Cloud Computing

A project under development with a semiconductor manufacturing company can monitor the detection and classification of failures in real time. With stream computing, failures in chips being manufactured are detected in minutes rather than hours or even weeks. Defective wafers can be reprocessed and, more importantly, adjustments can be made in the manufacturing processes themselves, in production.

Additionally, we may think that cloud computing is also a booster for Big Data because public clouds can be used to support huge amounts of data. The cloud's elasticity characteristics allow us to power virtual servers on demand only at the time of processing these data.

Anyway, Big Data is knocking on our doors. Its potential is not yet fully recognized, but we already see clear signs of this importance to solve diverse problems such as socioeconomic issues and even epidemic prevention.

As for companies, Big Data opens up a new and still unexplored territory. We lack knowledge, experience and even professional expertise. It starts talking about new functions as data scientists, but it is inevitable that the CIOs have to put Big Data on the screen of their radars.

The opportunities that the five "V" s bring can not and should not be wasted.

The other day I wrote a post with a simple formula to conceptualize Big Data. It is equal to volume + variety + velocity. But I usually add two more V's to this equation: veracity and value. Let's detail these topics a bit more.

Volume is clear. We generate petabytes of data every day. It is estimated that this volume doubles every 18 months. Variety also, since these data comes from structured (now minority) and unstructured systems (the vast majority), generated by emails, social media (Facebook, Twitter, YouTube and others), electronic documents, Powerpoint presentations, instant messages, sensors , RFID tags, video cameras, etc.