While it's very impressive that today's technology allows us to gather incredible amounts of data, the reality is much of the data is currently collected before anyone answers: "What do we want to do with this data?" The result: Your organization has a lot of data that isn't very useful for business.
History and Evolution of Data Analytics: The concept of'Big Data' has been around for decades. Many organizations now understand that, if they capture all the data sets that streams into their businesses, they could apply analytics to get significant insights and value from the data. Even in the 1950s, decades before anyone even uttered the term "Big Data," the businesses were using analytics – especially numbers in an excel sheet which were analyzed manually to gain insights and trends. The companies used this information for future decisions. Whereas, today, the business can identify insights for immediate action as the new benefits which the big data analytics brings are efficiency and speed.
Artificial Intelligence and the Internet of Things are both one of a kind innovations all alone, however, what makes them all the more intriguing is the place they converge. As the applications of IoT and AI are independently interesting, their joined use cases hold even more dazzling potential, as indicated by scientists and industry specialists. The Internet of Things is getting more brilliant. Organizations are fusing artificial intelligence--specifically, machine learning--into their IoT applications. With an influx of investment, a pile of new products, and a rising tide of big business organizations, artificial intelligence is making a splash in the Internet of Things (IoT).
Several factors have fueled the rise of big data. People now store and keep more information than ever before due to widespread digitization of paper records among businesses. The proliferation of sensor-based Internet of Things (IoT) devices has led to a corresponding rise in the number of applications based on artificial intelligence (AI), which is an enabling technology for machine learning. These devices generate their own data without human intervention.
The tsunami of big data created by the Internet of Things (IoT) demands that companies employ intelligent data management techniques to separate the wheat from the chaff, or find the'good data'. Adding to the fact that 90% of the world's data has been created in the last few years alone, it's vital that businesses grasp meaningful insight from data and analytics – but what key areas should be focusses on for best results, and how could this enhance the backbone of your company, the supply chain? With IoT set to exponentially increase the amount of available data as billions of devices activate and connect online, companies will need to turn to machine learning. Daniel Newman, founding partner of Futurum Research and CEO of Broadsuite Media Group, warns it will be simply too much for humans to handle alone. Machine learning can eliminate data junk and "keep data lakes clean and consistent", even when it comes to unstructured historical data, he says.