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Companies must manage information, data quality to avoid risks

Paul Newman Archive

Information risk management and data quality checks are important components of successful big data strategies, according to Castlebridge Associates. These two factors help companies minimize inaccuracies in their databases, which can hinder their ability to achieve their goals and put them at risk for operational inefficiencies or even failure.

Companies need to view their data as an asset, similar to tools and equipment, that enables them to get jobs done, the source adds. If they let their tools break or fail to make repairs on equipment, they lose productivity, make flawed goodsand even put workersafety at risk. Data quality tools can ensure the materials they need to accomplish critical tasks are in the best working order.

Last year, many businesses launched big data strategies or set aside the resources to do so in the near future. Because of this push, data professionals have become highly sought after. Data analysts topped hiring managers' priority lists for 2013 on career site Dice.

"We're seeing big data is a big deal for hiring managers," managing director of Alice Hill told Data Informed in an interview. "For big data as a category, year over year job postings are up 335 percent. That's a pretty sizable increase."