Business goals have been used to drive apps since well, apps.
Next came efficiency through better workflows.
Now organizations are scrambling to parse through, collect, and use the right data.
If you build an app without a solid data architecture, harnessing the data contained within your app will very likely be a painful and costly endeavor, if it’s possible at all. Data can be disparate, siloed and difficult to transform into something meaningful without the right mechanisms in place, wasting time and money on work that could have been avoided with proper planning.
“Think about it this way: Your enterprise applications will come and go. The one thing that will truly provide competitive differentiation for your organization is your data.” -Informatica, Think “Data First” to Drive Business Value.
If you are starting an app from the ground up, you have the unique opportunity to get your data handled as part of the MVP, which frees you up from many complications later on. Perhaps more importantly, you’ll be able to provide meaningful and immediate insights and business value from the jump.
At a super high level, here’s how to do this:
Step 1: Determine what insights would provide the most value to you and your stakeholders.
These will change over time, but you’ll need to start somewhere.
Step 2: Choose your data points.
Be aware of unstructured data (videos, images, audio, text documents written by humans) and how that might also play in your data landscape.
Step 3: Choose how you’ll collect the data.
With the wide range of high-powered techniques and tools available, there is an art to extracting the data at the right time and in the right form without diminishing the user experience. Using cloud data resources such as Google Cloud Platform will be a valuable feather in your technical quiver.
Step 4: Implement your plan.
There are countless ways to do this. We’ll leave this for you to figure out.
Step 5: Visualize your data.
Step 6: Create business insights.
Again, there’s a virtually unlimited number of ways to do this. The better and user-friendly the tools, the higher the adoption will be at your organization.
Some organizations are doing this right - like Waze. MIT Professors Andrew McAfee and Erik Brynjolfsson point out in their superb book, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (Norton 2014), the genius of apps such as Waze is the ability to recognize third-party or external conditions and inform users of meaningful data points, as well as collect data from the users themselves. From there, Waze uses this information to turn all the smartphones running its program into sensors that upload data continuously — speed and location, for example — to the application’s servers. Social participation and input is also critical so that users know where policemen are or that an accident took place just before an upcoming bridge, for example. This is then processed and returned to users in the form of intelligence that matters — what is going on around them and how can they respond to it — so that they make informed driving decisions. That was impossible before the advent of IoT and modern predictive analytics.
For more information about the conjoining of big data, BI and mobile application development, see this great article on Forbes.
At Skylarq, we approach every project with a data-first mentality. Our small team of senior developers runs circles around traditional software development teams. If you need help harnessing the data contained within your application(s), we’re happy to chat with you to see how we can help.