Are you Human, or 01100001 01110010 01100101 00100000 01111001 01101111 01110101 00100000 01101101 01100001 01100011 01101000 01101001 01101110 01100101?
Most of you have just gone to search for a binary to text converter to decipher what all those one’s and zero’s mean. This is the very definition of what is Data (the language of machines) versus information (readable and understandable text / language for humans).
I could give you another cool statistic like 90% of the entire worlds data was created in the last two years, but we get it, we have amassed a staggeringly large amount of data across the globe and we have absolutely no intention of slowing down. In fact we started calling it BIG data, marvelling at how we have increased the Volume with the ability to store much higher capacities with higher densities, at how we have introduced a whole new Variety of data with new devices, and of course the Velocity of which we are creating this data, with 5G networks, and handheld super ultra mega pixel phones capable of taking 20 photos of your Instagram food per second. There was another “V” associated with big data that was mostly overlooked when “BIG data” became a buzz word in the tech space, and that was Value.
How do we determine value of our data? Can we get the machines to do it for us? Absolutely! That’s what all this A.I. and Machine Learning is meant to do as we have too much data being created, too quickly in too many places for us to keep track of, and let alone know what to keep, what to protect and especially, what to destroy!
How does data turn into information? You just did a minute ago with the one’s and zero’s above by pasting them into a binary to text converter, but what if you had literally trillions of them? As of 2020, 1.7MB of data is created every second by every individual, so that’s 14,260,634 Bits (14.2 million one’s and zero’s) per person…..per second.
You’d simply give up as a human after 1 second. Machines can do it much better than us. But even after you have turned all that data into information (readable by humans) you then have literally billions of years worth of reading to do. The information has yet to be classified and sorted into some kind of usable structure. So we need our machines to know how to sift through all the noise and make sense of it, then present it back to us in a nice and easy way so that we make immediate intelligent decisions of what to do with that data and what value it could hold to us.
Sounds nice doesn’t it? Kind of like a “nice to have” solution for our amassed data sets. The problem is that now, it’s no longer a nice to have, but a mandated requirement in most countries around the world to be able to know what information you have across your data repositories. With the advent of cloud, your data is now spread out across multiple data centres, multiple public cloud repositories (possibly across multiple countries) and even across multiple personal devices making this an increasingly difficult task, and believe me no one else is going to take responsibility away from you for this. The Cloud doesn’t “do your mess for less”, there is very much a shared responsibility model (always read the fine print).
This mandate typically comes in the form of information governance and compliance laws that have been created mostly for data privacy reasons. In some countries this is really well defined and categorised into personal information (such as your name, age, date of birth etc) and sensitive information (such as ethnicity, religious beliefs, health and criminal records and increasingly biometric and genetic information).
So we have a lot of data, in a lot of places, that we need to turn into information, then put that information into context, so that we can classify it and make sure we are compliant and avoid fines and legal action before we can even use the technology to do cool stuff with like finding new revenue streams. A lot of businesses and government entities have appointed chief data officers and compliance officers responsible for ensuring we are doing the right thing with our data and most of these folks I have spoken to can actually put a TCO price on the process it takes to find information and ensure compliance in one system, let alone spread across multiple distributed infrastructure and storage locations.
Data Driven Technology Evangelist, NetApp ANZ
Techie with Table Manners
My mission is to enable data champions everywhere. I have always been very passionate about technology with a career spanning over two decades, specializing in Data and Information Management, Storage, High Availability and Disaster Recovery Solutions including Virtualization and Cloud Computing.
I have a long history with Data solutions, having gained global experience in the United Kingdom and Australia where I was involved in creating Technology and Business solutions for some of Europe and APAC’s largest and most complex IT environments.
An industry thought leader and passionate technology evangelist, frequently blogging all things Data and active in the technology community speaking at high profile events such as Gartner Symposium, IDC events, AWS summits and Microsoft Ignite to name a few. Translating business value from technology and demystifying complex concepts into easy to consume and procure solutions. A proven, highly skilled and internationally experienced sales engineer and enterprise architect having worked for leading technology vendors, I have collected experiences and developed skills over almost all Enterprise platforms, operating systems, databases and applications.
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