Join Bridgewater State University for a Website Search Webinar on Dec. 10 | REGISTER NOW
Data Analysis with Managed Search

November 12, 2024

Kevin Montgomery

|

3 min. read

Large scale data analysis and research are easier with Managed Search. Managed Search includes the infrastructure, search technology and support to back powerful and insightful data platforms.

Beyond Keyword Search – Searching and Analyzing Large Data Sets

Businesses and organizations can generate large and diverse amounts of data, but those large datasets are only valuable when the underlying trends, variations and issues can be found and extracted into meaningful insights. Companies offering data analysis services and products don’t need to reinvent the wheel when it comes to searching large collections of data, documents and content, they just need a scalable and easy to integrate search service.

Working with Large Datasets

Consistently processing, analyzing and extracting structured data from unstructured sources, such as website content, log files, transcripts and more, can be challenging. Relational databases may not always support the types and quantity of data that are being searched and queried. ETL (extract, transform, load) processes can be inflexible while also being difficult to maintain and update. 

Search platforms, like Solr, can provide a stand-alone large-scale content indexing and search service. Solr includes flexible APIs for indexing content, searching for documents, and customizing filtering, facets, and relevance modeling to provide accurate high quality search results.

Data analysis with Managed Search

Indexing and Updating Data

Keeping source data up to date is imperative to ensure downstream datasets and insights are composited from the freshest and most accurate sources of truth. Maintaining large-scale, high availability data storage is costly and time-consuming. Compliance challenges, additional resources and ongoing maintenance and updates can complicate large data projects, especially when handling those issues internally, as opposed to using a compliant managed service provider.

How to Search, Filter, and Facet Data

Querying and searching large datasets is more powerful and effective when data can be filtered, segmented and faceted by key categories, topics, data types and more. Databases and APIs can be inflexible and difficult to iterate on without migrations, refactors and breaking changes. Open-ended search platforms, such as Solr powered by Managed Search, that include filtering, faceting, relevance modeling and other search customization can be more accommodating to unstructured and varying data.

Building Data Search with Managed Search

SearchStax Managed Search provides stable, scalable and predictable environments to develop, test and deploy large scale reliable search as part of your product. Managed Search includes several critical features for reliably scaling document and data analysis workflows.

API Integration

Managed Search includes the powerful Solr search and indexing API endpoints along with infrastructure orchestration, deployment and management APIs so you can easily integrate with Managed Search with product, deployment and monitoring systems.

Security and Updates

Managed Search includes security features, software updates and technical support to keep your search service running flawlessly without additional management and staffing overhead. Your product team can reliably build and deploy search-powered features and workflows while maintaining compliance and following security best-practices.

Disaster Recovery, Backup and Restore

Managed Search includes data and configuration backup and restore features so your search systems stay up even when disaster strikes. Managed Search can recover from disasters in as little as 10 minutes to minimize data loss and downtime.

Large scale data storage and analysis typically requires large volume storage with fast updating and query processing to ensure that data sets and results contain the most accurate information. Solr supports a variety of different data types and can be extended and customized as needed for the various data types and documents being analyzed.

“Stability, performance and availability have all been top notch even as we’ve seen data grow 100% every month. It’s been great to use SearchStax as they’ve allowed us to focus on the things we really care about - creating great products and finding more customers. To top it all off we’ve gotten 15x the value out of SearchStax versus hiring an engineer to be focused on search and infrastructure.”

Richard Nolan​, President
TrackDrive.net

See how TrackDrive built custom data search with Managed Search.

Getting Started with Managed Search

Schedule a Demo to learn more about Managed Search and how you can build reliable scalable search experiences without the headaches of infrastructure management. Talk to our search experts to learn more about scalable search infrastructure management and how Managed Search can help your team build, deliver and optimize data processing pipelines built with Managed Search.

Start Now for Free

Try Managed Search for 14 days and see how easily you can add robust search to your data processing workflows.

By Kevin Montgomery

Product Marketing Engineer

Managed Search handles the infrastructure management and support so your team can focus on building and delivering.

You might also like: