Big data has become a household name in the past few years, and more industries are beginning to embrace the technology with the passing of each day. While a general understanding of what the solutions do and how they work is shared among decision-makers and IT professionals, the specific demands of management and policy creation tend to be a bit more foggy given the sheer novelty and rapid innovation of analytics tools.
This is why so many firms have begun to outsource big data projects to vendors of solutions and services, given the need for speedy time to market and expert management of the technologies and processes themselves. One of the more overlooked demands of business analytics software is the data preparation aspect of management, which will often dictate how successful the projects are in the long run.
In focus: Data preparation
Philip Howard, research director for Bloor Research, recently published an analysis piece in IT-Director.com to explain some of the reasons why older data preparation processes and strategies will simply not be as effective today, as well as what needs to be done to improve them. According to Howard, demand for streamlined and optimized data preparation services and support has appeared to grow in the past few years, leading many vendors to adjust their offerings.
Considering the fact that enhanced demand will spur competition and lead developers toward more innovative pursuits, data preparation practices and service offerings are likely to expand significantly in a relatively short period of time. The author pointed out that consolidation will play a major role in trends relevant to data preparation, with service providers focusing on the creation of comprehensive packages that assist clientele in efficiently enjoying accurate insights.
Manipulating a wide range of data formats and types can be difficult for any business, which is why managed service providers are in such high demand today.
Importance of proper preparation
When data preparation is not handled properly, the chances of seeing the desired results from business analytics endeavors will be inherently lower, as the files involved will not be fueling insights as well as they should be. Any company that is not entirely comfortable with the demands of data preparation but is working to implement a major analytics program will need to take a step back and refine its practices to ensure that the investment yields preferable results.