Microsoft Azure

  • Published:
    27 October 2015
  • Languages:
    English, Chinese (Simplified), Chinese (Traditional), French, German, Japanese, Portuguese (Brazil), Spanish, Russian
  • Audiences:
    IT Professionals
  • Technology:
    Microsoft Azure
  • Credit towards certification:

Designing and Implementing Big Data Analytics Solutions

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Watch an Exam Prep session from Microsoft Ignite 2017

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 in the exam. The higher the percentage, the more questions you are likely to see on that content area in 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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As of February 2017, this exam was updated. To learn more about these changes and how they affect the skills measured, pleasedownload and review the exam 70-475 change document.

Design big data batch processing and interactive solutions (30–35%)
  • Ingest data for batch and interactive processing
    • Ingest from cloud-born or on-premises data, store data in Microsoft Azure Data Lake, store data in Azure BLOB Storage, perform a one-time bulk data transfer, perform routine small writes on a continuous basis
  • Design and provision compute clusters
    • Select compute cluster type, estimate cluster size based on workload
  • Design for data security
    • Protect personally identifiable information (PII) data in Azure, encrypt and mask data, implement role-based security, implement row-based security
  • Design for batch processing
    • Select appropriate language and tool, identify formats, define metadata, configure output
Design big data real-time processing solutions (30–35%)
  • Ingest data for real-time processing
    • Select data ingestion technology, design partitioning scheme, design row key of event tables in HBase
  • Design and provision compute resources
    • Select streaming technology in Azure, select real-time event processing technology, select real-time event storage technology, select streaming units, configure cluster size, select the right technology for business requirements, assign appropriate resources for HBase clusters
  • Design for Lambda architecture
    • Identify application of Lambda architecture, utilise streaming data to draw business insights in real time, utilise streaming data to show trends in data in real time, utilise streaming data and convert into batch data to get historical view, design such that batch data doesn't introduce latency, utilise batch data for deeper data analysis
  • Design for real-time processing
    • Design for latency and throughput, design reference data streams, design business logic, design visualisation output
Operationalise end-to-end cloud analytics solutions (30–35%)
  • Create a data factory
    • Identify data sources, identify and provision data processing infrastructure, utilise Visual Studio to design and deploy pipelines, deploy Data Factory Jobs
  • Orchestrate data processing activities in a data-driven workflow
    • Leverage data-slicing concepts, identify data dependencies and chaining multiple activities, model complex schedules based on data dependencies, provision and run data pipelines
  • Monitor and manage the data factory
    • Identify failures and root causes, create alerts for specified conditions, perform a restatement, start and stop data factory pipelines
  • Move, transform, and analyse data
    • Leverage Pig, Hive, MapReduce for data processing; copy data between on-premises and cloud; copy data between cloud data sources; leverage stored procedures; leverage Machine Learning batch execution for scoring, retraining, and update resource; extend the data factory with custom processing steps; load data into a relational store, visualise using Power BI
  • Design a deployment strategy for an end-to-end solution
    • Leverage PowerShell for deployment, automate deployment programmatically, design deployment strategies for automation

Preparation options

Online training
Practice test

Take a Microsoft Official Practice Test for exam 475

Beginning in April 2017, over time, practice tests will become available in multiple languages, including Spanish, Chinese (Simplified), Chinese (Traditional), French, German, Japanese, Portuguese (Brazil), and Russian. To see when a specific language is offered for this practice test, please check back.

Exam prep video

Preparing for exam 70-475? Watch the online prep sessionhere.

From the community

Who should take this exam?

This certification exam is targeted towards data management professionals, data architects, data scientists and data developers who design big data analytics solutions on Microsoft Azure. Candidates for this exam will have relevant work experience in big data analytics solutions.

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Preparing for an exam

We recommend that you review this exam preparation guide in its entirety and familiarise yourself with the resources on this website before you schedule your exam. See the Microsoft Certification exam overview for information about registration, videos of typical exam question formats and other preparation resources. For information on exam policies and scoring, see the Microsoft Certification exam policies and FAQs.


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 of the topics listed in the "Skills measured" section.