AUGMENTED CURIOSITY

Before the term "Big Data" existed, Dr. Jerzy (George) Lewak (theoretical physicist and co-founder of SpeedTrack), envisioned the coming data explosion and associated problems with finding information. He knew it was impractical to solve this problem using solutions based on relational database technology, invented in the 1970s, and concluded that the problem required a completely new, "blank sheet" design that would efficiently scale to accommodate the exponential growth in the volume and variety of data.



Our Technology


SpeedTrack Offers Game Changing Technology

Forget everything you know about storing, accessing and using information! Starting from scratch, SpeedTrack invented technology that is independent of how data is stored, does not require a relational database and provides a completely new experience in terms of accessing and wielding information. We call this Technology For Information Engineering or TIE and the client user interface Guided Information Access (GIA).

The critical foundation methods of GIA are currently used on many web sites and commonly called faceted metadata search or faceted navigation were invented by Dr. Jerzy Lewak, SpeedTrack’s cofounder and Chief Technology Officer. The inspiration for this invention was born in 1991 from Jerzy’s frustration with the available solutions for retrieving information.

In order to understand the value of how the GIA Platform solves the information dilemma, we must first understand the difference between data and information. Data is a string of characters that describe something: an address, a product name, a price etc. Data becomes information when it answers a question, or facilitates a decision. Information is in the association of a descriptive term, and the item they refer to, such as an address of a resident, a name of a product, a price of a product. So information is synonymous with answers.

The focus of conventional IT applications is on storing data in fixed structures (databases, cubes, mainframes, etc.). This approach requires you to either:

1. Search or query the data to determine if an answer exists (the equivalent to shooting arrows in the dark, hoping to hit something), or

2. Rely on pre-defined indexes of data – designed assuming what information will be desired in the future.

As a result, you can spend time searching for information that may not be there, or sometimes the system returns massive result sets of thousands (or millions) of records, with no guidance on what went wrong or how to refine the query. And it is difficult to include new data sources that were not contemplated in the original design.

Rather than requiring you to make a guess at what information is available, or to rely on predefined indexes, GIA presents you with a list of every unique word or value from every field contained in your data. As you make selections from these words and values, the lists narrow or expand to reveal only words and values that are associated with your selections. This occurs n-dimensionally across every field. You are essentially "navigating" your information, continuously making new discoveries and expanding your knowledge.

GIA stores all of the associations that exist between the words and what they describe. By capturing the associations, GIA stores information (as opposed to just storing data). Using this approach, GIA essentially stores every possible answer contained in your data, and presents them in a dynamic interface.

Storing the associations, that is the information, is the foundation for the following several key advantages over other systems:

1. Ensures contextual relevance with every search/analysis. The system “knows” every possible answer contained in the data.
2. All of the information is displayed for you to view in a single interface, this allows you to view and understand the breadth and range of answers that the data contains.
3. Allows you to navigate information by simply selecting from the unique words, characters and values contained in the data, (turns the average lay user into a powerful data miner).
4. Removes non-relevant information from view as selections are made, guiding you to what is meaningful to you, in context. You navigate the information, learning about relationships that may never have been apparent otherwise. This eliminates any guessing while performing search or analysis, no other system we know of does this or has a display capability to do this for an n-dimensional search.
5. Information can be stored in a universal matrix structure, independent of the structure of the data.
6. Because the focus is on the information contained as opposed to the structure of the data, GIA provides the flexibility to handle both structured data (contained in databases) and unstructured data (contained in documents, emails etc.) in exactly the same fashion.

Experience Information
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