Itcertkr는 여러분의 요구를 만족시켜드리는 사이트입니다. 많은 분들이 우리사이트의 it인증덤프를 사용함으로 관련it시험을 안전하게 패스를 하였습니다. 이니 우리 Itcertkr사이트의 단골이 되었죠. Itcertkr에서는 최신의Microsoft DP-750자료를 제공하며 여러분의Microsoft DP-750인증시험에 많은 도움이 될 것입니다.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploy and manage data pipelines and workloads | 30-35% | - Operational reliability
|
| Topic 2: Prepare and process data | 30-35% | - Data quality and validation
|
| Topic 3: Configure and manage Azure Databricks environments | 15-20% | - Workspace and compute configuration
|
| Topic 4: Secure and govern data using Unity Catalog | 15-20% | - Access control and policies
|
근 몇년간IT산업이 전례없이 신속히 발전하여 IT업계에 종사하는 분들이 여느때보다 많습니다. 경쟁이 이와같이 치열한 환경속에서 누구도 대체할수 없는 자기만의 자리를 찾으려면 IT인증자격증취득은 무조건 해야 하는것이 아닌가 싶습니다. Microsoft인증 DP-750시험은 IT인증시험중 가장 인기있는 시험입니다. Itcertkr에서는 여러분이Microsoft인증 DP-750시험을 한방에 패스하도록 실제시험문제에 대비한Microsoft인증 DP-750덤프를 발췌하여 저렴한 가격에 제공해드립니다.시험패스 못할시 덤프비용은 환불처리 해드리기에 고객님께 아무런 페를 끼치지 않을것입니다.
질문 # 71
Which operation guarantees ACID compliance in Delta Lake?
정답：C
설명：
Delta Lake ensures ACID compliance through its transaction log (Delta log). It tracks all changes, enabling consistency, isolation, and rollback capabilities. File append operations alone are not transactional. RDD transformations are low-level and not ACID-aware.
질문 # 72
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains two managed Delta tables named sales.schema1.table1 and sales.schema1.table2.
sales.schema1.table1 contains sales data from the current year.
sales.schema1 .table2 contains historical data.
You need to load all the rows from sales.schema1.table1 into sales.schema1.table2. The solution must preserve any existing data in sales.schema1.table2 and minimize processing effort.
Which command should you run?
정답：C
설명：
To load all rows from one table into the other while preserving existing data and minimizing processing effort, you should use the SQL INSERT INTO statement.
Preserves Data: INSERT INTO appends new rows to the target table without modifying or deleting the existing data.
Lowest Processing Effort: It performs a direct data append at the storage level. Unlike MERGE INTO, it does not scan the target table for matches, saving significant compute time and costs.
Delta Lake Optimization: Because these are Delta tables, appending data simply writes new parquet files and commits them to the transaction log, making the operation fast and efficient.
Reference:
https://medium.com/@gema.correa/handling-schema-evolution-and-schema-compensation-in-databricks-lessons-from-the-field-7af8d915beef
질문 # 73
You have an Azure Databricks account that contains workspaces enabled for Unity Catalog.
You need to implement audit logging to meet the following requirements:
* Capture audit logs for all the workspaces in the account.
* Retain the audit logs for 90 days.
* Minimize storage and ingestion costs.
The logs will be reviewed only during security investigations and will NOT be queried regularly.
To where should you send the audit logs?
정답：B
설명：
An Azure Storage account provides durable, comparatively low-cost retention for diagnostic and audit logs that are accessed infrequently. A lifecycle or retention policy can preserve the logs for 90 days and then remove them automatically. This matches an investigation-only access pattern without paying the ingestion and indexing charges associated with Log Analytics. Azure Monitor metrics stores numerical monitoring measurements, not the complete audit-event records required here. Azure Event Hubs is a streaming transport intended to forward events to consumers and is not the final long-term retention destination. Log Analytics is appropriate when teams need frequent querying, dashboards, and alerting, but those capabilities introduce unnecessary cost for logs reviewed only during occasional investigations. Storage therefore best satisfies centralized retention and cost requirements.
질문 # 74
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named finance, finance contains two schemas named default and procurement.
You need to create a table named assets in the procurement schema, assets must contain the following columns:
* asset.id
* asset, type
* asset_name
How should you complete the SQL statement? To answer, drag the appropriate values to the correct targets.
Each value may be used once, more than once, or not at all You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
The correct SQL statement uses the full three-part namespace finance.procurement.assets with the three specified columns.
In Unity Catalog, every object lives in a three-tier hierarchy: catalog # schema # table. Using the full path finance.procurement.assets guarantees the table lands in the right schema regardless of the session's current catalog or schema context. Omitting the catalog or schema name relies on the session default, which may not be finance.procurement - a silent mistake that's hard to catch.
The column names asset_id, asset_type, and asset_name must match the spec exactly. Unity Catalog applies access controls, lineage tracking, and tagging at the column level, so the names are meaningful beyond just the schema. Once created, any GRANT statements can target specific columns for fine-grained access control.
Reference: https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create- table-using
질문 # 75
You have an Azure Databricks workspace that contains multiple all-purpose clusters.
You discover that some clusters remain idle for long periods after users finish their work.
You need to reduce compute costs without affecting active workloads.
What should you do?
정답：B
설명：
To reduce compute costs from idle clusters without impacting active workloads, you must configure Auto-Termination and use Cluster Policies.
Core Remedies
*-> Auto-Termination: Set a strict inactivity timeout (e.g., 20-30 minutes) on all-purpose clusters to automatically shut them down when idle.
Cluster Policies: Enforce maximum auto-termination limits across the workspace so users cannot disable or set excessively long idle timeouts.
Single User Access Mode: Use this mode where possible, as it tracks idleness more accurately than Shared mode by monitoring the specific user's activity.
Reference:
https://medium.com/@sujathamudadla1213/databricks-lakehouse-platform-describe-how- clusters-are-terminated-and-the-impact-of-terminating-a-b6236689fd2e
질문 # 76
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Itcertkr의 인지도는 고객님께서 상상하는것보다 훨씬 높습니다.많은 분들이Itcertkr의 덤프공부가이드로 IT자격증 취득의 꿈을 이루었습니다. Itcertkr에서 출시한 Microsoft인증 DP-750덤프는 IT인사들이 자격증 취득의 험난한 길에서 없어서는 안될중요한 존재입니다. Itcertkr의 Microsoft인증 DP-750덤프를 한번 믿고 가보세요.시험불합격시 덤프비용은 환불해드리니 밑져봐야 본전 아니겠습니까?
DP-750최신 덤프데모: https://www.itcertkr.com/DP-750_exam.html