Eight Big Data Mistakes and How to Avoid Them


The big data market will trigger $34 billion in IT spending this year, according to a Gartner forecast. Most of that investment will pay for upgrades of traditional systems to better gather and analyze data coming from Website traffic, social networks, sensors and customer interactions. But are organizations getting the most out of their investments in big data? Apparently not. The recent book, Too Big to Ignore: The Business Case for Big Data (John Wiley & Sons/available now), reveals that companies still face a steep learning curve. Author Phil Simon writes that both managers and employees can get overwhelmed by big data, to the point at which they fall into the following classic traps that distract them from what should be the core goal of any project: to more effectively achieve business-benefiting strategies. By staying focused on what really matters, he contends, you and your work colleagues will get the most out of the vast volume of information out there. Simon is a speaker, author and tech consultant, and has been featured on NBC and CNBC, among other media outlets.

Eight Big Data Mistakes and How to Avoid Them

Try to Import, Load and Link All the Data  That is cost- and time-prohibitive. It's best to zero in on the most useful data to yield better analytics.

Eight Big Data Mistakes and How to Avoid Them
Dennis McCafferty is a freelance writer for Baseline Magazine.

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