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How to Prepare and Organize Data and Content for Better Search Through Search Technology

July 23, 2019
How to Prepare and Organize Data and Content for Better Search Through Search Technology

A little organization can make a world of difference for your organization when your users need to access important information. A lack of structure can make it more difficult for your search solution to pull relevant results. For people within your company, bad data organization can result in wasted time and the creation of duplicate files. For external users, it can lead to people leaving your site to find what they need elsewhere.

Finding and accessing your own information shouldn’t be a problem. That’s why it’s important to create some structure for your data and content so that all the information you need is in its right place.

Better Data Organization for Search Solutions

If you have access to structured data, that’s a great place to start. Structured data can make it easy for your organization to find the information you need if you know the correct attributes. While search engine software can crawl unstructured data, the addition of structured data can improve the relevance and precision of results.

An electronic database allows you to create collections of information that are organized and stored for use. The use of a database allows specific users to sort and tag files, text, and other information in a way that improves organization and information retrieval.

One way to prepare and organize your data is to invest in a database management systems (DBMS) based on a relational data model. This setup allows specific users to access and manage relations relation, which are two-dimensional tables that store data about objects, events, and other entities. Relational columns can be organized into certain characteristics, while rows stand for certain files, records, or other data items.

Users with access can then add, update, find, sort, or retrieve data as needed, adding features to the records along the way to improve the relevance of search results or organize files so that they’re only available to certain people. For example, an ecommerce site that sells clothing can organize different items by identifying product characteristics like product color, brand, type of clothing, and other characteristics. These criteria help filter out results that would have appeared from unstructured text. As a result, a user searching for a new pair of shorts won’t be as likely to see results for short sleeve shirts simply because they both use the word “short.”

Structured data also allows you to organize data so that only the right people see certain information. Data items can be tagged with user access so that they don’t end up in results pages for outside users and other people without proper clearance. The right search software can extract structured data from text to enhance the search. Also, the right software can be taught to identify if a file contains specific patterns, for example a credit card number, to constrain the results. As a result, you can set the software to flag those pages to make them more secure. Thanks to this type of advanced logic, it can help you keep your data organized even if a user isn’t there to manually sort something entered into the system.

Invest in Search Engine Software and Appliances That Keep Your Data Organized

Organized data seems like a no brainer, but it does require the right technology to succeed. Text searching and relational database management each rely upon radically different paradigms for organizing and retrieving information, so you need a solution that marries both together.

Thunderstone search engine software and search appliances give you benefits of a SQL relational database (RDBMS) that intelligently queries and manages databases. With our core technology, we can solve even the most complex information retrieval challenges.

Ready to take control of your organization’s information? Request a demo today to test out Thunderstone’s enterprise search solutions for yourself or contact us to talk to one of our experts about we can help you organize your data.

Why Does a Relational Database Matter for Search Engine Software?

May 13, 2019
Why Does a Relational Database Matter for Search Engine Software?

Relational databases and search engines don’t “marry” easily, which can lead some people to think to two can’t work in tandem. However, that doesn’t mean that relational databases don’t matter for search engines. While difficult, there are ways that can allow you to take advantage of relational databases through your search engine solution.

Why is a Relational Database Beneficial for Search Engine Software?

Most recent DBMSs are based on the relational data model, which is great for handling complicated queries and database operations. The fundamental organizational structure for data in the relational model involves something called a relation, which is a two-dimensional table made up of rows and columns that stores data about entities. These entities are objects or events. For example, a healthcare organization could list patients, doctors, insurance carriers, and services as entities that require data collection.

Relational columns represent specific data characteristics, such as specific attributes or data items patient names, home addresses, and other details. The rows signify records or occurrences. In our medical example, these could be services or actions completed by doctor, patients, and other similar data items. Every record in a given table is unique, which allows relational search to pinpoint these exact rows and make it easier for people to access their information.

Thanks to these qualities, relational databases offer many advantages that can improve the overall quality of search results. They help enable better sorting and filtering options, such as being able to search for results based on product color, manufacturer, or other specific details. It also allows the search to see past basic text when pulling these results. For example, a normal search for red shoes may lead Red Wing boots to appear simply because of the name. With a relational database, the color and manufacturer are separate attributes, which allows for more accurate results based on intent on not basic text.

How Relational Databases Can Benefit Search Engine Software

In a basic sense, databases serve as electronic rolodexes while search engines act as the index of a book. In other words, a good database houses all your information while a search engine can access information within that database. The challenge here is that relational search needs to properly and thoroughly crawl a wide variety of data sources, understand the relationships between them, and provide accurate, relevant results.

Another challenge is that databases can store and retrieve a lot of structured data, but search engines typically query unstructured text. As a result, it’s difficult to properly design a relational database for search, but it’s immensely valuable when done right.

That’s where Thunderstone can help. Our Texis search software is a database management system (DBMS) which follows the relational database model and addresses any inclusion of narrative full text. Because Texis is based on the versatility of open standard SQL, it can address complicated search requirements. It also serves as an "intelligent agent," allowing users to quickly and easily access complicated information, allowing you to take full advantage of complicated relational databases without it harming your ability to search within your organization.

Complicated isn’t a bad thing when you have the right solution. Request a demo today to test out Thunderstone’s enterprise search solutions for yourself or contact us to talk to a Thunderstone expert about how we can help you harness the benefits of relational search for your organization.

What is the Difference Between a Database and a Search Engine?

February 12, 2019
What is the Difference Between a Database and a Search Engine?

The lines between a database and a search engine aren’t always clear. For the average user, this may not be something they ever consider, but some clarity is beneficial for any business trying to solve any search challenges. Here’s a quick rundown on the differences between a database and a search engine.

What is a Database?

In short, a database is a collection of information that is organized and stored to be accessed for later use. As an example, a manual version of a database would be like a rolodex with specific fields of information. In this scenario, information is recorded on sheets of paper, possibly organized in folders, and stored in a single place where people with access can go and retrieve that information when necessary.

An electronic database operates largely the same way, except all this data is structured to ease of organization and information retrieval. This database is accessed and managed by specific users through a database management system (DBMS). Users with access can then add, update, find, sort, or retrieve data as needed.

What is a Search Engine?

If a database is like a rolodex, then search engines are more like the index of a book—except that it’s a collection of every index for every book you have. Databases and search engines are both capable of search for data and handling queries. Each technology relies on different paradigms to organize and retrieve information. While databases can store and retrieve a vast amount of structured data, search engines can search unstructured text.

Search engines vary greatly in scope. If you ask the average person about search engines, he or she will think of Google and Bing as examples. However, search engines also apply smaller-scale full-text search software, such as those for online publishing, interactive catalogs, classified advertising, digital asset management, intelligence and web searching.

Search engine software makes the process of retrieving relevant information much easier by allowing users to search for information with natural language text. The results will then be organized by relevance, which can include text documents, geographic information, images, video, audio, and other payload data.

Why Not Have Both?

While databases and search engines don’t “marry” easily, there is technology available that offers a true marriage of the two. Thunderstone’s search engine software and search appliances give users the benefits of both thanks to Texis, the core technology for all Thunderstone products.

Texis is the first search engine software available with the fully-integrated structure of an SQL relational database (RDBMS) that intelligently queries and manages databases. This is due to Thunderstone’s Metamorph, a concept-based natural language search engine that uses advanced lexical set logic to intelligently understand search queries and retrieve relevant responses.

Whether your business needs a solution for complex information retrieval challenges or a hosted search appliance, Thunderstone can help. Request a demo for one on Thunderstone’s search engine software today or contact us to talk to a Thunderstone expert about how Texis technology can be a solution for your search challenges.