Option F (MERGE) is used to merge data from a stage into an existing table,
creating new rows for
any data not already present. This is not needed in this case as we simply want
to load the data from file5.csv.
Therefore, the architect can use either COPY INTO tablea FROM @%tablea or COPY
INTO tablea
FROM @%tablea FILES = ('file5.csv') to load only file5.csv from the stage. Both
options will load the
data from the specified file without overwriting any existing data or requiring
additional configuration
QUESTION 5
A large manufacturing company runs a dozen individual Snowflake accounts
across its business divisions.
The company wants to increase the level of data sharing to support supply chain
optimizations and increase its purchasing leverage with multiple vendors.
The companys Snowflake Architects need to design a solution that would allow the
business
divisions to decide what to share, while minimizing the level of effort spent on
configuration and
management. Most of the company divisions use Snowflake accounts in the same
cloud
deployments with a few exceptions for European-based divisions.
According to Snowflake recommended best practice, how should these requirements
be met?
A. Migrate the European accounts in the global region and manage shares in a
connected graph architecture. Deploy a Data Exchange.
B. Deploy a Private Data Exchange in combination with data shares for the
European accounts.
C. Deploy to the Snowflake Marketplace making sure that invoker_share() is used
in all secure views.
D. Deploy a Private Data Exchange and use replication to allow European data
shares in the Exchange.
Answer: D
Explanation:
According to Snowflake recommended best practice, the requirements of the large
manufacturing
company should be met by deploying a Private Data Exchange in combination with
data shares for
the European accounts. A Private Data Exchange is a feature of the Snowflake
Data Cloud platform
that enables secure and governed sharing of data between organizations. It
allows Snowflake
customers to create their own data hub and invite other parts of their
organization or external
partners to access and contribute data sets. A Private Data Exchange provides
centralized
management, granular access control, and data usage metrics for the data shared
in the exchange1.
A data share is a secure and direct way of sharing data between Snowflake
accounts without having
to copy or move the data. A data share allows the data provider to grant
privileges on selected
objects in their account to one or more data consumers in other accounts2. By
using a Private Data
Exchange in combination with data shares, the company can achieve the following
benefits:
The business divisions can decide what data to share and publish it to the
Private Data Exchange,
where it can be discovered and accessed by other members of the exchange. This
reduces the effort
and complexity of managing multiple data sharing relationships and
configurations.
The company can leverage the existing Snowflake accounts in the same cloud
deployments to create
the Private Data Exchange and invite the members to join. This minimizes the
migration and setup
costs and leverages the existing Snowflake features and security.
The company can use data shares to share data with the European accounts that
are in different
regions or cloud platforms. This allows the company to comply with the regional
and regulatory
requirements for data sovereignty and privacy, while still enabling data
collaboration across the organization.
The company can use the Snowflake Data Cloud platform to perform data analysis
and
transformation on the shared data, as well as integrate with other data sources
and applications. This
enables the company to optimize its supply chain and increase its purchasing
leverage with multiple vendors.
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Students Feedback / Reviews/ Discussion
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Emirates
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upvoted 2 times
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upvoted 2 times
Danny 1 month, 1 week ago - United States CUSTOMER_STATE_NAME: Costa Mesa =
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