The Most Influential in Customer Service

Wrapping my head around Big-data problem

Last week at a meetup in Boston, I was told to give my 2 cents on big-data with an analogy. Idea is to make the problem understandable even by a 12 year old, and that made me think. So, based on what all I have gathered, and seen from my experience, what exactly is big-data and is there a simple analogy to explain it to people.

Here is my 2 cents: wait for it.. Wait for it.. “Your Big-data problem is like your garbage problem”.

Garbage:

Things that we don’t know what to do with or how to use.

Things that we have not used for ages.

Things that we have used enough and found it is of no further use.

Someone else’s garbage that might have something that is of some use to you.

Big data includes:

Data sets that we capture but are not sure what to do or how to use.

Data-sets sitting out there that has not been monitored or used for ages.

Data-sets that comprise of information that we think are sufficient for helping us make business decisions.

And Data-sets captured by others that might be of some strategic relevance to us.

I have been talking with a couple of fortune 100 organization’s big-data team members and asked about their big-data initiatives. Findings were clear - that is, big-data is not clear enough. Let me try to explain what is going on:

Say, you have tons of garbage that you are concerned about and you want to make sure nothing useful is thrown out. Now, you are handed a shiny glove(tools) to help you help yourself by digging through your data. Is this picture looking right? This is what most of the companies are struggling with. Sure, they can deal with their garbage but it’s not their core competency. Your core job is not to filter through that garbage. This puts you at high risk of failing.

Very few smart companies are doing it right by calling experts to look at their big-data and help them with cleansing. This helps them do it more efficiently. You save on trial-error cost; you get to best practices first and adopt it in your core sooner.

So, it is important for companies to realize who best can serve as their Waste Management professionals. It won’t even hurt if a redundancy is infused to help get to best solutions faster and minimize failure risk.

Therefore, garbage is the best analogy I have found to explain big-data problem and how to resolve it. Surely, I am all ears to listen to better analogy that simplifies the meaning and sheds appropriate light into this issue.

Stay tuned, I will be posting a playbook for helping companies get started with resolving their big-data problem faster and cheaper.

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