Given the low cost-to-return ratio afforded by big data, it’s no surprise that the big data software industry is currently expanding in a way that can only be described as exponential. In fact, according to a recent market size and forecast report on information management software, the big data software industry is expected to grow by approximately 50% through 2019. And as more organizations are adopting reliable business intelligence solutions, the revenue being generated as a result is likewise seeing an explosive bloom, with approximately $17 billion created from 2015–2016.
However, the situation isn’t perfect, and some businesses are finding themselves waking up from the dream of big data to something a bit less fantastic. But the truth is that the problems these organizations are facing have less to do with inherent problems in the concept itself, and much more to do with how business intelligence tools are being used. Many businesses do not understand how to effectively use business intelligence software to organize and analyze captured data. The result is that many organizations are growing disenfranchised with the idea of big data itself.
Simply put, the complexity of many big data solutions is putting too much responsibility on the shoulders of IT departments, reducing accessibility for non-tech, and non data-scientist users—and unfortunately, this generally includes CEOs, department leaders, and other decision makers. The end result is that big data becomes underutilized, and the potential ROI falls away quickly.
Fortunately, technology exists that can help users better understand and use big data, such as data analytics software programs that make use of automation, cloud-based storage, cross-platform compatibility, and other advanced features. Perhaps best of all, these programs are designed to be able to operate and be operated without any in-depth technical understanding, collecting, storing, organizing, analyzing, and extrapolating valuable information in a way that is completely accessible for users of all education backgrounds.
Although the basic function of analytics software is to capture and analyze relevant data, there is a significant range of use to be found within this service. Organizations often use such software to self-evaluate business processes, identifying potentially-flawed areas, and helping to determine effective solutions. At the same time, this software can be directed to analyze incoming data in order to chart emergent trends, allowing for business decisions that are better-informed and highly-targeted. In actuality, the limitations of data analytics software often depends upon the parameters set by the user, which means that as long as the data is available, analytics software can be tailored to apply it towards almost any specific objective, such as:
As stated before, the truth is that business data analytics software can be used in an almost infinite number of ways. As long as data is involved, analytics software can interpret it for valuable conclusions.
There are a number of analytics software programs available on the market, and many share a number of valuable features, such as data visualization, enhanced collaboration services, real-time reporting, mobile accessibility, and cloud-based architecture. However, the defining feature of a superior analytics software may well be its intuitive usability. With more and more decision makers becoming directly involved in the analytics process, the need for software that can be used effectively with little or no training is always increasing. Organizations that are interested in finding a truly effective analytics software solution need to first consider the learning curve associated with it. After all, overly complex and non-intuitive programs are much less likely to be fully adopted, company wise, and any analytics program—no matter how powerful—becomes useless, when not used.
The big data software industry will likely to continue to expand for the foreseeable future. In fact, 74% of sales leaders are committed to be using sales analytics within the next 18 months.
But with analytics software becoming ever more available, it’s becoming all the more important for organizations to be able to identify the benefits associated with specific software solutions. By choosing the correct analytics software, businesses can turn the constant flow of raw data into valuable, actionable conclusions, giving themselves a distinct advantage over competitors who do not.