Introducing the Big Data MOPS Series

Big data – or whatever you prefer to call it – is a game changer. And not to mince words: If you’re not using big data to improve your business – e.g., revenues, profits, operational efficiencies, decision making, etc. – then don’t do big data. It’s not worth the time, money or hassle. 

Big data – or whatever you prefer to call it – is a game changer. And not to mince words: If you’re not using big data to improve your business – e.g., revenues, profits, operational efficiencies, decision making, etc. – then don’t do big data. It’s not worth the time, money or hassle. 

Big data is not new. There’s no question that big data has received a lot of center stage attention and fanfare the last few years. Ready or not, this new age of big data is forcing organizations to look at their data – big and small, existing and potential – in a new light. But as disruptive and/or exciting as this may sound, we can’t afford to fall into the trap of believing that the “data” in “big data” is something new. Because it’s not.

Consider these “big” data sources: email, photos, videos, spreadsheets, PDF documents, satellite images, social media data, blogs, audio files, GPS data, call center transcripts, open data, RSS feeds, clickstream data, and the list goes on. Are any of these data sources new? Of course not. We’ve been collecting this data for many, many years. 

So what’s new? Why all the hype? The simple answer is technology. We now have big data technology (much of it being open source) that allows us to store all this data at a fraction of the cost and process it in a fraction of the time – as compared to our existing, traditional systems. Not only that, we can combine, fuse, and integrate all this data – regardless of volume or format – like never before. As a result, we are able to get more creative with our data analysis, discover more insights, answer more and better business questions, and subsequently, improve the bottom line for our organization. 

MOPS is not new either. If we want to figure out how big data can help our organization make faster and better business decisions, then it’s important to understand the evolving discussion around the following interrelated data topics: Monetization, Ownership, Privacy and Security (or MOPS, for short).

Even though these data topics aren’t new, we’re seeing big data escalate this MOPS discussion from the backroom to the boardroom in many organizations. Consider these questions, for starters:

• On monetization: If data is deemed a corporate asset, what are we doing to monetize it?
• On ownership: Beyond our corporate data, who owns the “big” data we can now pull in from the outside? If we don’t own it, can we still monetize it?
• On privacy: What are we doing to protect the privacy of our customers’ data? Are we using “big” data to expose more about our customers without their knowledge, understanding or permission?
• On security: What are we doing to secure our data from corporate data breaches? One breach alone could bring an organization down to its knees. Permanently. 

In this new age of big data, these questions can no longer be confined within our business groups and/or IT. These are executive-level questions, and if they’re not, it behooves us to find out why.

An invitation. The MOPS questions I posed above barely scratch the surface of this evolving, complex and somewhat messy discussion. A single blog post – even a long one – wouldn’t do the discussion justice. That’s why it’s being addressed in a series of blog posts called The Big Data MOPS Series, courtesy of Smart Data Collective.

I will be leading this discussion, and I invite you to join me to share your own perspectives, ask questions, or simply read along. As the series develops, I will focus on current “breaking” events that are relevant to this MOPS discussion. 

It’s a big data world out there. Now let’s be safe.

Coming up next in the series:

• 60 Minutes, You Got It Wrong. Data Brokers Aren’t Evil.
• Who Owns the Data? Well, It’s Complicated.
• The White House Recently Completed a Study on Big Data Privacy. Do You Care?
• If You Think Data Security is IT’s Responsibility, Think Again.