Federated search is a software approach to querying multiple datasets with one request, commonly used for accessing company information. It saves time and is used by search engines like Google. Funnelback is an example of a tool that uses federated search. The main disadvantage is information overload, but there are techniques to sort relevant data. Commercial tools help create federated search functions but require in-depth knowledge of databases and data access techniques.
A federated search is a computer software approach to querying multiple datasets with a single query request. This is commonly used to access company information about specific data or products. A federated query is relatively simple to implement and provides quick access to multiple sets of data in a combined report format.
Federated search is one of the most basic methods of accessing data from multiple databases. This saves time because a search query can be automatically performed on multiple datasets. Most search engines perform a form of federated search on the Internet. These engines can evaluate multiple sources with a single request, making information readily available.
The popular search engine Google® is an example of a federated query that reads unstructured data on the Internet. This federated search engine provides quick results of different datasets. Federated queries use special indexing techniques that allow you to quickly sort and return data.
Funnelback® is an example of a search tool that uses federated search. This tool can read both structured and unstructured data contained in multiple databases. This search tool is similar to a standard indexing search engine that reads data based on specific search criteria and returns it in one sorted view.
One of the main disadvantages of a federated search is the information overload returned by this type of query. When a federated query runs against multiple data sources, thousands of records can be returned. This causes too much data to be returned, making it irrelevant.
A federated search system will typically return thousands of records on a single query. This requires a special business algorithm to return the most relevant data at the top of the list. There are several techniques that can be used to sort relevant data. These are typically based on data accuracy, usage, and correlation with other relevant information within the data.
Many commercial tools help companies create federated search functions. These tools typically include connectors and special software interfaces that allow different data sets to be connected. Integrating these federated search tools requires in-depth knowledge of databases and data access techniques.
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