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How search enables role-based data classification and sharing across the government

Government data strategies lay a promising groundwork for how data will be used to drive more informed decision making internally and more streamlined public services externally. A commonality between these strategies is the need for improved role-based data sharing and data re-use. The sticking point, however, is in the way to implement data sharing when there are known silos across and within various departments.

How to increase website engagement with search

The search experience on your website is often the key driver of visitor satisfaction. Even on well-designed, well-organized websites, visitors frequently resort to search to find the exact products, services, content, and information they need. In fact, many visitors go immediately to the search box. The quality of search results they get back, and the ease with which they can customize and filter those results, can play an outsized role in engagement, conversion, and customer loyalty.

Announcing the Logz.io Search Bar

Engineering teams hoping to gain full-stack observability into their environment need access to the relevant logs, metrics, and traces generated by their cloud infrastructure and applications. Accessing the relevant data quickly is essential – not just because it is more convenient, but because faster engineers are also business-critical for many organizations.

Adding Search to Rails with MeiliSearch

There are many ways to add search functionality to a Rails application. While many Rails developers choose to use the native search functionality built into popular databases like MySQL and Postgres, others need more flexible or feature rich search functionality. ElasticSearch is probably the most well known option available but it has its own issues. Firstly, it is a resource hungry beast. To run ElasticSearch properly in production, you need a few beefy servers.

Elastic Enterprise Search: Next-gen search experiences backed by ML

At ElasticON Global 2021, we shared a future view of Elastic Enterprise Search and how we’re continuing to build next-generation, machine learning-powered search experiences backed by the speed, scale, and relevance of Elasticsearch. We also highlighted the many ways we plan to keep building even more flexibility into our solutions.