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April 16, 2019

Using Artificial Intelligence to Improve Data Analytics

Using Artificial Intelligence to Improve Data Analytics

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Artificial Intelligence is defined differently throughout industries, even though the foundation is essentially the same, the focus of AI shifts depending on the organization that provides the definition. The most widely accepted definition is by the English Oxford Living Dictionary that defines AI as, “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision making, and translation between languages.”

The term was first coined by John McCarthy in 1956, at the Dartmouth Summer Research Project on AI, the term has since evolved to fit many different interpretations that adapt to each field. AI has grown exponentially, and it is now being used by several industry leaders including Apple, Gmail, Tesla, Amazon, Netflix, Spotify, and more. These companies have millions of users and take advantage of the tools AI provides to predict user behavior and enhance their overall experience. More specifically, they use machine learning, a subset from AI, to process and organize the large amounts of data proactively and efficiently.

The global market for data analytics’ compound annual rate (CAGR) is expected to grow approximately 30% between 2017-2023, exceeding the valuation of $77.64 billion. This is not only because of the large increase in data, but because of the increasing ability to use machine learning techniques to analyze the data proactively. Before AI, data was not being exploited to its full potential because it comes in great quantities that are overwhelming and confusing for people. Machine learning, on the other hand, has the ability to track, collect, organize, and unify first-party data to make real time decisions.

A study reveals that before AI, manual data cleansing before analysis took 80% of the average analysts time - which is time that could have been used to analyze data in other ways, which is a part of the process that machine learning does. Text analytics, an advent of machine learning, can explore large numbers of interrelated features, bring clarity to documents and data.

Artificial Intelligence can help every company in the field be proactive by analyzing data efficiently. Companies are often faced with the dilemma of either partnering with an organization whose focus is the analysis or bringing in additional employees. The option of linking your data with companies that specialize themselves on analyzing big data through machine learning can bring a lot of benefits because the tools come with experience that is key to the whole process.

Let’s start an EPIC journey.