Learn about Full Text Search with SAP HANA Platform in this free openSAP online course. With a large amount of data collected by companies, SAP HANA provides fast and convenient search-based access to unstructured data. With this course, you’ll learn about full-text indexing and search via SQL, fuzzy search, search rules for duplicate checks and much more. If you’re using SAP Business Suite or SAP S/4HANA, you’ll also learn about SAP HANA enterprise search.

Self-paced since October 12, 2017
Language: English

Course information

Course Summary

Today, enterprises and organizations collect and analyze huge volumes of data about everything from incident messages and service reports to research documents and patent files. With SAP HANA, you can provide fast and convenient search-based access to unstructured data. SAP’s in-memory data management platform not only provides the technology for building analytical applications, but also natural language processing (NLP) components. Learn how to leverage SAP HANA’s capabilities for full-text search and application development.

This course starts with the basics on full-text indexing and search via SQL. In unit 2 we focus especially on fuzzy search and how to use “search rules” for duplicate checks and matching. Next, we’ll present the tooling to create search models, the interface to query such models, and how to use the native search UI. We’ll then explain “SAP HANA enterprise search” in the context of SAP Business Suite and SAP S/4HANA, and how it relates to and extends “native” SAP HANA search technology. Finally, we’ll talk about some adjacent technologies like SAP file processing and SAP HANA graph. Demos and hands-on exercises are provided throughout.

Please note, that the full-text search and capabilities of SAP HANA on-premise and SAP HANA Cloud slightly differ. The course content explains the features of SAP HANA on-premise.

Course Characteristics

  • Starting from: September 13, 2017, 09:00 UTC. (What does this mean?)
  • Duration: The course is open for 4 weeks
  • Effort: 4-5 hours in total
  • Course assignment: You can take the course assignment at any time whilst the course is open.
  • Course closure: October 12, 2017, 09:00 UTC
  • Course language: English
  • How is an openSAP course structured?

Course Content

  • Unit 1: The Basics: Full-Text Indexing and the Contains Predicate
  • Unit 2: Matching: Fuzzy Search and Search Rules
  • Unit 3: Search Models: Using Core Data Services and ESH_CONFIG
  • Unit 4: API and Query Language: Using ESH_SEARCH
  • Unit 5: User Interface: The SAPUI5 Search UI
  • Unit 6: SAP Business Suite and SAP S/4HANA: SAP HANA Enterprise Search
  • Unit 7: Beyond Search: SAP HANA File Processing and SAP HANA Graph

Target Audience

  • Data scientists
  • Application developers
  • Technical business analysts

Course Requirements

  • Basic database knowledge
  • Basic understanding of full-text indexing and search applications is helpful

Training Systems

If your primary interest in taking this course is getting an overview of SAP HANA search capabilities, 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’ll therefore provide the necessary instructions and installation procedures in the respective units.

Course contents

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Learners

Current
Today
10,811
Course End
Oct 12, 2017
7,084
Course Start
Sep 13, 2017
5,862

Rating

This course was rated with 4.5 stars in average from 403 votes.

Certificate Requirements

  • Gain a Record of Achievement by earning at least 50% of the maximum number of points from all graded assignments.
  • Gain a Confirmation of Participation by completing at least 50% of the course material.

Find out more in the certificate guidelines.

This course is offered by

Markus Fath

Markus Fath spent some years in SAP HANA Product Management before joining the SAP HANA Development organization. He now works as a development architect, focusing on SAP HANA Multi-Model – Spatial, Graph, and the JSON Document Store.