Artificial Intelligence and Big Data, I bet you will be surprised if I tell you that these concepts are as old as Greek Mythology.
But who on Earth ever thought that these concepts will become crucial today to a country's innovation, competition, and product development?
Similarly, like Artificial Intelligence, Big Data has a very early rise, but it was called differently then. It was the library, the place where a lot of information could be found, growing exponentially with time. In analogy to this, Big Data is a huge online library, where a lot of information can be found disorganized, difficult to be processed or analyzed.
How humanity was operating with it until now?
Initially, Big Data worked on a 'Collect now, Process later' approach. The data will substantially grow and grow, and we would have nothing more than a pool full of inaccessible and unprocessed data from which it would be difficult to get out. Furthermore, the amount of time coupled with the cost of hardware and software was immensely making the process of Big Data analysis very complicated.
Over time, this dark data started making sense and creating value by the usage of different tools like Hadoop or R which helped with processing and analyzing. After this invention, the statisticians had a greater opportunity to work under their hypothesis because of the usage of large amounts of data instead of representative samples.
Until now, the development of Big Data has been a milestone in the history of disruptive technologies, but there have been cases when the collected data could not be accurately analyzed due to the limited capacity of individuals or already invented tools. This was the moment when under the umbrella of Artificial Intelligence, Big Data started intertwining its roots with this technology, offering in this way a more favorable ecosystem for companies striving to get reliable insights.
Big Data created a culture leading the companies operations. To boost the company's market share, focus on acquiring online customers and building relationships with them. To maintain these relationships, integrate the data gathered from the customers and make the necessary analysis to notice what happens to the company in real-time.
Keep in mind that these two broad terms are complementary to each other. Big Data lacked tools to help to organize, preprocess, analyze and turn them into value. On the other hand, AI craved "the raw material", the data. Thus their combination created the perfect technology which enabled solutions to complex problems.
Once the set of the big data has been inferred, preprocessed and ready for analysis, machine learning or deep learning algorithms are used to make predictions. The more the algorithm is trained, the smarter the AI engine becomes. This makes the machine take into control the majority of this process and leave out in this way the human intervention.
Is old Big Data dead forever?
Big Data started as a technology with its issues: the difficulty in preparing and processing the data for future analysis.
Since AI fulfilled this gap by making the whole cycle work, why would you think that Big Data can stand alone?
Not a single reason should make you think that Big Data is as strong as it was in 2007 when it was first issued. Take a deep breath and accept it. Big Data is dead!
For now, Big Data will be remembered as the technology that played an important role in changing the mindset of enterprises by utilizing social media and focusing on the online customer relationship builder.
We are at that point in this technological transformation era that we have enormous and enough amounts of data to be processed. Now is important to find ways of combining this data with AI and extract the most valuable information from it.
Is Big Data AI the next big thing?
The future is promising for the newborn AI Big Data, that is for sure. This development is shaping the future of the firms and the way how they grow the business value. Since this combination focus on the business value, it will continue developing in the future, offering to the businesses a safer environment.
Taking into consideration that the amount of Data is growing every single day, the demand to structure such data will increase. Data scientists will still be needed to develop and train the models of Artificial Intelligence and finally analyze the results. Consequently, the two fields, Big Data, and Artificial Intelligence can’t stand without each other from now on.
Those who will not deploy Big Data AI architectures, for sure will fall behind their competitors and lose customers, market share, brand loyalty, etc. If we have seen so many accomplishments of Big Data Artificial Intelligence until now, imagine what would happen if the current buzzword Deep Learning will be incorporated by all enterprises as the big ones like Google, Amazon, Netflix has done. Businesses will rise to another level, by solving real-life business problems efficiently and effectively.
This combination of technologies can boost business performance from the customer relationships perspective. More sustainable and reliable relationships can be created with the help of Big Data AI predictions and analysis. For this reason, companies’ greatest asset after the human is Data. They should take care of data gathering and mining to continue with the necessary analysis for their business.
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