The difference between data and results

Let’s say you wanted to find some information about a painting you saw in a museum a few years ago. You remember it was a Renaissance painting of a queen, but not the name or artist. Your first step is probably to use a search engine to search something like “renaissance painting queen.” The results show you images of a few famous paintings, but not the one you remember. Next are links to museums, a fine art blog, and a scholarly article about portraits of women in Renaissance art. Even after adding descriptors to your search, you’ll likely spend time combing through search results to find the painting you remember.

In situations where we are searching for something without complete information, this gap will always exist – the gap between the available data and the result we are looking for. Even the most advanced machine learning and artificial intelligence relies on existing information and data inputs to produce results. But when finding answers carries high stakes like protecting a business from millions in fraud or catching a criminal, it’s imperative that technology makes that gap as narrow as possible.

Computers want data, humans need answers

When you use a search engine, you’ll notice that it displays the total number of results it finds for your search. This number is usually close to 100 million. Search engines know that no one wants that much data. (As the old joke goes: where’s the best place to hide something you don’t want anyone to find? Page two of your search results.) But search engines need to know every possible result to deliver those that are most relevant. Given broad information like “renaissance painting queen”, the search engine employs complex technology to attempt to deliver the best results on page one. To some extent, the search engine attempts to predict what you’re looking for since the pool of potential results is so big.

If your search engine were to deliver an unorganized list of all 100 million results it found for “renaissance painting queen” the likelihood of finding anything relevant on the first page is essentially zero. While more data is helpful for computers, it is often unwieldy and confusing for humans. We do best with a few, highly relevant data points. When searching for a single painting, an exhaustive list of every renaissance painting ever created is useless to a human. But a computer can use that list as a starting point to parse out relevancy through things like popularity or subject. Put simply, access to data is important, but it’s only half the battle.

Searching vs. finding in public records

Much like popular search engines, public records technology uses search inquiries to query millions of records. And as the name suggests, most of the records used are public and identical between providers. The best providers supplement that universal data with proprietary records to widen the gap between them and the competition, and to close the gap between data and results. With supplemental data and advanced search technology, the best public records solutions are better able to help users find what they’re looking for.

Whether you’re looking for information about a person, business or assets, there’s often a lot on the line. Unlike our Renaissance painting example, you can’t afford to spend time combing through data. Some public records providers tout the number of records they have. But users need their tools to deliver the right answers at the right time. Often, you’re searching with incomplete information. And while it’s unlikely that a public records solution will ever be able to deliver the exact result you’re looking for every time you search, the difference between 20 potential results and 5 highly relevant results can have a significant impact on your outcomes.

Closing the gap

For the professionals who rely on public records technology, the gap between data and results must be as small as possible. Whether fighting or preventing crime, managing risk or protecting key government programs, the stakes for your searches are higher than ever. In the age of big data, access to information is half the battle, but only half. Machine learning, AI and sophisticated search technology delivers on the other half with public records solutions that help deliver the answers you need faster than ever before.