Can Machine Learning Make Big Data More Accessible?


If you are a person enjoying certain familiarity with the terms tech world, you must have come across terms such as Artificial Intelligence, Machine Learning and Big Data. Each of these terms carry an indomitable weight and significance to the world of business and technology.

Every moment the million bytes of digital data produced contribute to the staggering growth of digital data which can be utilised for drawing effective and useful analytical insights to help business processes and add value to different endeavours in life. Grossly, this is termed as Big Data.

The machines and machine intelligence are getting smarter to understand human needs and contexts. Today machines can easily comprehend what we prefer as user, the kind of constraints we have and the kind of reality already there to make certain things happen. Grossly, this ability of machines to learn from human activities and respond accordingly is called machine learning.

Now machines and machine led software programmes and apps produce a multifaceted and huge volume of digital data contributing to the possibilities proclaimed by the Big Data analytics. Question that most Big Data solutions providers should consider is that how far Big Data is playing a positive role to make Big Data more accessible and discernible. Through the rest of this post we are going to enquire about this.

  • What The Data Says?

Across every sphere new technologies are breaking through and creating new ways of traction. While Big Data has become the most crucial technology to make use of overwhelming volume of digital data, Internet of Things after being conceived as a technology pertaining to home appliances has made its foray into industrial environments. Machines are continuously producing data and as the machines are getting smarter and more responsive to learn from human interactions, they are adding more valuable data to the process of analytics and data centric decision making.

A recent study by Dell entitled “Machine Learning Techniques in Manufacturing,” it is cited that typically having a bigger emphasis on data driven decision making are at least growing 50% faster or more than that. So, the improved and enhanced role of intelligent machines in business and industrial environments is paving the way for better and more rapid adoption of Big Data.

  • Artificial Intelligence and Machine Learning

Artificial Intelligence or AI has been there for a few years and there are several successful apps, algorithms, machine logic and systems that are presently held as great example of this applied technology. Machine learning is a close companion of this technology which precisely refers to the enhanced capacity of machines to learn from the human interactions and accordingly respond to user contexts.

For some time it seems machine learning and artificial intelligence are working as an inseparable entity in diverse applications. While machines continuously learning from human beings enriching our experience these learnings are also actively being used to make algorithms and apps more intuitive and user optimised.  On the other hand, intelligent AI based algorithms are continuing to make machines more capable to learn from human interactions. Thus both AI and machine learning are working closely to add value to the digital interactions.

But what artificial intelligence services are most enthusiastic about is the huge scope of producing insightful digital data through these new types of digital interactions powered by intelligent machines and algorithms. The intelligent digital manoeuvres powered by AI and machine learning technologies are also enjoying a mutually empowering relations with one another.

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