Big Data and Mobile Apps Are Converging in the Enterprise
Yesterday,
I nearly drowned in a sea of extraneous data. In just one hour during
an important conference call, my laptop overflowed with 300 e-mails from
an email thread I frankly didn’t care about. Imagine how much time I
could have saved if my system knew I was unavailable, and sent me only
the two notifications I truly needed: That the customer I was on the
call with owed us an invoice, and that my next appointment was delayed
by half an hour.Clearly, enterprise users need an easy and intuitive way to parse all their data into a useful context. Just as clearly, they also need to have the right information delivered to them at the right time, on the right device. These days, that device is likely to be mobile — be it laptop, smartphone or tablet — as sales of desktop computers erode and enterprises increasingly accommodate tablets in the workplace..
I say it’s time for big data to play a starring role on the small screen — the small screen of mobile devices, that is. Businesses primarily view big data as collecting and storing zetabytes of data from diverse sources for eventual business analysis. But in today’s connected and mobile world, decision-makers can’t wait for “eventual.” They need big data apps that intelligently gather and analyze data as it comes in from other apps on their device (your calendar and sales management apps, for instance). Think of the ramifications: big data apps could suggest different ways to improve sales or — dare I say it — know not to send me thousands of emails on topics I don’t care about when my calendar shows I’m in a meeting.
Such contextual real-time analytics can be extended across any number of roles and tasks: A sales rep driving to one meeting could be alerted that a good prospect two blocks away wants to meet. A Chief Marketing Officer could see which social media campaigns deliver the best return on investment. Or an inventory manager could know which store just sold out of fashion’s “It” purse and needs immediate replenishment. These are just examples. The convergence of big data and enterprise mobile apps means that anyone, anywhere, can glean the insight she needs to make better, faster decisions.
Think Like a Consumer
The key is in the design. Developers building mobile apps for the enterprise need to combine the ease of use of consumer apps with enterprise-class security and data-collection technologies. And they need to optimize their apps for each device’s small screen.
Consider Intuit’s Mint, which organizes and analyzes consumers’ finances. The company’s desktop, tablet and smartphone apps are all designed to maximize both screen real estate and context. On the desktop app, you can manage and sort your finances in full detail. Mint’s tablet app is smaller and more limited, enabling you to see a list of accounts, but not interact with them in the same depth. Its smartphone app focuses on notifications. Imagine how much could get done if businesses designed their big data apps this way.
In healthcare, for example, doctors making bedside rounds could tap into mountains of clinical research to discover the optimum treatments for their patients — and they could see the results as instantly intuitive charts or as scrollable lists (similar to the iPhone’s email app) depending on whether they’re carrying tablets or smartphones.
In IT, big data apps could predict cyber-attacks and send alerts, show scenarios and recommend actions depending on which mobile device technologists are carrying.
These are just examples, but I firmly believe that big data will soon permeate every aspect of business. I also believe that the convergence of contextual, real-time, data with mobile devices makes everyone and everything smarter. When you look at it that way, the small screen becomes huge.
Roman is GoodData’s visionary leader; in 2007 he had the crazy idea that cloud computing could finally make good on the broken promises of generations of BI. Roman has been a tech entrepreneur for almost 20 years. He was Founder and CEO of NetBeans (acquired by Sun Microsystems) and Systinet (acquired by Mercury Interactive and later Hewlett Packard).
Clearly, enterprise users need an easy and intuitive way to parse all their data into a useful
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