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NEW QUESTION: 1
Supplier Relationship Managements MOST important intent is to what?
A. Reduce Material Cost
B. Quicker Lead Time
C. Reduce Unnecessary Inventory
D. Higher Quality
Answer: C
Explanation:
Supplier Relationship Managements MOST important intent is to reduce inventory. By
reducing unneeded inventory can have quicker lead times and lower material costs.

NEW QUESTION: 2
You manage a Microsoft Exchange Server 2019 organization that contains several thousand users.
All the users connect to their mailbox by using a mobile device and Exchange ActiveSync.
You need to prevent the users from syncing email messages that are older than 14 days to the mobile devices.
What should you use?
A. a conditional access policy
B. an Outlook Web App mailbox policy
C. an ActiveSync device access rule
D. a mobile device mailbox policy
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/exchange/clients/exchange-activesync/mobile-device-mailbox-policies?view=exchserver-2019

NEW QUESTION: 3
You create a SQL Server 2008 Analysis Services (SSAS) solution. The cube structure is as shown in the following exhibit. (Click the Exhibit button.)

You need to ensure that the Amount measure can be aggregated for the DimCustomer dimension. What should you do?
A. Create a referenced relationship between DimCustomer and FactCustomerAccount. Set DimAccount as an intermediate dimension.
B. Create a many-to-many relationship between DimCustomer and FactCustomerAccount. Set FactTransaction as an intermediate measure group.
C. Create a regular relationship between DimCustomer and FactTransaction.
D. Create a many-to-many relationship between DimCustomer and FactTransaction. Set FactCustomerAccount as an intermediate measure group.
Answer: D

NEW QUESTION: 4

A. Microsoft Azure Table Storage
B. a Microsoft Azure HDInsight Hadoop cluster
C. a Microsoft Azure HDInsight Storm cluster
D. a Microsoft SQL Server database
E. a Microsoft Azure SQL data warehouse
Answer: A,E
Explanation:
A: Azure SQL Data Warehouse is a SQL-based, fully-managed, petabyte-scale cloud data warehouse. It's highly elastic, and it enables you to set up in minutes and scale capacity in seconds. Scale compute and storage independently, which allows you to burst compute for complex analytical workloads, or scale down your warehouse for archival scenarios, and pay based on what you're using instead of being locked into predefined cluster configurations-and get more cost efficiency versus traditional data warehouse solutions.
E: Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores-on-premises or cloud-based-Table storage lets you scale up without having to manually shard your dataset. Perform OData-based queries.