One of the surveys conducted in 2018 revealed an overwhelming response from the tech giants regarding more interest in
Big data analytics and AI investments. No doubt, today’s business is all about analyzing data. It could be IoT Big data or social media data which has broadened the scope of Big data technologies as a whole. Interestingly, Big data analytics is not the solo player in this game. Furthermore, Big data analytics trends for 2019 indicate a direct connectivity between big data analytics and AI for better big data insights.

But what are the analysis behind it and what are those Big data trends for 2019? Let’s look at 5 big data trends for 2019 which can influence artificial intelligence!

Trend 1 # Big data meets Artificial intelligence with the enhanced use of IoT

No wonder that Internet of Things 2019 trends indicates a sharp growth. As per statistics we are expected to witness a growth of IoT from $1.2 trillion to $6.5 trillion by 2024. It is the increased use of smart devices, automation technology and reduced cost of smart sensors which are triggering high demands for IoT.

Of course, every customer wishes to simplify life with robotic processes like Amazon Alexa or Google Home or Microsoft’s Cortana. But what’s happening behind their functions?

These IoT devices are ultimately generating data which is customer data. It can be sourced to Big data analysis to track the customer behavior pattern, their trends and much more valuable information. Not to mention, today’s businesses are willing to visualize real-time reports and not static reports.

Hence, IoT Big data works as a key provider of data here. Data processed out of Big data tool is fed to AI systems which further applies algorithms to find meaningful insights out of those data. Furthermore, these results processed using big data analytics and AI can be used for further IoT development to create new devices.

Read more on Big data and IoT – A perfect match.

Trend 2# Edge computing will play a significant role in Big data analytics and AI processing

Nowadays enormous data has been generated due to increased use of IoT devices and digitalization in everywhere. One real problem which occurs due to this in Big data is bandwidth issue and lag time to gather those data. This happens because Big data transport takes considerable time to collect and analyze data at the data center of the cloud. This is most of the cases not the actual site of data generation.

To overcome this problem Edge computing takes the pivotal role.As per edge computing working principle, it processes the data at its collection point. No doubt, edge computing in big data enhances the Big data performance in terms of data analysis speed and traffic.

Want to know more how Cloud computing serves in Big data analytics? Read on – The purpose of Cloud for Big data analytics

Now, this increased use of Edge computing is expected to open up new opportunities in AI. Not to mention, this is due to the advanced application of Machine Learning through the implementation of neural networks. Edge computing and artificial intelligence combination will increase the use of Edge devices which will ultimately need special AI chip generation. Hence, there will be a rise of AI enabled chips in IoT – a new business growth area for AI chip manufacturing companies.

Trend 3# More use of Machine Learning for Big data analytics will grow Natural Language Processing in AI

As the machine learning technologies have reached a new dimension in 2018, the ‘big’ benefit of Big data is in realization. However, only when it is blended with intelligent automation. Getting big data insights from the unprecedented data stream( whether it is structured and unstructured) by the human analysts is a real mammoth task.

So,what’s go better than automate this analytical model with the help of Machine learning? Not only such automation model derives the result at a better pace but also provides the below inputs for the business –

-Clear market trend

-Reveals customer behavior

-Uncover hidden data pattern

-Accurate results

-Better data management

Now, Machine learning and Deep learning are the branches of Artificial intelligence. So, in the next level, it will enhance Neural networking to embed the code in computers to think it like humans. Finally, it analyzes the Big data fed into it based on the theory of probability. Big data and machine learning together generate predictions and decisions which is certain to a great extent. 

Know more about Machine Learning vs. Deep Learning

Trend 4#  More use of Big data technologies in Cybersecurity will enhance AI space

With the use of Machine learning and Big data, now companies can perform predictive analysis to identify the deviation of normal data pattern. This, in other words, helps to point out the potential threat areas of business. It is indeed a critical area for any business with the increasing challenges of security issues in the IT world.

Read on Security and Ethical challenges of IT to know more on it.

Big data technologies will be more used to monitor employee activities to prevent possible data breaches. In this scenario, Big data analytics are used to identify the behavioral pattern of the employees inside an organization. Also, Big data analytics will play a critical role in the Intrusion Detection System (IDS) of an organization. This will provide all the necessary data related to the traffic that the IDS system usually monitors.

However, the above solutions do not assure 100% prevention of cyber attacks. Furthermore, if such incidents happen what we need is rapid response to minimize the damage and also to recover from damage. This could be sorted out with the use of intelligent security systems which is nothing but real-time implementation of AI. Machine learning algorithms have the capabilities to respond on an actual basis even with changing patterns.

Trend 5#  AI will be the key to analyzing Dark data set in Big data

Dark data is a subset of Big data which is never analyzed, and remain undiscovered. This is ultimately a potential information loss for the business! And do you know the volume of such dark data? As per the IDC report, 90% of unstructured data remain as dark data in Big data world! But is dark data useful?

As per Gartner “dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing). Similar to dark matter in physics, dark data often comprises most organizations’ universe of information assets. Thus, organizations often retain dark data for compliance purposes only. Storing and securing data typically incurs more expense (and sometimes greater risk) than value. “

So, one of the key Big data analytics trends for 2019 is an increased need for organizations to analyze such dark data. This is expected to present better big data insights. However, harnessing such dark data have different constraints which include

-The legal and regulatory issue

-Intelligence issue

-Technology issue, etc.

Here comes the role of AI for processing and transforming such unstructured data into structured data using different AI techniques like natural language processing. Based on those structured data companies can get better insights on the undiscovered area of dark data.

Final Thoughts

No doubt, Big data analytics trends for 2019 clearly show that it will be growing bigger with changing trends. However, as the analysis trend is pressing the market towards more business goals, adapting Big data and Artificial intelligence capabilities will definitely work as a boon for data-driven competitors in the market. Not to mention, the key technology in 2019 will be Artificial Intelligence, and Big data will aid it with more data power.

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