SAP HANA 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 lets you combine Big Data with corporate data in a way that is both simple and fast. **Please note**: This course is replaced by the updated [Big Data with SAP Vora - Engines and Tools][1]. [1]: https://open.sap.com/courses/hsvo2
Mode autodidacte
Langue: English

Informations sur le cours

SAP HANA 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 lets you combine Big Data with corporate data in a way that is both simple and fast.

SAP HANA Vora allows you to process enterprise and Hadoop data cost-effectively for real-time business applications and analytics by providing enterprise-class, drilldown insight into raw data. 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 is the third course in our SAP HANA Core Knowledge Series, which will give you an insight into some of the core features of SAP HANA.

Course Characteristics

Course Content

Week 1: Overview: SAP HANA Vora

Week 2: SAP HANA Vora Data Modeling Tool

Week 3: Development in SAP HANA Vora

Week 4: 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 HANA 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.

Contenu du cours

  • Week 1:

    Overview: SAP HANA Vora
  • Week 2:

    SAP HANA Vora Data Modeling Tool
  • Week 3:

    Development in SAP HANA Vora
  • I like, I Wish:

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

    Good Luck!

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Ce cours a eu lieu du 6 sept. 2016 au 5 oct. 2016.

11138 apprenants étaient inscrits le jour 1 du cours.

Lorsque l'examen final était terminé, ce nombre avait augmenté à 14323.

19163 apprenants sont actuellement inscrits.

Rating

This course was rated with 4.07 stars in average from 1145 votes.

Certificate Requirements

  • Obtenez un certificat de réussite en gagnant plus de 50% du nombre maximal de points pour la somme de toutes les tâches hebdomadaires.
  • Obtenez une attestation de participation en complétant au moins 50% du matériel du cours.

En savoir plus lisez les lignes directrices pour le certificat.

Ce cours est offert par

Puntis Palazzolo

Puntis Palazzolo is a Sr. Data Scientist at SAP where she manages the SAP Big Data solution, SAP Data Hub, Developer-focused and Advanced Analytics topics in her role in SAP Data Hub/SAP Data Intelligence Product Management team. She has more than a decade of experience in software design and development, machine learning systems and database technologies in different industries such as Bioinformatics, Military and Health Care and applications such as Handwriting and Voice Recognition, Image Processing, Natural Language Processing and Recommendation Engines.

Puntis has several research publications in the field of Machine Learning and Data Science and has patented ideas in the field of Recommendation Engines.

Her academic background is in Computer and Electrical Engineering, Computer Science and Software Engineering.

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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