Enterprise search is the practice of making content from multiple enterprise sources such as databases and intranets, searchable to a defined audience. "Enterprise search" is also used to describe the software of search information within an enterprise.

Enterprise search systems index data and documents from a variety of sources such as file systems, intranets, content management systems, e-mail, and databases. Many enterprise search systems integrate structured and unstructured data in their collections. Enterprise search systems also use access controls to enforce a security policy on their users.

Electronic discovery or ediscovery refers to discovery in legal proceedings such as litigation or government investigations where the information sought is in electronic format. The ever increasing amount of litigation, greater volumes of data and a move toward adding in-house e-discovery capabilities require strong tools for ediscovery.

Data is scattered throughout companies and has become progressively more difficult to manage. Companies are dealing with big data, data in shared repositories such as Box.com, data on mobile devices, etc.

Many issues affect knowledge management. The five most important are big data, cybersecurity, mobility, social analytics, and customer engagement.

The availability of big data has opened many options for understanding everything from customer preferences to medical outcomes.

Information access and retrieval within most organizations is a work in progress. There might be a general search system for marketing information, and probably one or more database search systems.

The larger the organization, the greater the number of information retrieval systems. Each laptop and mobile device has a search system. Mobile phone apps sport their own search systems. The lawyers in an organization may have different search systems for specific types of legal matters. The enterprise resource planning (ERP) users have a search system. When it comes to enterprise search, there are many silos.

Big Data is everywhere. But to harness its potential, organizations should understand the challenges that come with collecting and analyzing Big Data. The three values that are important in managing big data are volume, velocity, and variety. These three factors serve as guidance for Big Data management, highlighting what businesses should look for in solutions.

But even as organizations have started to get a handle on these three V’s, two other V’s, veracity and value are important as well, if not more so.