*This is an updated version of the openSAP course “Big Data with SAP HANA Vora”. It will provide updated and new content.* SAP Vora is an in-memory query engine that plugs into the Apache Spark execution framework to provide enriched interactive analytics on data stored in Hadoop. It allows you to combine Big Data with corporate data in a way that is both simple and fast.
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言語: English

コース情報


This is an updated version of the openSAP course “Big Data with SAP HANA Vora”. It will provide updated and new content.

SAP Vora is an in-memory, distributed, query-processing engine, designed as a Big Data solution, which extends the Apache Spark framework to provide enriched interactive analytics on data stored in Hadoop. It lets you combine Big Data with corporate data in a way that is both simple and fast.

SAP Vora provides enterprise-class drilldown insight into raw data, which allows you to inexpensively process enterprise and Hadoop data for real-time business applications and analytics. It also allows you to blend incoming data from customers, partners, and smart devices into enterprise processes by combining business data with external data sources to make better decisions through greater context.

This course dives deeper into the SAP Vora tools and new distributed analysis engines released in SAP Vora 1.4 for performing relational queries, time series, graph, document database analysis, and disk store.

Course Characteristics

Course Content

Week 1: Overview: SAP Vora
Week 2: Data Analysis Engines/Functionalities
Week 3: Data Analysis with SAP Vora Tools
Week 4: SAP Vora Deployment
Week 5: Final Exam

Target Audience

  • Data scientists
  • Application developers
  • Technical business analysts

Course Requirements

Knowledge of Hadoop and Apache Spark

Training Systems

If your primary interest in taking this course is to get an overview of SAP Vora, you do not need access to a training system. However, we realize that many of you will be interested in completing the hands-on exercises based on the instructions in the course. We will therefore provide the necessary instructions and installation procedures in the respective units.

Further Content Expert

Puntis Jifroodian

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Puntis Jifroodian is a senior data scientist in the SAP Big Data Product Management team, focusing on SAP Vora and “developer-focused” topics.

Puntis has a decade of experience in software design and development, machine-learning-based systems, and database technologies in various industries such as bioinformatics, defense, healthcare, handwriting and voice recognition, image processing, and natural language processing. Puntis has several research publications in the field of data science and has patented ideas in the field of recommendation engines.

コースの内容


  • Week 1:

    Overview: SAP Vora
  • Week 2:

    Data Analysis Engines/Functionalities
  • Week 3:

    Data Analysis with SAP Vora Tools
  • Week 4:

    SAP Vora Deployment
  • I Like, I Wish:

    We Love Your Feedback … And Want More
  • Final Exam:

    Good Luck!

Reactivate this course


You can access all graded assignments and earn a Record of Achievement with openSAP, course reactivation option. Learn more or reactivate now!

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今すぐ登録する

このコースは 9月 06, 2017 から 10月 12, 2017 まで開催されていました。

13401 人の学習者が登録しました。

Rating


This course was rated with 4.32 stars in average from 597 votes.

コース提供者


Jason Hinsperger

Jason Hinsperger is a senior product manager in the SAP Big Data Product Management team, focusing on SAP Vora.

With over 20 years of experience in the enterprise and OEM database and data management space, Jason has been involved in developing enterprise RDBMS software and architecting data-driven applications across many industries in partnership with OEMs, both on premise and in the cloud.

Balaji Krishna

Balaji Krishna is a senior director in the SAP HANA Vora Product Management team and owns overall responsibility for SAP HANA Vora and Hadoop integration topics with SAP HANA.

With over 20 years of experience working in enterprise software development, Balaji has been involved in various topics such as analytics, data warehousing, and Hadoop/Big Data in Support, Consulting, and Product Management teams.

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