Big Data with SAP HANA Vora

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.

This course was retired in October 2023.

Seit 5. Oktober 2016 im Selbststudium
Kurssprache: English

Kursinformationen

Retired

This course was retired in October 2023.

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.

Lernmaterial

  • Course content no longer available

  • 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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Lernende

Aktuell
Heute
19.240
Kursende
5. Oktober 2016
14.323
Kursstart
6. September 2016
11.138

Bewertungen

Der Kurs wurde mit durchschnittlich 4.07 Sternen bei 1145 abgegebenen Stimmen bewertet.

Anforderungen für Leistungsnachweise

  • Den Leistungsnachweis erhält, wer in der Summe aller benoteten Aufgaben mindestens 50% der Höchstpunktzahl erreicht hat.
  • Die Teilnahmebestätigung erhält, wer auf mindestens 50% der Kursunterlagen zugegriffen hat.

Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.

Dieser Kurs wird angeboten von

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.