According to IBM, we create around 2.5 quintillion bytes of data
every day. For this reason, Economist has projected that there would
be seven times more data in 2020 than what was created in 2014.
This unprecedented growth was the main reason behind the arrival of
the one of the most innovative inventions of the digital age, the Big
Data. It has not only provided a way to the businesses to extract
benefits from the burgeoning data but it has also helped to increase
efficiency in every business process.
In this piece, we’re going to take you through a deep analysis of
current trends and future possibilities of Big Data.
Machine Learning
According to Gartner, machine learning has been one of the top trends
of 2016. The term machine learning refers to the key element for the
preparation of data and predictive analysis in businesses moving
forward.
The next step would be the creation of a link between data analytics
and cognitive computing. Somewhat it is in the same way that
businesses of today has accepted the relationship between analytics
and big data.
Budding Romance with Artificial Intelligence
Hottest trend we have seen in the early months of 2016 is the
increasing focus on AI by Big Data analytics solutions. This is because it
helps in analyzing gigantic amounts of data and gain meaningful
insights.
Current resurrection of AI is pretty much the result of Big Data. The
area that is getting the most attention in Artificial Intelligence is
that of Deep learning. Though its algorithms were created decades
ago, it wasn’t until now that they could be applied to gigantic
data in a cheap and quick manner and unleash their full potential.
According to graph of Google Trends, Deep Learning is the buzz word
that can be seen at an uphill trend and gaining popularity among the
users (alongside the term “machine learning” which has been
already discussed above). Coming back to the AI, it has been working
at its best to help Big Data deliver its promises.
Spark all the Way
Creating a lot of buzz, Apache Spark can be seen growing as a
complimentary analysis tool and will certainly continue to grow in
the same way for a long time to come. Various players including IBM
and Cloudera have already embraced the open source framework that has
provided with required credibility. The key reasons behind its
success are that it is much faster than Hadoop's MapReduce, easier in
programming, and holds the ability to lend itself to machine
learning.
Conclusion
In many ways, we are still in the early phase of the Big Data
revolution. It was just the first phase that included the development
of infrastructure for the storage of massive amounts of data.
Artificial Intelligence is gradually bringing about a trend towards
the inception of the application layer of Big Data. The pairing up of
AI and Big Data will be driving an incredible innovation covering
every single industry. To conclude, Big Data is about to get a hell
lot of bigger than you ever thought!
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