The big data and analytics market represents a fast-growing multibillion-pound global opportunity. Recent IDC forecasts expect this sector to grow six times the annual growth rate of the overall IT market through 2018, catalysed by line-of-business analysts driving growth into the double digits.
As businesses big and small are exploring new ways to capture, understand, and use their data in ways to differentiate themselves in an increasingly competitive market, the momentum around making big data and predictive analytics more mainstream is only set to grow in 2016. Here are our top five predictions for the year ahead.
- Data scientists will be the head-hunter’s best friend.
Every January, the global tech industry collectively laments the lack of data scientists as industries worldwide churn out unprecedented volumes of data. The past year has seen the number of advertised data scientist jobs in the UK increase by 22 per cent, in addition to the push from the nation’s tech sector for ‘data scientist’ to be added to the UK’s skills shortages list. Across the pond, the US has seen a 27 per cent growth rate for operations analyst jobs - the highest category for growth according to the U.S. Bureau of Labour Statistics, and much higher than national average of 11 per cent.
It’s clear that the hottest job of 2016 will be in data science. Globally, analytics is the new maths, opening doors for those with the skills. The increase in the number of university programmes that incorporate data analytics as standalone modules within business degrees stands as a testament to the growing appreciation for data science as a business skill beyond the four walls of computer science departments.
While this year will see the rise of the data scientist, the year will also see empowered line-of-business analysts taking charge of the data generated by their own departments for real-time data-driven decision making. These line-of-business users ultimately have the upper hand when it comes to analysing function-specific data. A centralised data scientist within an organisation, however, would understandably take longer to dissect and understand niche data, potentially working on a marketing project one day and a manufacturing operations project the next.
According to a TDWI survey of senior management professionals in business intelligence and analytics, you no longer need a degree in statistics, mathematics or any other quantitative discipline to carry out predictive analytics. Interestingly, only 34 per cent of the business intelligence and data warehousing executives surveyed see it as crucial for analysts to have an academic background in statistics or mathematics. There are specific analytics tools for that. What’s more important is knowledge of the business, critical thinking, and a deep understanding of the underlying data being analysed. This poses an interesting challenge to businesses lobbying to address the global “analytics skills shortage”.
- IT departments will embrace the self-service analytics programme.
Last year, Alteryx surveyed data analysts on the top barriers facing the industry. More than a third (37 per cent) of these industry experts cited waiting for data from other departments as a huge obstacle in their way, while another third couldn’t access the data they needed. It’s easy for analysts to make inferences with whatever little data they have on hand, which could lead to flawed results. This is why open, instant access to data is crucial for line-of-business analysts to run the right figures and make the right data-backed decisions.
There are people across the business that have characteristics of data analysts in their day to day jobs. This could be the marketing professional or business development executive yearning for data analytics to inform their strategy. With this swell of interest and activity in data analytics, it’s interesting to note than more than half of the respondents (52 per cent) in the survey from Alteryx are forced to use too many tools and or deal with long processes that ultimately tack on extra time. In 2016, rather than having to add to their work load by having to pull data for each department, IT departments will take on a strategic role in providing the right infrastructure for analytic independence across business functions.
- Data gravity will pull analytics to the cloud.
2016 also will be the tipping point for analytics in the cloud. The best part of this decade has seen the business world recognise the benefits of the cloud as a phenomenal business delivery platform. As more and more data sources move to the cloud, we are seeing analytics gravitate towards where the business data lies.
The term ‘data gravity’ refers to just that - organisations tend to have their analytics tools closer to where their data is. For example, if enterprises are using data sources like Amazon Redshift, SQL Azure, or Spark in the cloud, it makes business sense to opt for analytics tools that also work in the cloud. 2016 will see an increase in such cloud-born data, which will fuel analytics in the cloud. Even for businesses with the majority of their data on-premise, the rise of the mobile sales force means that various data sources need to be blended, analysed and shared remotely, such as Salesforce data with on-premise SQL server data.
An analytics tool that can live both on-premise and on the cloud can keep businesses transparent and up-to-date in real time.
- The Internet of Things (IoT) will propel businesses to explore geospatial analytics
Analysts will begin to get an unprecedented amount of location reference data from connected devices. According to a top industry analyst firm, only 23 per cent of organisations are presently using location intelligence to make business decisions. With the plummeting cost of IoT devices, however, this is set to change dramatically in 2016. We would expect this figure to potentially double by the end of 2016 with the drop in cost and the rise in self-service analytics platforms.
For many companies, figuring out how key variables interact based on their physical location will become critical. We work with a lot of retailers and quick-service restaurants, where the analysts are constantly examining demographic changes, store revenue projections, customers and their proximity to what the nearest store might be and other metrics. Beyond the service sector where geospatial analytics are traditionally used, we are starting to see more interest in unexpected industries.
For example, healthcare services company Cardinal Health uses geospatial analytics to understand where to build and establish nuclear pharmacies. These outlets are used to produce cancer detection medication which only has a six-hour shelf life, so being close to where the medicine is consumed is of critical importance. While IoT has been a prominent topic of discussion in the tech sector for several years now, this will be the year that data analysts move beyond collecting data generated by these connected devices and begin combining this data for deeper analysis.
Big data and analytics solutions present significant business opportunities, and with the start of 2016, organisations that are able to take advantage of the most important trends in the analytics space will be prepared to enjoy the best of big data.
Stuart Wilson, VP EMEA, Alteryx, Inc.
Image credit: Shutterstock/Sergey Nivens