According to the research, undertaken by Hitachi Vantara, a wholly owned subsidiary of Hitachi, the adoption of IoT platforms will dominate enterprise IT strategies in 2018, with IoT solutions delivering “valuable insight to support digital transformation” rapidly becoming a strategic imperative in almost every industry and market sector.
The predictions for IT trends for 2018 are jointly authored by Hubert Yoshida, chief technology officer for Hitachi Vantara, and Russell Skingsley, chief technology officer for the Asia Pacific region.
According to Yoshida, IT must work closely with the operations side of the business to focus on specific business needs and define the scope of an IoT project.
“Enterprises should look for an IoT platform that offers an open, flexible architecture that simplifies integration with complimentary technologies and provides an extensible ‘foundry’ on which to build a variety of industry applications that companies need to design, build, test, and deploy quickly and with minimal hassle,” Skingsley says.
Here’s Hitachi Vantara’s other predictions for IT trends in 2018:
2: Object storage gets smart
Enterprises started their digital transformation this year but the first problem that they ran into was the ability to access their data. Data is often locked in isolated islands that make it costly to extract and use. These islands were built for purpose and not to be shared, and many contain data that is duplicated, obsolete or no longer used because of changes in business process or ownership.
“Data scientists tell us that 80% of the work involved in gaining analytical insight from data is the tedious work of acquiring and preparing the data. The concept of a data lake is alluring, but you can’t just pour your data into one system, unless that data is properly cleansed, formatted and indexed or tagged with metadata so that the data lake is content aware. Otherwise you end up with a data swamp,” commented Skingsley.
While object storage can store massive amounts of unstructured data and provide metadata management and search capability, the ability to be context-aware is missing. Object storage now has the ability to be “smart” with software that can search for and read content in multiple structured and unstructured data silos and analyse it for cleansing, formatting and indexing.
“Hitachi Content Intelligence can extract data from the silos and pump it into workflows to process it in various ways. Users of Content Intelligence can be authorised so that sensitive content is only viewed by relevant people and document security controls are not breached. Content Intelligence can create a standard and consistent enterprise search process across the entire IT environment. It can connect to and aggregate multi-structured data across heterogeneous data silos and different locations and provides automated extraction, classification, enrichment and categorisation of all of an organisation's data,” said Skingsley.
3: Analytics and artificial intelligence
Next year will see a growth in analytics and artificial intelligence across the board as companies see real returns on their investments. According to IDC, revenue growth from information-based products will double the rest of the product and services portfolio for a third of Fortune 500 companies by the end of 2017.
“AI became mainstream with consumer products like Amazon Alexa and Apple Siri, and Hitachi believes that it is the collaboration of AI and humans that will bring real benefits to society. Through tools like Pentaho Data Integration, our aim is to democratise the data engineering and data science process to make Machine Intelligence – a combination of Machine Learning and AI – more accessible to a wider variety of developers and engineers,” said Skingsley.
Pentaho’s machine learning orchestration, with integrations for languages like R and Python and for machine learning technologies like Spark MLlib, are steps in that direction. Lumada, Hitachi’s IoT platform, enables scalable IoT machine learning with flexible input and outputs, standardises connections that can automatically configure and manage resources, and is compatible with Python, R and Java for machine learning.
4: Wider adoption of video analytics
Video content analytics will be a “third eye” for greater insight, productivity and efficiency in a number of domains beyond public safety. Algorithms that automatically detect and determine temporal, spatial and relational events combined with other IoT information, like cell phone GPS and social media feeds, to apply to a wide range of businesses like retail, healthcare, automotive, manufacturing, education and entertainment.
Yoshida believes that video can provide unique functions like egomotion — 3D motion used in autonomous robot navigation — behavior analysis and other forms of situational awareness.
“Retailers are using video to analyse customer navigation patterns and dwell time to position products and sales assistance to maximise sales. Video analytics relies on good video input so it requires video enhancement technologies like de-noising, image stabilisation, masking and super resolution. Video analytics may be the sleeper in terms of analytics for ease of use, ROI and generating actionable analytics,” Yoshida said.