3 Shifts in the Modern Data Environment

The problem isn’t different—it’s just harder

Providing organizations with reliable data for better decision-making is an undertaking that has not fundamentally changed in decades. Despite massive technology advances and new tactics, the IT organization managing data infrastructure today still has the same overall mission: moving data from its moment of creation and making it accessible and understandable by decision-makers at the moment of need.

However, while the objective has stayed the same, the obstacles to successfully create and maintain a source of analytical truth within a business have become exponentially more difficult.

Perhaps the biggest hurdle in recent years within the modern data environment has been new sources of data that generate unprecedented amounts of output, often with very little (if any) structure. From clickstreams, server logs, and social media sources to machine and sensor readings, the onslaught of data from these channels has been overwhelming—literally. From an economic and performance point of view, traditional enterprise data warehouses (EDWs) simply cannot keep up with this data tidal wave.

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