What is Enterprise Search?

How many workplace applications does your company use? The majority of the apps your company uses are likely to add significant value and increase productivity in some ways; however, they may also be quietly reducing productivity.

With so many apps to navigate, it’s more difficult than ever for employees to access the information they need to perform their jobs. They frequently don’t know what information is stored in which apps, and even when they do, they have trouble locating the precise data they require.

It’s a problem that is silently reducing team efficiency. That’s why an increasing number of businesses are using enterprise search to address this problem. With this software, employees can more easily find the information they need by conducting searches across their internal data, files, and applications, leading to increased efficiency, minimal time wastage, and quick results.

Continue reading to find out more about enterprise search, including its definition, work, and features to look for in an enterprise search platform in 2024.

What is Enterprise Search?

Enterprise search is functionality that locates data and information across repositories in an organization’s unified digital environment. Just like we use search engines like Google and Bing in our daily lives, enterprise search is sophisticated functionality utilized by an organization’s employees to locate desired information, files, or documents.

Data from various sources, including documents, intranets, databases, emails, and the Internet, is searched, indexed, and displayed via a specialized enterprise search tool. Its primary objective is to help businesses locate pertinent data within their data landscape, which will increase worker productivity and save time.

An enterprise search example includes knowledge management. Using enterprise search, employees can easily find the required information regarding anything through the organization’s knowledge management process. The improved search facilitates discovery and avoids the production of unnecessary data.

Besides, enterprise search is growing and evolving into something new. For instance, Gartner created Insight Engine in 2017, a system that helps businesses synthesize information interactively by ingesting, organizing, and analyzing data. Forrester, another analyst firm, defines this new category as Cognitive Engine.

How does Enterprise Search Work?

Enterprise search tools find all relevant data from various organizational sources through a combination of indexing, querying, ranking, and presentation mechanisms. They work just like a search engine; however, instead of the entire Internet, their search is limited to content related to a given enterprise.

The information is gathered from multiple sources. Data that is organized and unstructured are stored in separate “containers.” Let’s understand how enterprise search works:

• Exploration: In the exploration phase, the enterprise search engine software collects data by crawling all available sources, both internal and external, to the company.
• Indexing: Following data recovery, the enterprise search platform tracks relationships within the data to perform analysis and enrichment. The results are then stored to enable precise, rapid information retrieval.
• Search: At the front end, employees ask for information in their home languages. The enterprise search platform then presents the results that it believes are most pertinent to the query, either as individual pieces of content or as a whole. The employee’s work context is taken into consideration in the query response. Depending on their work and search histories, different people might receive different responses.

There are different types of enterprise search. However, they might vary in the querying phase of the search:

1. Siloed: Performs individual search in each repository and returns results by data source.
2. Federated: Performs an individual search that is sent to multiple databases at once, and again, the results are returned by the data source.
3. Unified: Performs singular search into a given index, and after searching across multiple data sources, platforms, and applications, it returns a singular set of results.
4. AI: Utilizes machine learning to a unified index with regards to creating a more relevant list of results.

Key Features of an Enterprise Search

Large organizations typically contain extremely diverse and dispersed information, which is always hosted on a variety of enterprise apps and repositories. These include email systems, file systems, archives, data lakes, websites, intranets, social networks, and both public and private cloud platforms. They also include content management systems (CMS), enterprise resource planning (ERP) solutions, CRM, and relational database management systems (RDBMSs).

Let’s look at the important features of an enterprise search:

1. Connectors

Data connectors are an integral component in an enterprise search engine used for indexing data. They use different protocols to provide a codeless connection to and from different touchpoints, making it easy to sync data from the original source to an index.

2. Data Security

Other important components are data security and privacy. An enterprise search engine should comply with corporate security standards and government regulations. The software should also control user accessibility with accurate permissions.

3. Natural Language Processing (NLP)

Natural language processing (NLP) is a component of artificial intelligence (AI) that examines human-computer interactions through natural language. The ultimate goal is for computers to read, interpret, and comprehend human language in a way that is beneficial to the current process.

4. Artificial Intelligence (AI)

Artificial Intelligence (AI) is used in machine learning to enable systems to learn from experience and improve automatically without explicit programming. Its primary objective is to develop computer programs that can access data and use it for educational purposes.

5. User Experience Design

Product design for user experience (UX) aims to provide end users with relevant and meaningful experiences. It includes designing each step of the process needed to obtain and incorporate the product, covering usability, function, design, and branding.

Why is Enterprise Search Strategic in Big Companies?

Let’s discuss the significance of enterprise search in big businesses’ strategies, covering everything from basic searching to advanced cognitive search and all of its applications.

1. Content without access is worthless.

Enterprise search can help employees find the information they need to do their jobs. They can access both internal company data and external data sources, such as databases, paper, document management systems, and so on.

2. Time is money: How Enterprise Search Increases Productivity?

According to studies, here is the expense of employees spending time searching for knowledge:

• “The knowledge worker searches for information for roughly 2.5 hours a day, or roughly 30% of the workday.” – IDC.
• “The study discovered that in more than a third of searches, employees in the US and the UK spent up to 25 minutes looking for a single document on average.” – LookUpYourCloud.
• “An estimated 28% of the workweek is spent by the average digital worker searching through emails, and nearly 20% is spent looking for internal information or locating coworkers who can assist with particular tasks.” – McKinsey & Company.

