2016 is over, and 2017 is here. Even though we lost some great people last year, it was also a year in which we saw many achievements and accomplishments. For the Xplenty team, it was a good year all around. We recently announced our latest funding and the acquisition of Driven, we now serve more than 120 enterprise customers all over the globe, and we enhanced our platform to support more integrations. We are continuing to add more features to our product to make life easier for data professionals and developers as they deal with data.
So what lies ahead? It’s the time of year many of us make all sorts of predictions. Therefore, I decided to take a stab at it as well. Here are my four predictions for 2017 data related trends.
More data sources and more complexity
It seems that we can’t get enough of data. It’s everywhere, ranging from the producer end to the consumer end. Many of us, individuals and businesses alike, produce and consume data on a regular basis. What are the implications of such massive levels of data production and consumption? On a very basic technical level, it means we need more devices to produce data, more storage to store data, and more computing power to process data. On the social and even philosophical levels, I believe we cannot even begin to understand the impact data has on this world, on our society, and on us as individuals right now. A study from 2011 shows, for example, that our regular, almost natural, reliance on Google to come up with search results affects our memory and our ability to memorize information. But I digress. We will handle more data and more data sources in 2017, and it will be more difficult to integrate and process that data.
More analytics, too
With the increase in data sources and volume, companies will rely more and more on analytics. Data-driven organizations will rule, and businesses that fail to adapt and become data driven will fail. The golden age of analytics is upon us, and companies that are smart enough to capitalize on analytics will flourish. That said, becoming data driven involves much more than creating a slogan and a few eye-catching dashboards. Companies must implement behavioral and structural changes to become data driven, which is a big challenge in and of itself. Here’s a good case study about a few companies and their journeys to become data driven. More analytics also means more data products and tools to use within an organization, including databases, integration and preparation tools, and visualization and reporting tools. This will be a very lucrative market for vendors that can provide the ease of use, flexibility, and scalability required to handle analytics-related tasks.
Ease of use is key
We live in an interesting era in which simplicity and complexity are intertwined. The technology landscape is becoming more complex, but the tools we use to master that landscape are becoming simpler to operate; in the future, I think they’ll become even simpler than they are now. The generation that has grown accustomed to using sleek mobile applications to order a taxi or make a purchase online expects to receive a similar experience whether they’re at work, coding, or running an IT operation. Software developers need to ensure that the products they deliver offer inviting user experiences and intuitive interfaces because potential users won’t flinch before moving on to the next product if it’s not appealing enough, regardless of its functionality.
I’m not trying to diminish the importance of functionality by any means, but I’d like to drive home the idea that user experience is as important if not more important than functionality when designing a software product.
The cloud is everywhere
The cloud is everywhere. Gartner forecasts that by 2020, corporate "no cloud" policies will be as rare as “no internet” policies are today. I tend to agree. At Xplenty, we see them all the time: businesses making their first steps towards the cloud, offloading data storage and analytics projects to the cloud, or building entire IT architectures in the cloud. It’s a massive shift of technology paradigms. The move to the cloud goes hand in hand with the first prediction I made that we’ll have more data sources than we can handle. The move to the cloud liberates companies from the constraints of connectivity, infrastructure, and IT expertise in many cases, and this ties strongly with the phenomena of departmental or even individual projects that can take shape in a matter of days as opposed to months or even years when all the resources are constrained to traditional on-premise IT frameworks.