When big data first became a highly popular technology trend, discussions in boardroom meetings related back to volume and variety, as companies were viewing the analytics solutions as viable candidates to help them make sense of the complex and massive information assets. However, this only takes care of two out of the three descriptors used to characterize big data, with the third being velocity.
As big data and advanced analytics have matured, more businesses are beginning to recognize that velocity might simply be the most important part of the equation, as evidenced by a greater interest in fast data. After all, the whole point of analytics is to get predictive and prescriptive insights before competitors can, allowing the firm to more fluidly navigate new trends and get an edge over others in their field.
Notes from a pro
Forbes recently published a blog post that explained some of the pathways companies will likely have to take to achieve fast data. The source argued that one of the best explanations to date on what fast data involves came from consultant Randy Bean who was interviewed in a recent article published in The Wall Street Journal.
"In contrast [to big data's historical focus], Fast Data is about "data in motion" and immediate response and action," Bean told the WSJ, according to Baldwin. "It's the velocity component of the Big Data triad. While large corporations have been focused on the variety and volume of data they manage, Fast Data applications are being developed to seize on the opportunities presented by data velocity."
Baldwin then went on to argue that the volume and variety components of big data are going to remain in their current forms for years to come, as there will always be a strong set of resources businesses can use to acquire valuable information. However, he noted that slowing down sources that are currently generating data too quickly could be an issue.
Getting it right
Fast data could represent the next level of performance in analytics, but it will take effort. Companies struggling to achieve fast data in such a way that yields accurate and timely insights might want to consider leveraging the services of a professional solutions provider, as this will leave the more difficult aspects of the projects to the professionals.
At the end of the day, investing in analytics is becoming more critical, and putting resources in the right places is vital.