What is the first thing that comes to your mind when you hear the word ‘blob’? Without any context, it sure sounds like an obscure, mystic object you are playing against in a game of Minecraft. I can almost bet we have all seen the horrifying manifestation of our definition of BLOB on the web somewhere. However, in the world of data, blobs are extremely powerful and have transformed the way data is represented and transmitted.

Photo by Michael Dziedzic on Unsplash

Anything and everything that can represent information about an entity is data. Our name, address, cell-phone number, genetic-information, family-tree, all represent information about us…

Photo by Wolfgang Hasselmann on Unsplash

Machine Learning on Cloud is becoming the new Black — lovable, but a trend which needs significant thought and research. ML PaaS is one of the most desirable and also the fastest growing trend in the public cloud space. Almost every cloud provider is constantly trying to improve their ML platform by offering a more comprehensive solution for Developers, Data Scientists and DevOps Engineers. But a big problem with ML on Cloud is how complex and costly these solutions can become as a company scales. However, Microsoft has built a very robust ML PaaS System.

In part-I of this series, we jumped straight into a big blob of … BLOBs. That was quite a journey! In part-II of this series, we will talk about why and where to use BLOBS.

Photo by Artem Verbo on Unsplash

Just a quick refresher course on blobs:

  • BLOB is an acronym for Binary Large Object.
  • BLOBS are huge chunks of raw binary data.
  • A BLOB can be made of several other “constituent” BLOBs.
  • A BLOB can be accessed via a special URL called a BLOB URL.

When we talked of blobs, we learned that blobs are binary representation of any and all kinds of data…

Shruti Chaturvedi

Woman in Tech | Cloud, DevOps Engineer | Deep Learning fanatic | https://www.linkedin.com/in/shruti-chaturvedi-developer/

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