IBM BigInsights Text Analytics (V4) – SPVC – 2W654G SPVC

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Details


Course Code: 2W654G

Brand: HDM – BIGSQL

Category: Analytics

Skill Level: Intermediate

Duration: 8.0H

Modality: SPVC

 

 

Audience


The course is designed for data scientists and developers who want to use Text Analytics.

 

Prerequisites


  • Students should be familiar with SQL, Hadoop, and the Linux file system.
  • Have taken DW601 – IBM BigInsights Overview
  • Although not required, it would also be helpful for students to take the DW644 – IBM BigInsights Bigsheets to have a better understanding of how BigSheets can work with Text Analytics. Student can attend many free courses at www.bigdatauniversity.com to acquire the necessary requirements.

 

Short Summary


Learn how to use IBM® BigInsights® Text Analytics to extract information from unstructured and semi-structure documents

 

Overview


Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace.

Learn how to use IBM® BigInsights® Text Analytics, an information extraction system, to extract information from unstructured and semi-structured documents.

Using IBM BigInsights Text Analytics you can create extractors using a visual web interface. The visual extractors are then automatically translated into Annotation Query Language (AQL) rules to extract structured information from unstructured and semi-structured documents. You can apply Text Analytics to big data at rest in IBM BigInsights and big data in motion in IBM Streams.

 

Topic


  • Understand and describe the need for text analytics
  • Understand the Annotation Query Language (AQL)
  • Describe the AQL data model
  • Text Analytics web tooling
  • Navigate a Text Analytics project in the web UI
  • Import documents into a project
  • Understand the Text Analytics development process
  • Use the tooling to create and test extractors

 

Objectives


  • Understand and describe the need for text analytics
  • Understand the Annotation Query Language (AQL)
  • Describe the AQL data model
  • Navigate a Text Analytics project in the web UI
  • Import documents into a project
  • Understand the Text Analytics development process
  • Use the tooling to create and test extractors
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