Back to top

Enterprise Search and Big Data Webinars

View our on-demand webinars in which our experts discuss and demonstrate search and big data best practices, use cases, and customer success stories. Get our latest webinars, videos, blogs, and other educational content delivered monthly to your inbox, sign up for our free monthly Search & Big Data Newsletter or connect with us:

Facebook   Twitter   LinkedIn   Google Plus

0

Speaker: Bill Fowler, Search Technologies' GSA Architect

View our webinar and demo to learn about how you can replace your GSA risk-free and cost-effectively with the ST Search StackTM - a complete enterprise search solution built around Elastisearch (or Solr).

Speakers: Paul Nelson, Chief Architect, and Alexander Olaru, Managing Architect

View our webinar to learn how enterprise data lakes are very useful for search, discovery, and analytics. You'll see best practices and approaches to extracting insight from data through a live demo using Cloudera Search and Morphlines.

Speakers: Paul Nelson, Chief Architect, and Jonathan Blasenak, Architect

View our on-demand webinar to see how you can implement an open source log analytics stack for log management, customized analytics platforms, and complex queries execution. A live demo of Apache Kafka, Elasticsearch, Logstash, and Kibana is included.

Speaker: Phil Lewis, European Technical Director

Even the top-tiered e-commerce sites sometimes fail to provide a good search experience for online shoppers. The effectiveness of your e-commerce site search can greatly impact your conversion rate. View our webinar to learn how to use a scorecard to methodologically evaluate and improve site search performance.

Speaker: Paul Nelson, Chief Architect

Using big data to collect and analyze event and user logs can provide insights into search accuracy improvements. View our on-demand webinar to learn about the algorithms and processes for computing search engine scoring metrics. These are enormously helpful for evaluating your search engine accuracy before deployment.