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Guidance and results for the data-rich, yet information-poor.

‘Big Data’ Is Dead

Style: "Porcelain pastel"Possibly the most overused and the least understood term since ‘cloud computing’, ‘Big Data’ is dead. It is dead because of it’s complete uselessness in the sense that the phrase itself has lost its meaning. In a constantly maturing industry like Data Mining and Analytics, there can be no clear blanket term to replace ‘Big Data’; What was once a blanket term for a collection of information now lacks specificity and no longer applies universally. Data Mining has evolved in a variety of ways, each of which will be further examined in this post.

Firstly, as analytics become more advanced, some important terms are emerging to reference new, narrowly focused, and highly specialized tools and technologies. As identified by VentureBeat.com, the top items about which you’ll want to be in the know are as follows:

1. Smart Data: As companies needs to more efficiently mine data through solely electronic needs takes precedent in the coming years, one can expect to hear more and more about ‘Smart Data’, data which can be processed without a human mind combing through it by utilizing predictive analytics to anticipate consumer actions. In today’s marketplace, examples such as automated personalizations and recommendations through companies like Amazon, Netflix, and LinkedIn can already be clearly observed.

2. Data Science: A useful term whose popularity has skyrocketed recently, with close to but perhaps not so much overuse as is associated with ‘Big Data’, ‘Data Science’ is meant to refer to a new field which utilizes statistics, machine learning, natural language processing, and computer science to extract meaning from large amounts of data, often with the goal of creating new data products.

3. NewSQL: The scalability of NoSQL combined with the strong ACID guarantees of legacy relational databases offers users new options when dealing with relational data. NoSQL will continue to be valuable for companies who do not require an ACID guarantee, but NewSQL is a solid buzz word of which to be aware and an item whose presence will likely continue to grow.

4. Predictive Analytics: A complicated process which relies on advanced machine learning and statistics to recognize and exploit patterns, predictive analytics is perhaps the root of many of the above mentioned items. Relying on manipulation of historical data to anticipate future actions allows Data Scientists to advise companies and consumers in their best interest. Activities in this arena are applicable in any possible industry and are the driving force behind consumer recommendation services and even fraud detection.

Although the circumstances that gave rise to ‘Big Data’ are still relevant, processes in this arena have progressed, and will continue to progress, beyond the need to store copious amounts of data. New and better systems for processing data will continue to emerge, as will more highly specific terms to describe them.

If you’re interested in learning more about Data Mining’s changing landscape, consider joining The Modeling Agency for a free webinar.  TMA’s training seminars are another, more in-depth way to canvas this growing field and ensure that your company is receiving the maximum benefit from your amassed data.

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