We discussed in another article the key role of enterprise data infrastructure in enabling a culture of data democratization, data analytics at the speed of business questions, analytics innovation, and business value creation from those innovative data analytics solutions. Now, we drill down into some of the special characteristics of data and enterprise data infrastructure that ignite analytics innovation.
First, a little history – years ago, at the dawn of the big data age, there was frequent talk of the three V’s of big data (data’s three biggest challenges): volume, velocity, and variety. Though those discussions are now considered “ancient history” in the current AI-dominated era, the challenges have not vanished. In fact, they have grown in importance and impact.
While massive data volumes appear less frequently now in strategic discussions and are being tamed with excellent data infrastructure solutions from Pure Storage, the data velocity and data variety challenges remain in their own unique “sweet spot” of business data strategy conversations. We addressed the data velocity challenges and solutions in our previous article: “Solving the Data Daze – Analytics at the Speed of Business Questions”. We will now take a look at the data variety challenge, and then we will return to modern enterprise data infrastructure solutions for handling all big data challenges.
Okay, data variety—what is there about data variety that makes it such a big analytics challenge? This challenge often manifests itself when business executives ask a question like this: “what value and advantages will all that diversity in data sources, venues, platforms, modalities, and dimensions actually deliver for us in order to outweigh the immense challenges that high data variety brings to our enterprise data team?”
Because nearly all organizations collect many types of data from many different sources for many business use cases, applications, apps, and development activities, consequently nearly every organization is facing this dilemma.
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