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NEW QUESTION: 1
What versions of NetFlow export the TCP flags?
A. v7 & v8
B. v1
C. All of the above
D. None of the above
E. v5 & v9
Answer: E
NEW QUESTION: 2
Which HP Insight Online server management solution feature helps an SMB customer's staff save time and resources when deploying, managing, and supporting their systems?
A. easy, all-in-one access, secure, personalized dashboard
B. unified, extensible firmware interface
C. automated configurations to scale server deployment
D. event lifecycle management
Answer: A
NEW QUESTION: 3
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
Implement table partitioning to improve the manageability of the data warehouse and to avoid the need
to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
Partition the Fact.Order table and retain a total of seven years of data.
Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition
structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date
tables.
Incrementally load all tables in the database and ensure that all incremental changes are processed.
Maximize the performance during the data loading process for the Fact.Order partition.
Ensure that historical data remains online and available for querying.
Reduce ongoing storage costs while maintaining query performance for current data.
You are not permitted to make changes to the client applications.
You need to configure the Fact.Order table.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
Answer:
Explanation:
Explanation/Reference:
Explanation:
From scenario: Partition the Fact.Order table and retain a total of seven years of data. Maximize the performance during the data loading process for the Fact.Order partition.
Step 1: Create a partition function.
Using CREATE PARTITION FUNCTION is the first step in creating a partitioned table or index.
Step 2: Create a partition scheme based on the partition function.
To migrate SQL Server partition definitions to SQL Data Warehouse simply:
Eliminate the SQL Server partition scheme.
Add the partition function definition to your CREATE TABLE.
Step 3: Execute an ALTER TABLE command to specify the partition function.
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables- partition
NEW QUESTION: 4
Sie verwenden eine Microsoft Azure SQL-Datenbank als Data Warehouse. Die Datenbank befindet sich in der Standard-Serviceebene und verfügt über 400 elastische Datenbank-Durchsatz-Einheiten (eDTUs).
Sie laden Daten mithilfe von Azure Data Factory in die Datenbank.
Sie müssen die Zeit reduzieren, die zum Laden der Daten erforderlich ist.
Lösung: Sie verschieben die Datenbank in einen Standarddatenbankpool mit 800 eDTUs.
Entspricht die Lösung dem Ziel?
A. Nein
B. Ja
Answer: B
Explanation:
Explanation
We need at least 400 eDTUs and the use of a Standard database pool.
References: https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dtu-resource-limits