Most organizations have content stored across multiple content repositories built on multiple products and technologies, whether developed in-house or by various vendors. Reliably and securely acquiring content from one or multiple enterprise repositories is complex because every repository has a unique structure and security configuration. As a result, organizations may find it daunting to access their data and provide a unified search and analytics experience.
At the Search & Content Analytics practice of Accenture Artificial Intelligence, we help clients solve this challenge by building and deploying connectors to acquire content from a variety of unstructured and structured data stores, including file systems, document management systems, databases, and web content. The content connectors are part of our technology assets that help clients fill in the gaps in search, analytics, and natural language processing applications. Built on our proven, mature technology framework and backed by expert consulting and implementation services, Accenture’s connectors:
- Are search engine independent to future proof your investment in enterprise search and analytics applications
- Help reduce IT administrative and expense burden
- Are supported by an experienced engineering team that specializes in content processing, connector, and search technologies
- Ensure content processing efficiency, data quality, and security
- Provide flexibility for further modifications to fit your enterprise environment
Accenture’s content connectors can be implemented with a range of popular search engines, such as:
- Google Cloud Search
- Microsoft Search
- Azure Search
- Elasticsearch
- Solr
- SharePoint Search
- Cloudera Search
- Amazon CloudSearch
Our accompanied publishers can publish to HDFS (Hadoop Distributed File System) including commercial distributions from vendors, such as Cloudera, Hortonworks, IBM, MapR, and Pivotal.