For growth-minded organizations, the ability to effectively respond to market conditions, competitive pressures, and customer expectations is dependent on one key asset: data. But having just massive troves of data isn’t enough. The key to being truly data-driven is having access to accurate, complete, and reliable data. In fact, Gartner recently found that organizations believe poor data quality to be responsible for an average of $15 million per year in losses – a figure that can cripple most companies. Unfortunately, ensuring – and maintaining – data quality can be incredibly difficult. This is being exacerbated by the data architecture choices of an organization. Legacy architectures often lack the ability to scale to support the ever-increasing volumes of real-time data and cause data silos that slow the necessary democratization of data needed for an entire organization to benefit from.
