6 Hot Tech Trends for 2017
Data sciences and machine learning is going to be on everyone’s radar and that’s not rocket science.
Photo Credit : mbacrystalball.com/,
Sundeep Sanghavi, cofounder and CEO of DataRPM, a graduate of Microsoft’s Seattle Machine Learning Accelerator, explores six exciting new trends that will make you look at data science and machine learning with fresh eyes.
1. Automated Machine Learning Will Dominate the Data Science Industry
For those that aren’t au fait with the term, Machine Learning (ML) is a subfield of computer science that sees computers (and other devices) gifted with the ability to learn things without explicit programming.
This year, we will see Automated ML dominate the data science industry. Part of the reason for this is that Data Science and ML are intrinsically linked.
Over the coming year, companies and startups looking to work in Data Science will seek out those candidates with a sound knowledge of ML. Those without this basic building blocks need not apply.
2. Traditional business intelligence will be replaced by the Internet of Things
Traditional methods of gathering business intelligence will go the way of the Dodo as the Internet of Things (IoT) makes it easier than ever to gather this sort of information. Essentially, as the rise of sensor-driven devices engulfs all facets of society, about 50 percent of business intelligence (BI) platforms will capitalize on event data streams to find meaningful trends.
Sound like a long shot? It shouldn’t. Analysts from Gartner predicted this two years ago, so it isn’t exactly news. In the same way that ML will perform a not-so-hostile takeover of Data Science, so the IoT will colonize business intelligence. Time to skill up.
3. Money's no object
That is to say, spending on Data Science and ML is about to rocket. This is because, as an industry, Big Data and Data Science Analysis are moving out of an ‘emerging’ stage and into an established, more mature one. Currently, just 30 percent of businesses have experienced the Big Data revolution, but all of that is about to change.
Analysts also predict that between 2015 and 2019, Big Data spending will increase by more than 50 percent to 187 billion dollars, a net increase of 64 billion dollars in just four years. This year, 2017, sits neatly in the middle of that expansion so expect to see a sharp increase in spending across the sector.
4. Validate and explain
Part of the reason for the Big Spending boom is due to an increasing need to see validation and explanation of the data produced by all these millions of machines and events. After all, businesses investing in all this Data Science collection will, rightly, want to understand it.
As the industry currently sits, the United States is lacking some 200,000 data scientists, the people needed to make sense of all the information gathered and processed by numerous machines and algorithms. Naturally, this talent won’t come cheap and data scientists will be in great demand over the next 12 months.
5. The industrial IoT
A lot of the time, IoT news focuses on lifestyle fads such as watches that can turn on your TV and other wrist bands that can predict when you might die based on the amount of exercise you do. Ok, that might be a bit of an exaggeration, but you get the point.
However, the IoT is not limited to consumer goods. What happens when factories, oil tankers and hospitals all become connected in one glorious tech-type Hive Mind? According to Joseph Sirosh, corporate vice president of Data Group and Machine Learning at Microsoft, this trend in itself will change the ways in which we manage everything from football matches to electricity grids. It’s a Big Deal—capital B, capital D.
6. Every business to run on algorithms
You know those annoying processes that are done manually? Things like finances, monitoring sales, checking balance sheets and so on? Well, machines are about to remove those boring burdens from your tired shoulders.
Cloud accounting is a great example of one area where that is already happening. Invoices and payments are automatically processed in a fuss-free manner that frees up time for the more important aspects of running a business.
This article is an edited excerpt of a post titled, “Six New Data Science and Machine Learning Trends to Watch in 2017”, by Sundeep Sanghavi, cofounder and CEO of DataRPM, found here.
Around The World