Users' Perceptions of Big Data
The report, which aimed to record how users see the potential benefits of big data analytics, explored some of the more practical and popular applications, as well as some of the issues that are holding users back. Overall, people are excited, but still need a lot of help connecting unstructured and structured datasets. Here are a few of the key findings:
- 61% would find it “very useful” to link structured and unstructured datasets. Currently, unified data access across content repositories is a struggle for most respondents.
- 56% would find it “very valuable” or “hugely valuable” (18%) to be able to carry out sophisticated analytics on unstructured content -- particularly pattern analysis, keyword correlation, incident prediction and fraud prevention.
- For 70% it’s “harder” or “much harder” to research information held on their own internal systems compared to the Web. A lack of standardized analysis tools is given as a significant issue for improving business intelligence.
There is no shortage of data, only a means to process and make sense of it all. But that shouldn’t surprise you. After all, unstructured content is one of the biggest battles facing the enterprise. Just because Big Data becomes a buzzword doesn’t mean business knows what to do with it.
A Uphill Battle With Big Data
Slowly but surely, influence is growing. The AIIM report showed that:
- 9% of organizations are already making use of publicly available or open datasets to extract longer-term business intelligence or solve problems, and 42% are keen to do so. There is a similar willingness to link to external subscription datasets.
- 9% of organizations have seen value in analyzing their output print-streams, and 24% would like to do so. A further 33% had not previously thought about the possibility of mining printouts and statements for financial trends.
Despite the 9%'s ability to put big data to big use, most are struggling to organize their content. Without strong business intelligence models in place, or security checkpoints, or a basic understanding of what you can actually do with your data, it’s a slippery slope to doing nothing.
- The terms “content analytics”, “unified data access”, “semantic analysis” and "sentiment analysis” are generally understood by around half of the survey respondents. Specific big data technologies like Hadoop, NoSQL and Map Reduce are unfamiliar for three-quarters of those responding.
- There is some crossover of priorities between search and analytics, but most users see equal value in both. 55% of organizations currently have neither; only 8% have both.
Big Data vs. Analysis
So it seems that Big Data analysis comes down to two major issues. Companies either have too much data/not enough analysis, or they have the right tools, but they don’t have their data organized. Getting everyone on the right track will be a challenge, but not impossible. It requires a commitment to the right data technologies, finding the right people and getting serious about your content.
To get there, AIIM recommends asking what it calls “blue-sky questions” such as “if only we knew…” or “if we could predict…” or “if we could measure…” Considering how useful that might be to the business is more valuable than becoming overwhelmed about how it can be done or at what cost.
Additionally, for organizations with content in a digital landfill spread across disparate file shares and content systems, AIIM recommends considering how it could be rationalized prior to any big data projects. Most of the solutions to big data don’t require more technology or bigger budgets. They require a thoughtful approach to what content you currently have and a strategic plan for how to gain access to it, share it and analyze it so that it can add value to business goals and outcomes.
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