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NEW QUESTION: 1
You plan to create the chart shown in the following exhibit.

How should you create the dashed horizontal line denoting the 40th percentile of daily sales for the period shown?
A. Add a new percentile line that uses Total Sales as the measure and 40% as the percentile.
B. Create a horizontal line that has a fixed value of 24,000.
C. Add a measure to the visual that uses the following DAX expression.
Heasurel - PERCENTUEX.EXC (Sales,Sales[Total Sales],6.40)
D. Add a measure to the visual that uses the following DAX expression.
Heasurel = PERCENTILEX.INC (Sales,Sales[Total Sales],6.40)
Answer: A
Explanation:
The analytics feature enables you to show percentiles across groups specified along a specific axis.
Example:
1. Click on the analytics tab
2. Select Percentile
3. You can choose a specific percentile along with other formatting options.
4. Drag a date or non-numeric dimension into the Axis of a column chart


Add percentile lines to monitor daily revenue

NEW QUESTION: 2

A. Option C
B. Option B
C. Option A
D. Option D
Answer: A,C

NEW QUESTION: 3
A company named Fabrikam, Inc. has a Microsoft Azure web app. Billions of users visit the app daily.
The web app logs all user activity by using text files in Azure Blob storage. Each day, approximately 200 GB of text files are created.
Fabrikam uses the log files from an Apache Hadoop cluster on Azure DHlnsight.
You need to recommend a solution to optimize the storage of the log files for later Hive use.
What is the best property to recommend adding to the Hive table definition to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
A. STORED AS RCFILE
B. STORED AS ORC
C. STORED AS TEXTFILE
D. STORED AS GZIP
Answer: B
Explanation:
Explanation: The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data.
Compared with RCFile format, for example, ORC file format has many advantages such as:
*
a single file as the output of each task, which reduces the NameNode's load
*
Hive type support including datetime, decimal, and the complex types (struct, list, map, and union)
*
light-weight indexes stored within the file
*
skip row groups that don't pass predicate filtering
*
seek to a given row
*
block-mode compression based on data type
*
run-length encoding for integer columns
*
dictionary encoding for string columns
*
concurrent reads of the same file using separate RecordReaders
*
ability to split files without scanning for markers
*
bound the amount of memory needed for reading or writing
*
metadata stored using Protocol Buffers, which allows addition and removal of fields