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NEW QUESTION: 1
To load a specific table using ODI, do you need to draw directly in the flow all details about how the different servers involved are connected?
A. Yes, and also specify with variables the passwords for connecting to the data contained in the servers.
B. No, the code will be black box-generated directly by ODI.
C. No, ODI automatically designs the flow and how servers are connected.
D. In the ODI interface palette, choose the more convenient graphic objects to link the involved servers.
Answer: A
NEW QUESTION: 2
Two-speed IT refers to the rate of change of which aspects of IT?
A. development versus deployment
B. business needs versus IT needs
C. systems of record versus systems of engagement
D. infrastructure as a Service versus Platform as a Service
Answer: B
NEW QUESTION: 3
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft Azure SQL Database instance.
The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology 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.
Answer:
Explanation:
Explanation
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view
