Data is crucial. It’s what helps business runners make right decisions. It’s what they use to prevent fraud, determine clients’ behavioral patterns and make accurate financial forecasts. Companies don’t make the slightest business move now without studying thoroughly their data, and yet, according to the experts in Topological Data Analysis (TDA), there are still ways to exploit it more. For example there is a well known company Ayasdi which utilized the power of machine learning and topological data analysis to solve business needs.
What is Topological Data Analysis?
TDA, which originates from mathematical topology, is a discipline that studies shape. It’s concerned with measuring the shape, by means applying math functions to data, and with representing it in forms of topological networks or combinatorial graphs.
It has proven highly efficient for analyzing large, highly dimensional and feature-rich data as it displays shape-related properties, such as presence or absence of loops within data sets, and thus drastically helps analysts to discern key patterns.
Topological data analysis is of an interest to scientists and entrepreneurs around the world
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Currently, TDA is of an acute interest to both scientists and entrepreneurs around the world. It seems set to change how we, as humans, perceive and understand data. The shape representations it provides either draw summaries out of huge data sets or single out parts of them allowing to interpret data subsets without interfering noise getting in the way.
While displaying data in a succinct way, TDA still retains its important features and relationships between points in data sets. We might say, therefore, that it’s mostly concerned with lossless and clear compression.
In layman’s terms, this is how it works:
Suppose it’s summer and you’re standing at Times Square in New York City on a particularly busy Saturday evening. There are thousands of people around you, all rambling to no end in different languages, yelling over and vigorously interrupting one another. For you, a normal human being with just two ears to grasp sound with, it’s impossible to comprehend everything that’s being said. All you hear is indistinguishable, intense noise.
Now, imagine having a tool (or rather a set of tools) that’s capable of recording all these sounds, of promptly processing them and of getting back to you with quick, informative summaries that retrieve key points from each conversation and indicate where the similarities are between them.
Besides, it gives you an ability to tune into any particular conversation, if you are so inclined, and eliminate all the distracting racket in the surroundings.
Sounds good, huh? Well, that is, in a nutshell, what Topological Data Analysis has been developed for.
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