The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

From working in solitary cubicles to working with artificial bots, automation has come a long way and has changed how the modern generation works. Today, Artificial Intelligence (AI) and Machine Learning (ML) have become regarded as the future of tomorrow’s workforce and culture. At Idexcel, we have been keeping track of these ongoing trends.

It has been said that “with great power comes great responsibility.” If we tweak this statement a bit to reflect more contemporary times, we can also assuredly say that “with great technology, comes heaps of data.” The more we progress on the path of digitization, the more massive our datasets have become, and the idea that fascinates all data scientists is linked with the emergence of AI and ML technologies – how can they be used efficiently?

Here are top 10 trends that you should look out for as they shape the direction of data analytics in our future:

Augmented Analytics: This technology broadly utilizes the power of machine learning to automate data preparation and presentation. Through the use of augmented analytics, data scientists hope to be able to aid human intelligence, to produce rapid outcomes in different data-driven domains.

Artificial Intelligence and Machine Learning: Many of us might still be living in a bubble when it comes to AI assisted work. However, the fact of the matter is, that this bubble is going to burst. With robotics and artificial intelligence taking over at an increasing pace, there is a very heavy emphasis on getting data up and running to meet organizational goals. AI and ML will be used extensively to simplify work processes through the use of Big Data analytics.

Big Data: As technology has been advancing over the years and more affordable machines have emerged, faster processing powers have been available to businesses. Now, as cloud services are taking over traditional storage methods, there is a lot to look forward to regarding the increased output of processed information. As all these sources of information generate data, there is an imminent need to draw meaningful conclusions from the data – this is where Big Data comes into the picture. As the sources for storage get defined, Big Data provides excellent methods for allowing the manipulation of stored data to draw analysis and get the ball rolling.

Cloud and Edge Computing: One can easily say that technology has reached the Clouds. Companies such as Amazon, Google, and Microsoft are providing Cloud Services to organizations for storing their day to day data. Edge Computing, which is another form of shared computing, has become the next generation’s technology. Through the means of Edge Computing, organizations can overcome connectivity and latency issues, so that the distance data has to travel is reduced significantly. Edge Computing has seen an increasing rate of growth in mobile computing, as well as in the decrease of computer hardware. The rising use of IoT-enabled devices has ushered in an era of new technology.

Predictive Analytics: As more problematic situations emerge, there is a need to develop systems which can solve problems with ease and provide meaningful solutions. Predictive analytics prove to be the solution for such issues. The better the insights, the more structured are the solutions. Such are the capabilities of predictive analytics, as they help organizations gear up to tackle the worst possible issues.

Blockchain Technology: Digital currencies, such as BitCoin, owe their very existence to Blockchain technology. Given the success rate of cryptocurrencies, there is a lot of focus on merging Blockchain technology with the world of data science. The idea is to fuse the two methodologies together, to maximize the results. Since Blockchain technology is a versatile source, it can store any digital data; it has become a well-received option with data scientists.

As more and more organizations are taking analytics and data science seriously, there is an imminent need to progress to the next level of technology. Here at Idexcel, we work with clients every day to provide DataOps Consulting and Services; it has become an inseparable part of the modern organizational structure. As we progress into the future, the thin line between business intelligence and artificial intelligence will be removed; data will become smarter than ever before.

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