Enterprise search reduces the time employees spend locating the information they need, freeing up work schedules for more important tasks. This enhancement is especially crucial given the current focus on maximizing team performance in lean, digital, and agile organizations.

3. Enterprise Search, Insight Engine, or Cognitive Search

The next generation of information-gathering technology, cognitive search, receives, analyzes, and searches digital data content from various sources using AI capabilities like machine learning and natural language processing. Users get results that are more associated with their goals. Cognitive search solutions are necessary to provide the most valuable experiences for both customers and employees.

4. Enterprise Search Can be Applied to Many Use Cases.

Enterprise search engines can be applied to a wide range of use cases with the goal of increasing productivity, including:

• Digital workplace: Using enterprise search as part of a comprehensive digital workplace experience, teams can work together more successfully and be more productive.
• Customer service: It enables customer service agents to locate the information they require to provide top-notch customer service quickly and easily.
• Contact experts: It enables employees to search for experts as well as filter results based on expertise and knowledge.
• Talent search: It is the process of matching job descriptions from a database of possible applicants with candidates.
• Intranet search: Intranet search allows users to find the information they need from shared drives and databases.

What are the Main Criteria for selecting the Enterprise Search Capability?

The following are the main factors to consider while selecting enterprise search capability within a platform or tool.

1. Connectors

How many data connectors will an enterprise search engine need to index all of the data sources? It is best practice to include the sources scheduled for current indexing as well as those expected to be indexed in the future. However, a business might want to leave a data source out of the connection and indexing procedures if it intends to decommission it in the next year or so. This is especially true if a new source is used to migrate the data.

2. Privacy & Security

Ensuring data security and privacy is crucial when conducting an enterprise search. The enterprise search platform configuration must comply with corporate security policies, SOC2, and laws such as GDPR. Steps must be taken to guarantee the confidentiality and integrity of data and protect vital business assets.

Only users with the appropriate permissions can access information and documents due to the following enterprise search engine features and characteristics:

• Adhering to global and sector-specific regulatory requirements
• Utilizing the indexing pipeline’s integrated encryption to shield content from malicious users
• Personalizing the procedure with reference to IP limitations and encryption
• Coordinating with providers of single sign-on (SSO)
• Utilizing multilayer security throughout the cloud, on-premises data centers, intranets, and operations
• Limiting access for individual users and employing security filters for indexed content

3. Intelligent Search or Predictive AI

Enterprise search engines are expected to evolve toward predictive AI. Self-learning algorithms allow enterprise search tools to adapt to user behavior and learn from it, improving innovative results. Furthermore, refined results that get better over time can be supplied by utilizing custom APIs that are made to make search tools function optimally for a particular audience.

How Does Newgen’s Enterprise Search Boost Employee Productivity?

With native process automation, content services, and communication management features, Newgen is the top supplier of a unified digital transformation platform. Our enterprise search capability helps users find information from both structured and unstructured content across a variety of repositories, file systems, workgroup systems, and business systems through a single, unified interface.

To improve visibility and accessibility, our enterprise search unifies your organization’s disparate content repositories under a single user interface. Observe compliance and security requirements concerning the storage of data. The bespoke capabilities of Newgen’s enterprise search engine include:

• Federated Search Across Multiple Repositories
• Intuitive Search Engine
• Search Filters and Terms
• Customizable Search Configuration
• Systematic Organization of Content
• Controlled Document Access and Alerts

Bottom line,

Choosing an excellent enterprise search engine is an important decision for any organization. By comprehending the search engine’s essential features, considering your options, and properly implementing and maintaining them, you can guarantee that your company’s information is easily accessible and that your staff members can locate what they need quickly and effectively.

Spend some time assessing your company’s unique needs and making a well-informed decision to ensure a successful enterprise search engine implementation. The introduction of AI-powered enterprise search tools provides a unified search experience, enhanced with actionable insights as well as advanced analytics.

It represents a significant step toward optimizing an organization’s information retrieval processes. By utilizing their enterprise search capabilities to the maximum, organizations can boost productivity, encourage innovation, and achieve success by adopting these solutions.

Frequently Asked Questions

What is enterprise search in AI?

Artificial Intelligence (AI) technologies like Natural Language Processing (NLP), Semantic Search, and Machine Learning (ML) are utilized in enterprise search in AI to deliver a relevant and engaging search experience. It provides a unified point of access to enterprise content sources, enabling the enrichment, searching, and analysis of both structured and unstructured data.

Why do we need enterprise search?

Enterprise search enables easy access to vital data that can help businesses make wise decisions, enhance user productivity and teamwork, and gain a competitive edge over competitors in their sector.

What is enterprise search in information retrieval?

Large volumes of data are indexed and crawled from various data sources, including file systems, databases, and cloud storage options, to retrieve information in enterprise search. After the data has been indexed, the search engine allows users to perform searches using advanced filters, natural language queries, or keywords.