Many grandiose big data development predictions are made each year, but surprisingly enough, only a few publications focus on presenting the decision makers’ side, in terms of their daily big data challenges and dilemmas calling for action. This article is taking a new angle to the 2015 big data predictions, spotlighting the decision makers in charge of the 2015 big data projects – the people that we are developing our solutions for.
Big data technologies are continuously evolving and new players are constantly joining the big data landscape. But like in all fields, there’s not enough room for everybody and only the strong ones will survive. That’s nature.
After countless meetings with prospects over the years, and recurring requests and statements, I find that in order to truly be able to provide a market-winning big data solution, it is necessary to first figure out how it can turn the organizations into winners. In other words – what does the client need? What are his dreams and highest hopes in terms of big data technology? And most importantly – what does he need big data analytics solutions for???
Identifying the challenges the decision makers are facing, and the criteria, that in their opinion, has to be met by the vendors – requires a deep analysis, and a healthy differentiation of main issues that need to be dealt with, from less critical subordinate items that may be stalled.
With the above notes taken into consideration, five major factors will dominate the decision makers’ selections of their 2015 Big Data Analytics solutions:
- Driven by a fast ROI, predictive analytics will become a primary factor when companies consider either a continuing or initial investment in big data and analytics projects. Initiatives maturing from POC to pilot or production and beyond, lead to the ability to capitalize on the insights to launch new applications, products and services before competitors. As much as “low TCO and fast ROI” are perceived as a cliché and all of us are exhausted from using and hearing these terms – decision makers are still on limited budgets and still need to demonstrate the benefits of the products they have invested in, quickly.
- Seamless integration and quick implementation of big data products into IT and business processes will be uncompromised. Businesses that are looking to use big data for reducing business risks and achieve growth, or to apply big data analytics to their sales campaigns, will show a lot of interest in solutions that can be applied quickly to their IT infrastructure. A seamless integration provides data science teams with strategic competitive advantages, ultimately reflected in financial results.
- Ease-of-use – the promise of big data analytics lies in its ability to transform businesses into data-driven cultures. Analytics can be overwhelming and confusing when combined with complicated systems that are time- and resources- consuming. In order to adopt analytics, companies will strive for solutions that are simple to use, move fast, with high performance capabilities. In other words – products that deliver a systematic framework for guiding the companies’ approaches and priorities, addressing their quickly changing wants and needs.
- Flexibility translated directly into business benefits– data-driven companies will want their insights sooner than later. Flexibility related to how, when and where of getting to critical insights, will play a major role in the investments selections. In other words, decision makers will want accessibility to their data through their mobile devices, tablets and more.
- Recruitments – Companies will raise their investments related to recruitments of people who know what to do with big data. Nowadays, analytics are used in ways that differ greatly, depending on the human minds that interpret them. Data scientists are on the rise and are expected to bring major added value to organizations, leading them to excellence. These key individuals will obviously play a major part in the selection of big data analytics solutions for the organizations.
2015 is the year that organizations will be looking to fully utilize their big data products and take advantage of their existing intelligence, prioritizing the right use cases, and ultimately gain business advantage.