Exam 70-475: Designing and Implementing Big Data Analytics Solutions, exam 70-475 training materials and study guide materials

 

 Exam 70-475

    • Languages:
       English, Japanese, 
    • Audiences:
      IT Professionals
    • Certification
       Microsoft Azure

    • Skills measured

      This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area on the exam. The higher the percentage, the more questions you are likely to see on that content area on the exam. View video tutorials about the variety of question types on Microsoft exams.

      Please note that the questions may test on, but will not be limited to, the topics described in the bulleted text.

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      This preparation guide is subject to change at any time without prior notice and at the sole discretion of Microsoft. Microsoft exams might include adaptive testing technology and simulation items. Microsoft does not identify the format in which exams are presented. Please use this preparation guide to prepare for the exam, regardless of its format. To help you prepare for this exam, Microsoft recommends that you have hands-on experience with the product and that you use the specified training resources. These training resources do not necessarily cover all topics listed in the "Skills measured" section

      Here are some free demo for you to have a reference: 

      NEW QUESTION: 1
      The settings used for slice processing are described in the following table.
      If the slice processing fails, you need to identify the number of retries that will be performed before
      the slice execution status changes to failed.
      How many retries should you identify?
      A. 3
      B. 5
      C. 6
      D. 2
      Answer: B

      NEW QUESTION: 2
      You have a Microsoft Azure Machine Learning Solution that contains several Azure Data
      Factory pipeline jobs.
      You discover that the jobs for a dataset named CustomerSalesData fails.
      You resolve the issue that caused the job to fail.
      You need to rerun the slices for CustomerSalesData.
      What should you do?
      A. Run the Resume-AzureRMDataFactoryPipeline cmdlet and specify the
      -Status Retry parameter.
      B. Run the Resume-AzureRMDataFactoryPipeline cmdlet and specify the
      -Status PendingExecution parameter.
      C. Run the Set-AzureRMDataFactorySliceStatus
      -Status Retry parameter.
      D. Run the Set-AzureRMDataFactorySliceStatus cmdlet and specify the
      -Status PendingExecution parameter.
      Answer: D

      NEW QUESTION: 3
      Your company has two Microsoft Azure SQL databases named db1 and db2.
      You need to move data from a table in db1 to a table in db2 by using a pipeline in Azure Data Factory.
      You create an Azure Data Factory named ADF1.
      Which two types Of objects Should you create In ADF1 to complete the pipeline? Each correct answer
      presents part of the solution.
      NOTE: Each correct selection is worth one point.
      A. a linked service
      B. input and output I datasets
      C. sources and targets
      D. an Azure Service Bus
      E. transformations
      Answer: A,B
      Explanation
      You perform the following steps to create a pipeline that moves data from a source data store to a
      sink data store:
      * Create linked services to link input and output data stores to your data factory.
      * Create datasets to represent input and output data for the copy operation.
      * Create a pipeline with a copy activity that takes a dataset as an input and a dataset as an output.

      NEW QUESTION: 4
      Your company has a data visualization solution that contains a customized Microsoft Azure
      Stream Analytics solution. The solution provides data to a Microsoft Power BI deployment.
      Every 10 seconds, you need to query for instances that have more than three records.
      How should you complete the query? To answer, drag the appropriate values to the correct targets.
      Each value 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
      Box 1: TumblingWindow(second, 10)
      Tumbling Windows define a repeating, non-overlapping window of time.
      Example: Calculate the count of sensor readings per device every 10 seconds SELECT sensorId,
      COUNT(*) AS Count FROM SensorReadings TIMESTAMP BY time GROUP BY sensorId,
      TumblingWindow(second, 10) Box 2: [Count] >= 3 Count(*) returns the number of items in a group.

      NEW QUESTION: 5
      Note: This question is part of a series of questions that present the same scenario. Each
      question in the series contains a unique solution that might meet the states goals. Some question
      sets might have more than one correct solution, while the others might not have a correct solution.
      After you answer a question in this section, you will NOT be able to return to it. As a result, these
      questions will not appear in the review screen.
      You have an Apache Spark system that contains 5 TB of data.
      You need to write queries that analyze the data in the system. The queries must meet the following
      requirements:
      * Use static data typing.
      * Execute queries as quickly as possible.
      * Have access to the latest language features.
      Solution: You write the queries by using Scala.
      A. Yes
      B. No
      Answer: A

      NEW QUESTION: 6
      You are designing a solution that will use Apache HBase on Microsoft Azure HDInsight.
      You need to design the row keys for the database to ensure that client traffic is directed over all of
      the nodes in the cluster.
      What are two possible techniques that you can use? Each correct answer presents a complete
      solution.
      NOTE: Each correct selection is worth one point.
      A. salting
      B. trimming
      C. hashing
      D. padding
      Answer: A,C
      Explanation
      There are two strategies that you can use to avoid hotspotting:
      * Hashing keys
      To spread write and insert activity across the cluster, you can randomize sequentially generated keys
      by hashing the keys, inverting the byte order. Note that these strategies come with trade-offs.
      Hashing keys, for example, makes table scans for key subranges inefficient, since the subrange is
      spread across the cluster.
      * Salting keys
      Instead of hashing the key, you can salt the key by prepending a few bytes of the hash of the key to
      the actual key.
      Note. Salted Apache HBase tables with pre-split is a proven effective HBase solution to provide
      uniform workload distribution across RegionServers and prevent hot spots during bulk writes. In this
      design, a row key is made with a logical key plus salt at the beginning. One way of generating salt is
      by calculating n (number of regions) modulo on the hash code of the logical row key (date, etc).
      Reference:
      https://blog.cloudera.com/blog/2015/06/how-to-scan-salted-apache-hbase-tables-with-region-
      specific-key-ranges
      http://maprdocs.mapr.com/51/MapR-DB/designing_row_keys_for_mapr_db_binary_tables.html

      NEW QUESTION: 7
      Your company has a Microsoft Azure environment that contains an Azure HDInsight Hadoop
      cluster and an Azure SQL data warehouse. The Hadoop cluster contains text files that are formatted
      by using UTF-8 character encoding.
      You need to implement a solution to ingest the data to the SQL data warehouse from the Hadoop
      cluster. The solution must provide optimal read performance for the data after ingestion.
      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.
      Answer:
      Explanation
      SQL Data Warehouse supports loading data from HDInsight via PolyBase. The process is the same as
      loading data from Azure Blob Storage - using PolyBase to connect to HDInsight to load data.
      Use PolyBase and T-SQL
      Summary of loading process:
      Recommendations
      Create statistics on newly loaded data. Azure SQL Data Warehouse does not yet support auto create
      or auto update statistics. In order to get the best performance from your queries, it's important to
      create statistics on all columns of all tables after the first load or any substantial changes occur in the
      data.

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