Predicting the future is never an easy task. But as 2015 winds down, we can’t help but look forward to what the new year will bring.
Will you finally be able to buy a self-driving car? Will machines become smarter than man? And what, will happen to the world of data science?
We’re no fortune tellers, so we rounded up a bunch of experts to ask them what they thought. And here (in no particular order), is what they said:
What is going to be the biggest data trend of 2016?
“2016 will be exciting for Big Data – Big Data will go even more mainstream. 2016 will also be the year when companies without solid big data strategies will start to fall behind. In terms of technology, I see particular growth in real-time data analytics and increasing use of machine-learning algorithms.”
“In 2016, the world of big data will focus more on smart data, regardless of size. Smart data are wide data (high variety), not necessarily deep data (high volume). Data are “smart” when they consist of feature-rich content and context (time, location, associations, links, interdependencies, etc.) that enable intelligent and even autonomous data-driven processes, discoveries, decisions, and applications.”
“In 2015 we learned that 90% of the world’s data had been created in the previous 12 months. In the middle of this BigData explosion, I watched many executives desperate to get themselves up-to-speed as quickly as possible, in order to understand the commercial opportunities that these vast quantities of information will offer their business.
In 2016 – I hope to see those same executives not just looking towards how they can capture as much commercial value from that information as possible, but how they can create the best experiences for their customers. The bigdata motto for 2016 therefore needs to be “We must create more value from data than we capture.”
“2016 will be the year of deep learning. Data will move from experimental to deployed technology in image recognition, language understanding, and exceed human performance in many areas.”
“I would say Data science for the masses is one and the other is more disruption with open source technologies to the point that no one knows what Hadoop means anymore, and more projects we never heard of trying to flatten the time to data science.”
“[In the last decade] an ecosystem of tools, services, and companies have been built to address these digital problems. This is by no means meant to downplay those contributions. A decade later, and we built some amazing technology and products. These are, for the most part, solved problems. What remains unsolved are data problems in the real, physical, world.
The next decade of the big data industry will be about solving these problems. Borrowing what we know about building highly available, scalable, smart systems, and inventing new systems for analyzing streams of data emitted when analog actions and decisions occur.
This is both a natural progression of the industry, but also a fundamental shift in the kinds of technologies, people, and companies that will constitute the next generation of the data industry.”
“I think Big Data is ripe for consolidation in 2016. However, I see consolidation playing out differently in this space. Rather than one analytics firm taking over another, I see analytics being added into all sorts of enterprise software, from threat detection to marketing automation. The consolidation will happen horizontally in a variety of platforms, and some Big Data startups could well get absorbed by an incumbent in whatever vertical it is that they are disrupting.”
“Next year, the mantra “It depends” will become the accepted answer to all questions about how to share/viz/chart your data. Accepting the spectrum of audiences, purposes, and datasets will become the norm. Bar charts, pie charts and even wearable art will be accepted as valid ways to visualise data, as long as the creator has delivered something appropriate to the objective and the audience.”
•inspired by my latest column on ComputerWorld: Living With Data
“Open Data finally starts to get much better. It’s no longer enough to publish a data dump of info and expect the public to sift through it. From company transparency reports to government spending to crime stats, in 2016 we’ll rapidly move beyond crude data-dump Open Data to more sophisticated efforts that let the public actually use Open Data without requiring semi-advanced analytical or code skills.”
“I believe the main data trend of 2016 will be rise of the data savvy professional. Every organisational department (marketing, finance, HR. etc) is increasingly getting access and ownership over its own data. This democratization of data creates the requirement for all professionals in every team to have basic data science skills.
Consequently, and in addition to hiring full time data scientists, organisations will be looking for employees that can be part of such a data driven culture. These professionals do not need to have the level of competence of a real data scientist, but they will be required to handle and analyse their own data up to a certain level, and to ask the right questions.
These professionals will need to be data savvy! Since few already have this ability companies like DataCamp have taken the lead at getting the needed skills to professionals without interrupting their careers, and to turn them into data savvy professionals.”
“Several jump to mind but the one that sticks out is the surge in new apps that use strong encryption to secure mobile messaging, voice, video and file exchange, for businesses as well as individuals. Not many people have noticed this yet but they will. Doubtless, governments will be unhappy but there is no stopping this one. Businesses in particular no longer trust open communication so we’re heading for a world in which it will all be encrypted.”
“The use of personal-identifiable data is becoming a growing concern for consumers, a focus for regulators, and a battleground for consumer trust. Companies that proactively respect and protect consumer data are going to be the winners. Privacy will become the killer app for 2016.”
“Artificial intelligence for mobile phones (your phone being able to figure out what you are doing and predict what you are going to do next).”
– Andrea Cox, Open Data Institute
“Next year businesses will look at deriving value from ALL data. It’s not just the Internet of Things but rather Internet of Anything that can provide insights. Getting value from data extends beyond devices, sensors and machines and includes ALL data — including that produced by server logs, geo location and data from the Internet.”
“In 2016 I’m looking to fund those businesses that make possible to create APIs, turn web into data, all those difficult problems that constitutes the plumbing of the Internet, will be the like the Levi’s of the net”
“Enabling users to see a broad range of factors contributing to their business is becoming more important than ever. With the ability to combine both internal and external data sources, users now have access to more context around their data, which ultimately leads to more insights and better decisions. Adding socio demographic or location data to analysis easily and quickly can help organisations de-risk some of their management choices.”
“Machine learning will reduce the insight killer — time. Machine learning will replace manual data wrangling and data governance dirty work. The freeing up of time will accelerate data strategies.”
“As with every industry, disruptive forces—security, sustainability, speed and costs—are driving change in the way data centers are architected, constructed and operated. This should continue throughout 2016 as the ability to deliver applications and content to users while collecting and analyzing data becomes more critical to business success.”
“The use of masses of data as an indicator of success will turn to the quality of the data being collected. This will mean that the variety for each company is likely to decrease, but the specific data that will be collected will become far more efficient, useful and plentiful. As companies realize that most of what they collect isn’t being used and just taking up storage space, this will become more apparent and the use of this data will come under increased scrutiny.”
“In 2016 it will be all about what actions you will derive from the data you have access to. Bring in the algorithms. Algorithms define action and they are very specific pieces of software that are very good at a very specific action, much better than humans can do. Think for example of quickly determining the right advertisement based on your profile when you visit a website or finding an outlier in vast amounts of transaction data to determine fraud.”
“Because big data needs a lot of processing power, many organisations will make use of cloud-based, big-data-as-a-service offerings, so they can get the full value of their information, without the associated capital expenditure.”
“2016 will see an expansion of big data analytics with tools that make it possible for business users to perform comprehensive self-service exploration with big data when they need it, without major hand holding from IT.”
Did they get it right? Only time will tell!
Give us your best prediction for 2016 in the comments below.
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