Digital Landfill

The following are a few tips from AIIM analyst Doug Miles about getting started with Big Data and Big Content.  The excerpt is from our Industry Watch -- Big Data - Extracting Value from your Digital Landfill.  Downloads are free.

Although the term “big data” is surrounded by hype, 70% of respondents to AIIM’s new research “Big Data meets Big Content” envision a “killer app” that would be “very useful” or “spectacular” for their business. They understand that curating and analyzing content can enable effective decision making in organizations of any size and any industry. And yet, many cite business and technical issues that are holding them back from leveraging the incredible power of data.

Here are Doug's recommendations:

1. Ask blue-sky questions of your business such as “if only we knew…” or “if we could predict…” or “if we could measure…”  Consider how useful that might be to the business before thinking about how it can be done or at what cost.  
2. Play those questions off against the data you already have, data you could collect, or data that you could source elsewhere.  
3. Include in your thinking structured transactional data, semi-structured logs and files, and text-based or rich media content.  
4. Incoming communications from your customers, outbound communications to your customers, and what customers (or employees) are saying about you on social sites can all be useful for monitoring sentiment, heading off issues and analyzing trends.
5. Consider high volume streams such as telemetry, geo-location, voice, video, news feeds, till transactions, web clicks, or any combination of these.
6. If your content is currently digital landfill spread across disparate file shares and content systems, consider how this could be rationalized prior to any big data projects.
7. Content access for both search and analytics, and if necessary, content migration to dedicated big data storage, can be facilitated by unified data access products.
8. Don’t be tempted to rush into in-house developments or specific point-solutions without considering wider, more universal analytics platforms.
9. Consider SaaS and cloud deployment as a faster way to acquire experience and focus activity.  
10. Big data is much more about the breadth of the analysis and the insights that can be achieved than it is about the size of the data and the underlying database technology.

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Here are a couple of other resources that might be of interest:

Have you downloaded by new e-book?  It's called OccupyIT: A Technology Manifesto.