Elastic expands data management efforts to workplace search
Elastic previewed a new search service that brings enterprise and software-as-a-service data sources together to help users find relevant data, where it resides.
Elastic Inc.'s new Workplace Search service is aimed at enabling enterprise users to find data across an ever-expanding landscape of on-premises and cloud-based applications.
Elastic unveiled Workplace Search at the data search vendor's Elastic{ON} Americas East virtual conference April 23.
Workplace Search is built on top of the company's existing Elastic Stack, which includes the long-standing search function, Logstash log management and Kibana data visualization capabilities. With Workplace Search, organizations can connect to SaaS applications and other cloud data sources, alongside existing in-house data to enable data search queries. Workplace Search is now available as a beta preview.
Enterprises use a scattered set of workplace apps and employees need to search across these applications, using standard search engines from the tech giants or more specialized search technology from vendors like Elastic, Forrester Research analyst Mike Gualtieri said.
"Many workplace apps suites include built-in search such as Microsoft and Google, but the scope of that search is within those apps," Gualtieri said. "Enterprises can use Elastic's workplace search to break down those silos so employees can find answers and information across those silos."
Gualtieri estimated that the market for enterprise search will grow by 300% over the next three years as organizations replace old search technology. In that context, Elastic's timing with Workplace Search is positioned well to ride that wave of adoption, he said.
Elastic Workplace Search interface enables customized queries that span multiple data sources.
It's all about the data
In his opening keynote at the virtual conference, Shay Banon, founder and CEO of Elastic, provided a broad overview of his company's mission and where it's going, with new features such as Workplace Search.
"Everything starts with data," Banon said. "When I created Elasticsearch many, many years ago, the idea was to empower users to have control of their data, versus the other way around."
Part of controlling data is also the ability to search it. Banon noted that for many people the search box is their primary interface to the internet. He added that a search box helps make data sensible and consumable and is a foundational element for how organizations use data.
Workplace search as a conduit to data management
The Elastic Stack already had the ability to crawl, store and search data within an enterprise. What it was missing was an easy way to integrate that search with the growing number of SaaS applications that organizations are using.
Enterprises can use Elastic's workplace search to break down those silos so employees can find answers and information across those silos.
Mike GualtieriAnalyst, Forrester Research
With Workplace Search, Banon said a key goal was to create a consumer-type experience for search across the different data silos that an organization has. Onboarding the SaaS data sets for Workplace Search is set up via a point-and-click dashboard. The Elastic platform handles all the ingestion, rate limiting and security controls to connect and search the various SaaS data sets.
Also during the virtual event, Matt Riley, product lead for elastic search at Elastic, said one of the ways that connections to SaaS data are enabled is with a set of connectors for specific services. Among the initial set of connectors are integrations with GitHub, Google Drive, Dropbox, Salesforce, Microsoft Office 365, Jira and Confluence. Going a step further, Elastic introduced a new custom API connector for Workplace Search, with which an organization can build their own connection to a custom data source.
A key part of the Workplace Search is the ability to set relevance rankings based on the level of use within an organization. For example, sales teams when searching will likely have more interest in seeing data that sources from Salesforce, while an engineering team would see data coming from GitHub as more relevant, Riley noted.
"We're really excited to be releasing something that what we think is a pretty comprehensive solution for addressing all of the needs that employees are going to have, with things like making the searches personalized based on who the actual searcher is," Riley said.
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