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The Internet of Things and big data technologies have progressed enormously in 2016 – and 2017 is set to be a year when more enterprise use cases come to fruition.
The IoT architect role will eclipse the data scientist as the most valuable unicorn for HR departments. The surge in IoT will produce a surge in edge computing and IoT operational design.
“Thousands of resumes will be updated overnight,” says Dan Graham, Internet of Things technical marketing specialist at Teradata. “Additionally, fewer than 10% of companies realise they need an IoT analytics architect, a distinct species from IoT system architect. Software architects who can design both distributed and central analytics for IoT will soar in value.”
“Test/dev and disaster recovery will be the main components of a company’s environment that will be moved to the cloud, and production continuing to remain on premises,” says Marc Clark, director of cloud strategy and deployment at Teradata.
Deep learning is getting massive buzz recently. Unfortunately, many people are once again making the mistake of thinking that is a magic, cure-all bullet for all things analytics, according to Bill Franks, chief analytics officer at Teradata.
“The fact is that deep learning is amazingly powerful for some areas such as image recognition,” says Franks. “However, that doesn’t mean it can apply everywhere. While deep learning will be in place at a large number of companies in the coming year, the market will start to recognise where it really makes sense and where it does not.”
By better defining where deep learning plays, it will increase focus on the right areas and speed the delivery of value.
Waze and PokemonGo are just the start. Imagine leaving breadcrumbs across your life journey.
“You leave a breadcrumb at the grocery store so next time you buy some taco shells,” says John Thuma, director at Teradata. “You walk into the store two days later, and an alarm goes off telling you to buy taco mix. Augmented reminders, augmented notation and augmented journey maps.”
A research study from Business Insider estimates that 700 million IoT devices will be connected over LPWAN standards by 2021. Why? Because LPWANs will help IoT to take off.
“2016 was a year of big hype and little progress,” says Zach Supalla, CEO at Particle. “There’s a clear barrier of cost and power consumption when it comes to IoT products and if we can get these two pain points down, IoT will explode. LPWANs connect devices over a larger geographic area and use less power and those companies who can leverage these assets the best, will win out.”
The IoT market will see more consolidation as technology and processes improve.
Much like natural selection, the strongest ones will survive while the smaller players are gobbled up to build out more robust portfolios.
SAP just acquired an enterprise-grade IoT solution last month and Cisco made waves in February when it purchased Jasper Technologies for $1.4 billion.
“The rate at which these tech giants purchase startups will only increase as they continue to thirst for the innovation so many of these young companies are born from,” says Supalla.
2017 will be a “team-building year” for many in the IoT space, says Supalla. Investments will be made in fostering internal talent and attracting the right external hires to address the complex needs of launching a connected product.
Companies will continue to strive for integration while maintaining security – connecting business units and vertical industries such as marketing, healthcare and financial services, instead of restricting access to a handful of data scientists.
“Enterprises will finally be able to speak about big data in terms of ROI,” says Sushil Thomas, co-founder and CEO,Arcadia Data, “and not be limited to a TCO-only conversation that has surrounded it thus far.”
Organisations trying to scale their existing BI platforms to big data size will hit a brick wall with legacy analytics tools.
Research firms like Forrester have seen increasing interest from enterprises not only moving their data to Hadoop, but also running analytical applications on Hadoop clusters.
“Running BI natively on Hadoop allows analysts and business users to drill down into raw data, run faster reports and make informed decisions based on real-time data instead of abstracts,” says Sushil Thomas, co-founder and CEO at Arcadia Data.
“These will include city traffic services reacting to sensors in cars, bringing real-time and streaming data to the forefront in enterprises,” says Thomas.