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NEW QUESTION: 1
DRAG DROP
You are developing a SQL Server Integration Services (SSIS) package that imports data into a data warehouse.
You are developing the part of the SSIS package that populates the ProjectDates dimension table. The business key of the ProjectDates table is the ProjectName column.
The business user has given you the dimensional attribute behavior for each of the four columns in the ProjectDates table:
ExpectedStartDate - New values should be tracked over time. ActualStartDate - New values should not be accepted. ExpectedEndDate - New values should replace existing values. ActualEndDate - New values should be tracked over time.
You use the SSIS Slowly Changing Dimension Transformation.
You must configure the Change Type value for each source column.
Which Change Type values should you select? (To answer, drag the appropriate value from the list of values to the correct location or locations in the answer area.)
----

Answer:
Explanation:

NEW QUESTION: 2
In the enterprise data center, which are the three main components? (Choose three.)
A. VPN and remote access
B. WAN services
C. Network Infrastructure
D. Interactive services
E. Internet services
F. Data Center Management
Answer: C,D,F

NEW QUESTION: 3
Given:

What is the result?
A. -catch-
-finally-
-dostuff-
B. -finally
-dostuff-
-catch-
C. -finally-
-catch-
D. -catch-
Answer: C

NEW QUESTION: 4
You plan to preprocess text from CSV files. You load the Azure Machine Learning Studio default stop words list.
You need to configure the Preprocess Text module to meet the following requirements:
* Ensure that multiple related words from a single canonical form.
* Remove pipe characters from text.
* Remove words to optimize information retrieval.
Which three options should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Remove stop words
Remove words to optimize information retrieval.
Remove stop words: Select this option if you want to apply a predefined stopword list to the text column. Stop word removal is performed before any other processes.
Box 2: Lemmatization
Ensure that multiple related words from a single canonical form.
Lemmatization converts multiple related words to a single canonical form Box 3: Remove special characters Remove special characters: Use this option to replace any non-alphanumeric special characters with the pipe | character.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/preprocess-text