We’re not quite ankle-deep in 2017 yet, but it’s most definitely getting in between our toes. Look for these six business intelligence trends to dominate 2017. By the time we’re knee-deep (or even shin-deep), they’ll be directing how people do business in the BI space.
1. Cloud adoption will continue to outpace on-premise adoption
Call 2017 a storm, because the cloud is going to continue to grow.
If you’re confused about what the cloud is (*raises hand sheepishly*), cloud computing is “storing and accessing data and programs over the internet instead of your computer’s hard drive.” And its popularity has exploded over the past few years. So much so that Gartner now says find quote we had trouble finding
According to Gartner research (paywall protected, but worth every penny), a cloud-based infrastructure is one of the key critical capabilities for any business intelligence software. Those critical capabilities, by the way, are the same ones used to help place vendors on the yearly Magic Quadrant (again, paywall protected, but worth it).
In last December’s #makedatasimple Crowd Chat, BI experts discussed what technologies would grow, and which would go, in 2017. Their responses suggest the cloud’s continuing importance:
If you’re an SMB, why should cloud computing interest you?
- Cloud computing’s actually more secure. If you’re an SMB, you might not have the same cyber-security resources as a cloud service provider. Data’s what they do, so they usually have “more computing power and more robust defenses.” Cloud service providers are like professional bodyguards for your data. The kind with glasses and earpieces who radiate a sense of quiet, Zen-like danger.
- The cloud doubled SMB profits and grew revenue by 25%, according to one study.
- Data and information stored in the cloud is accessible anywhere. Need data while you’re away from work computer? If that data’s in the cloud, it can be accessed anywhere, on any device.
- That same anywhere, anytime accessibility makes collaboration easier, wherever your your people are. So that team member on maternity/paternity leave who just had a genius brainstorm during the 3:37 AM feeding? They can log in, hop on, and share the info, even if other people won’t see it until a godly hour (shout-out to new parents. Hang in there, guys.).
2. Machine Learning will make business intelligence more intelligent
In other words, it’s designing the machine (i.e. the computer) to learn on its own, so you don’t have to constantly reprogram it to learn new things. It’s the computer world’s equivalent of a fast learner.
For the past few years, a combination of machine learning and AI has collected a lot of buzz, and it looks to become an even bigger business intelligence trend in 2017. This machine learning/AI blend found its way onto Gartner’s Top 10 Strategic Technology Trends for 2017 (paywall protected), where Gartner recommends businesses “evaluate a number of business scenarios in which AI and machine learning could drive specific business value, and consider experimenting with one or two high-impact scenarios.” It’s a sharp suggestion, given the ways machine learning can help businesses:
- Using machine learning helped increase “revenue up to the 20 times by tracking buyer behavior more quickly”
- Using machine learning has helped with “auto-correcting queries”
- Using machine learning can help hospitals design more effective treatments “by analyzing vast databases of medical case histories.”
- Using NLP (natural language processing), one example of machine learning, can cut down on the time you spend crunching numbers to get insights from data
3. Intelligent Digital Mesh is the new horizon of digital business
“Digital mesh,” a buzzword so hot right now even Hansel would blush, comes from Gartner’s review of 2017’s top tech trends. Gartner defines it as “a mesh of of people, devices, content and services” that makes up digital business, and makes digital business possible. With the increasing “blurring of the physical and virtual worlds” in digital business, people, and the business they do, are increasingly interwoven with digital ways of doing things.
The digital mesh is everything from the business intelligence software you use, to the machine learning algorithms that software uses, to the IoT devices that feed information to that software. That information, and those devices, mesh with you. Their combined impact is what makes digital business possible. And the success of your business strategy depends on how well you use the things that make up that mesh.
Analogy time: if you’re a business Jedi, the digital mesh is the Force. Even if you’re not a Jedi, and just force sensitive like Donnie Yen in Rogue One, the digital mesh will be with you. Always.
And, in the same way the plots of the Star Wars movies revolve around people who know how to use the force, the business world will revolve around people who know how to best use everything that makes up the digital mesh, from using AI and machine learning to “inject intelligence into things,” to capitalizing on new ways for your employees to collaborate.
4. Collaborative business intelligence accelerates insights
Look for collaborative BI to get bigger and better in 2017. Why? Collaboration offers a lot of benefits, and it adapts to broader workplace trends.
Employees (Millennials in particular) increasingly expect easy collaboration. I’ve been in group meetings with teammates as far away as Austin, TX, and Madrid, Spain. All that took was wrangling an app for a few minutes. A lot of my meetings now start with everyone opening the same Google doc, whether they’re physically present or not. It brings new meaning to that cliche about “being on the same page.”
When you’re shopping for BI tools, Gartner recommends that the tool have discussion threads, at minimum, as well as the ability to “like” content the way you would on LinkedIn or Facebook. Helpful extras to consider are features like real-time collaboration, and the ability to collaborate in the mobile app, as well.
One particularly impressive development in collaboration this past year was Yellowfin BI’s Business Analytics Workflow. Business Analytics Workflow takes the Gartner discussion board requirement one step further by organizing it around a kanban-style system, making it far easier on the eye than traditional discussion boards. Analytics Workflow also includes a heads-up-style system called Smart Tasks that creates items on your to-do list if your “data falls outside predefined threshholds.” One Capterra review said Yellowfin’s collaborative features helped with “creating a learning environment for our constituents.”
5. BI security is as essential as ever
One future trend of business intelligence is the so-called “democratization of data,” a process where those outside of IT departments will be able to get data as readily (or close to) as trained data scientists and tech experts. “Democratization” in this case implies more people accessing more data. That means more chances for that data to be lost, hacked, or misused.
Businesses are already planning chunks of spending around this increased vulnerability. 47% of enterprises “plan to increase spending on security technologies (access control, intrusion prevention, virus/malware protection, identity management, privacy) in 2017.” The SMB reaction isn’t far from that, with small businesses ranking cyber security as their number one priority in one study. Gartner’s predictions for 2017 also stress the need for security, citing the “relentless and ever-increasing security attacks” present in cyberspace.
6. The data scientist shortage is coming…plan accordingly
Numbers are useless without people to crunch them.
For all the talk of what data can do for your business, it’s only talk if there aren’t people who can turn raw data into insights. And it’s generally agreed that there will be a shortage of data scientists in the coming years.
All this helps explain why data scientists make six figures, according to Glassdoor.
One response to the data scientist shortage is to drop the need for data scientists. With the proper use of machine learning technologies, like NLP, a data newbie could ask the computer, rather than depending on their department’s overworked data scientist to translate the query into a programming language. IBM boasts that Watson, their machine-learning enabled AI program, will be able to do just this.
What does this mean for your SMB that may not be able to drop six figures on a newly-minted data scientist? Be on the lookout for business intelligence programs that use natural language processing.
Business intelligence trends I missed?
Are there any business intelligence trends you think will be particularly important or influential in the coming year that I didn’t list? Any vendors you think are really dominating these trends already? Let me know in the comments below.