The Microsoft 70-775 exam is focused on Big Data for Azure HDInsight. With the help of external resources about this exam and recommended books, links, and courses, you can prepare for the 70-775 exam. The Big Data Analytics Certification is the top-ranked certification internationally for today’s market analysts, business scholars, and marketers aspiring to enter or boost their career growth in this highly lucrative Big Data Analytics profession. Big Data Analytics training becomes essential for candidates in order to understand and successfully pass the Microsoft exam.
Who can take this exam?
Candidates who can appear for this exam:
– Data Scientist
– Data Architects
– Data Analysts
– Data Developers
– Other professionals who want to gain knowledge or want to be certified in the Big Data analytics profession on Azure HDInsight more specifically.
What is HDInsight?
Windows Azure HDInsight Service is a service that utilizes and provides Apache Hadoop clusters in the Azure cloud, distributing a suitable software framework designed to monitor, control, analyze and report on big data. It builds the HDFS/MapReduce software framework and related projects such as Pig, Sqoop, and Hive available in an easier, more scalable, and budget-friendly environment.
Windows Azure HDInsight Service makes use of Azure Blob Storage as the basic file storage system. You can also store it in the native Hadoop Distributed File System (HDFS) file system that defaults to the computer nodes, but your data can be lost if you deleted your cluster. Due to a thin layer over Azure Blob Storage, it gets demonstrated as an HDFS file system called Windows Azure Storage-Blob or WASB.
Microsoft HDInsight Server for Windows was stopped after it was released but lives on in two platforms: Hortonworks Data Platform (HDP) and Microsoft’s Parallel Data Warehouse (PDW). Both of these platforms provide fundamental solutions.
With HDP, it includes core Hadoop (meaning the HDFS and MapReduce), in addition with Pig for MapReduce programming, Hive data query, Hortonworks’ recently introduced HCatalog table management service for gaining control over Hadoop data, Scoop for data movement, and the Ambari controlling and management console. All of the above have been restructured to work on Windows, and all are open-source components that are suitable with Apache Hadoop and are being provided back to the community. With Parallel Data Warehouse (PDW), you may include an HDInsight region into the appliance, and this region consists of Hortonworks Data Platform (HDP), which can be accessed through Polybase.
Microsoft HDInsight Server is constructed to work with Windows Server and Microsoft SQL Server. In the case of Windows, HDInsight is combined with Microsoft System Center for administrative control and Active Directory for gaining control over security.
Microsoft Certifications related to this exam
This exam is essential for professionals who want to earn the MCSE (Microsoft Certified Solutions Expert) in Data Management and Analytics. Individuals wanting to earn MCP (Microsoft Certified Professional) can also start with this exam.
Is this exam difficult?
Individuals with no experience or have a little experience with Big Data, Azure, and PowerShell will find it hard to pass the exam. If you have already gained your work experience with HDInsight and the technologies related to the exam, it might become easy.
For gaining experience, you can first go for Big Data Analytics Certification with the help of Big Data Analytics Training.
Books recommended for this exam.
The following books may be recommended to help you pass this exam:
– Big Data Analytics with Microsoft HDInsight
– HDInsight Essentials – Second Edition
– Building Real-World Big Data Systems on Azure HDInsight
– Microsoft Big Data Solutions
– HDInsight: Microsoft’s Cloud Hadoop
– Architecting in the Cloud with Azure Data Lake
– Pro Microsoft HDInsight: Hadoop on Windows
– Learning Spark: Lightning-Fast Big Data Analysis
– Advanced Analytics with Spark
– Best Practices for Scaling and Optimizing Apache Spark
– Storm Applied: Strategies for real-time event processing
– Big Data: Principles and best practices of scalable realtime data systems
– Getting Started with Storm: Continuous Streaming Computation
– Streaming Architecture: 1st Edition
– Kafka: Real-Time Data and Stream Processing at Scale
– Learning Apache Kafka, Second Edition 2nd Edition
– Apache HBase Primer 1st Edition
– HBase in Action 1st Edition