Bringing your data together

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 Applied 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.

A wide range of content connectors 

Our connectors are available for a growing range of enterprise content repositories, including:


  • File Systems
  • NTFS / CIFS – SMB 1.0, 2.0
  • FTP
  • RSS
  • HDFS


  • RDB by Snapshot
  • RDB by Updates table
  • RDB bulk ingest (all tables & databases)
  • MongoDB
  • HBase
  • Hive
  • Google Big Query

Document / File Management Systems

  • Personal
  • Documentum
  • Dropbox for Business
  • Dropbox Personal
  • FileNet (alpha version available)
  • Google Drive  for Work (in progress)
  • OneDrive
  • SharePoint 2010/2013
  • SharePoint 2016/2019
  • SharePoint Online
  • Veeva Vault (planned)

Social Networks

  • Jive
  • IBM Connections
  • Yammer
  • Twitter
  • Facebook (planned)
  • Instagram (planned)


  • Gmail
  • MS-Exchange (in progress)
  • MS-Exchange On-Line (in progress)
  • MS-Exchange On-Line Personal (in progress)

Service Ticket Tracking

  • ServiceNow
  • JIRA
  • Zendesk (in progress)


  • Kafka Connector
  • Kinesis Connector
  • Azure Event Hub

Web & Wikis

  • Adobe Experience Manager
  • Atlassian Confluence
  • Atlassian Confluence Cloud
  • HTML Web Crawler
  • Selenium JavaScript Web Crawler
  • Mediawiki (alpha version available)

Other / Multiple Categories

  • SAP (planned)
  • Elasticsearch


  • LDAP Cache
  • Group expansion
  • Azure AD Group Expansion
  • JMS Service
  • HTTP Listener

In addition to our 50+ pre-built connectors, we also work with your organization and technology providers to develop custom connectors to support your unique needs.

Connector features

  • Security – Handle complex security environments with nested permission groups and multiple authentication systems by ensuring document-level security through authentication and single-sign-on (SSO).
  • Performance – Provide the flexibility to configure and optimize your search and analytics application’s performance, whether it is speed, content repository compatibility, or other requirements
  • Content enrichment – Provide advanced content processing capabilities, including data cleansing, metadata parsing, entity extraction, and categorization. Whether captured from the original source or automatically derived using text analytics techniques, metadata is a key element in the majority of successful search and analytics applications.

Contact us for further connector details and pricing for your search and analytics applications.