Surprising new stats on big data hurdles

The big data market has diversified significantly in the past five years or so, driven by more specific and robust demands among corporate users and a massive rise in investments targeted at advanced analytics capabilities. However, the news has not been all good, as it has become clear that many firms are experiencing significant setbacks in their big data strategies due to poor planning, a lack of expertise in-house and other issues that can indeed be quelled.

With support from a firm that can help out with some of the more complex aspects of big data, including preparation, integration, collection and optimization, these types of problems can be adequately mitigated a bit more proactively. A new report indicated that data preparation is actually the biggest dilemma companies are facing, and this is likely the result of a lack of awareness toward the necessity of these processes in an analytics strategy.

Significant setbacks
Smart Data Collective recently reported that access and integration have long been challenging matters that hold firms back from enjoying optimal analytics performances, and were cited by nearly two-thirds of respondents to a survey as significant concerns. However, the latest research indicated that these types of issues have been mitigated a bit more thoroughly, and the hurdles are shifting to impact the front-end aspects of big data management.

Data preparation is holding companies back from optimal analytics performances. Data preparation is holding companies back from optimal analytics performances.

According to the news provider, roughly 40 percent of companies are struggling to get a handle on data preparation before the information is sent to professionals for analys‚Äčis, representing the most common setback today. Data access, predictive models, and exploration were also involved in the research, but the source noted that they are not nearly as widespread of challenges as preparation.

Looking a bit further into the study, Smart Data Collective pointed out that the use of “convention systems” for analytics-related information management strategies are falling by the wayside, being replaced by far more advanced tools and frameworks, including in-memory databases. This is no doubt fueling a bit more complexity and difficulty with respect to data preparation given the relatively foreign formats involved that have not been seen by the average IT department quite yet.

Mitigating setbacks
Because of how quickly companies are beginning to invest more in big data analytics, the preemptive avoidance of these types of hurdles should be a priority in the coming years, otherwise returns will almost certainly suffer as a result. Managed service providers are already beginning to provide more intuitive and low-touch options for core analytics needs, including data preparation, and should be considered when in need of support for these matters.

Self-service data preparation, for example, can help companies to move fluidly through their analytics programs without having to staff an IT department with new, experienced professionals who specialize in these processes.