Snowflake ARA-C01 Exam With Confidence Using Practice Dumps

To ensure that ananalyst_usercan only access Snowflake from specific IP addresses, the following steps are required:

Option B: This alters the network policy directly linked toanalyst_user. Setting a network policy on the user level is effective and ensures that the specified network restrictions apply directly and exclusively to this user.

Option D: Before a network policy can be set or altered, the appropriate role with permission to manage network policies must be used.SECURITYADMINis typically the role that has privileges to create and manage network policies in Snowflake. Creating a network policy that specifies allowed IP addresses ensures that only requests coming from those IPs can access Snowflake under this policy. After creation, this policy can be linked to specific users or roles as needed.

Options A and E mention altering roles or using the wrong role (USERADMINtypically does not manage network security settings), and option C incorrectly attempts to set a network policy directly as an IP address, which is not syntactically or functionally valid.

 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 the flexibility 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.

These three design elements are required to meet the security, compliance, and governance requirements for the project.

To use Tri-Secret Secure in Snowflake, the Business Critical edition of Snowflake is required. This edition provides enhanced data protection features, such as customer-managed encryption keys, that are not available in lower editions. Tri-Secret Secure is a feature that combines a Snowflake-maintained key and a customer-managed key to create a composite master key to encrypt the data in Snowflake1.

To share some information stored in a view with another Snowflake customer, a secure view is recommended. A secure view is a view that hides the underlying data and the view definition from unauthorized users. Only the owner of the view and the users who are granted the owner’s role can see the view definition and the data in the base tables of the view2. A secure view can be shared with another Snowflake account using a data share3.

To hide portions of sensitive information from some columns, Dynamic Data Masking can be used. Dynamic Data Masking is a feature that allows applying masking policies to columns to selectively mask plain-text data at query time. Depending on the masking policy conditions and the user’s role, the data can be fully or partially masked, or shown as plain-text4.