Four Big Data Trends for 2018
Curious about the future of Big Data and AI? Here’s what the trends have it in 2018 for innovations.
Big Data is too complex to be skillfully handled by traditional processing techniques and Artificial Intelligence is one key area it has found solace in. While Data will soon replace Gold as the most important asset to mankind, putting it for appropriate use has transformed seeking information. Not to miss, the biggest of impactful technologies be it Internet Of Things, Machine Learning or even the Decentralized Apps, Big Data drives them all.
Here’s what the trends have it in 2018 for Big Data innovations.
Talking Robots Will Get Smarter Challenging Existing Live Support Systems
Starbucks have deployed Chatbots to take orders in text while MasterCard lets them reply to your transactional queries. They are cool good examples of automated chatting with website visitors in a more personalized way such that humans don’t guess if they are chatting with a robot. A step ahead of rules based action against a word; Chatbots are processed with possible combinations of the word in the natural language and its varying meanings thereby achieving better communication experience.
New business analytics tools have looked beyond Siri towards more organic communication between humans and machines and hinting at dependable virtual assistance. Such enhanced levels of Customer Experience (CX) has Big Data as the underlying engine that processes volumes of data and produces the most relevant answer based on the keywords in the query, as posted by the user.
Besides, staying focused to the point without losing customer interest; Chatbots are uninterruptedly live, collect and analyze customer data as an enriched knowledge base for different channels. Moreover, they are learning to negotiate too.
In 2016, Facebook allowed developers to integrate Chatbots to its messenger services.
From 30,000 bots deployed in first 6 months to over 100,000 today, the platform is processing 2 billion messages every month. Doubling the interaction between businesses and customers, the use of bots will rise from Facebook to other platforms by next year.
Businesses are already saving upto $0.70 per interaction and a promising 2018 will lead to 85% of AI governing customer interactions by 2020 is surely an exciting hint for the enterprises looking to cut down drastically on support resources.
Accurate Product Searching, Faster Shopping And Many More
E-commerce holds immense potential for the exponential customer data it has direct access to and there couldn’t be a more lucrative platform for Big Data applications to unlatch their ability. One of the largest online retail stores Rockher.com has the most talked about AI implementation backed by IBM Watson. ROSI, the integrated search engine does more than a usual search by computing data of diamonds in inventory and produce accurate results as per the Shape, Occasion, Size and Budget details given by the user.
Such deep customization in search coupled with response time down to a fraction of seconds has steered the focus of others in the league. India’s largest online fashion store Myntra is working towards automated custom clothing without any human intervention. Moreover, the brand wants automated recommendations to users asking for fashion questions. Yet again, the AI tool will crawl through data of years of trends and predict fashion trends for users in advance.
For the retailer, AI will be able to analyze every click performed and track it towards the customer preference for a particular product.
As the global population steering towards online stores will increase significantly to 8.9%, the zest to convert a visitor into a customer will see a momentous shift towards AI tools coming into play in 2018. The acceptance will grow steadily throughout 2018 and will rise by 2019.
2500 Trillion $ from online retail sales are projected for 2018, definitely AI has a role to prepare for.
The Unstoppable Internet of Things Will Continue To Grow
From Coffee Makers to Security Cameras, think of a device and it is connected to a network sharing real time data. Internet of Things has finally earned the acclaim it deserved and a few industries like Insurance are already splurging investments. As the total business expenditure towards IoT is anticipated to touch 6 trillion $ by 2021, responsive devices and a superlatively smarter network is all what the market will be focusing at in the upcoming years.
With such aggressive creation and sharing of content in real time, Big Data Science will spearhead the trends and let AI develop insightful applications; something more critical than just remotely operating our home appliances through phones. In 2017, more than 60% of global enterprises utilized analyzed data from connected devices to optimize processes and save millions.
As of now, 2018 will focus more on fortifying data confidentiality while the ongoing bandwagon to create innovative applications will continue.
Businesses have awaken to the imperative need of a faultless Cyber Security System and AI enabled applications will do just that. Processing historical data of cyber attacks and predicting the strategies for a multi-network setup like IoT, AI defense systems will get more in demand.
IoT is anticipated to contribute 15 trillion $ to global GDP by 2030 and 2018 is the starting point to reach the milestone.
And Finally,
Artificial Intelligence Will Become More Accessible
The SME pool has benefited the most out of the Cloud era, being able to use the best of applications at negligible hardware costing and Artificial Intelligence is the newest addition to their target list. Developing AI functionalities is no more a game of the giant conglomerates as prebuilt, ready to deploy AI applications are already in extensive demand and use. From small scale Chatbots to critical search thinkers, AI is everywhere.
By end of 2018, 75% of developers will be integrating AI enabled functionality in one form or the other into their projects.
Joining the league, Amazon has partnered with Microsoft for ‘The Gluon Network Project’. A sophisticated yet easy to imbibe deep learning library, Gluon lets AI developers built and deploy their ML models in the cloud. Using a Python API, developers can cut down on tedious coding with complete set of plug and play building blocks and highly customizable structures.
Enhancing the neural networks impact on the way we perceive technology, Big Data will compel more than 40% of fastest growing enterprises to automate processes.
Closing at 34 billion $ as the global worth, the agile Big Data markets are gearing up for decisive 2018.
How prepared are you?
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