Big Data is Meaningless
Big data is meaningless…without insights.
We recently attended the Big Data Innovation Summit in San Francisco, CA (#DataWest16), an event featuring 80 different sessions across two days.
Our #1 takeaway: Big data is meaningless without insights.
While big data was obviously the focus of the event, many of the speakers and sponsors emphasized the importance of retrieving insights from information that is available.
Let’s break down the statement “big data is meaningless without insights” even further and highlight how you can pull insights from all of the big data that is out there.
1. Don’t Let Your Big Data Lake Turn Into a Swamp
As illustrated in Reltio’s eBook, Watch Out for Crocs, there are great debates around what comprises a set of big data, and how you can get value from it:
“…a data lake will be a dumping reservoir, with no quality or form, eventually turning into a data swamp, without master data management (MDM) discipline to support reliable, crystal clear insights. Lack of reusable form, may also mean repeatedly going back to the well to re-interpret data.”
In other words: Don’t let your big data insights get lost in the noise (swamp).
One way to prevent this from happening is knowing the right questions to ask.
Here at Zignal Labs, we eat our own dog food. As we say, the single most important aspect of any Zignal Labs build is setting up the initial taxonomy. That is, asking the right and known questions.
While the answer is often 42, preparing a set of questions is crucial navigating through the “big data lake.” Similar to when you prepare a hypothesis for a science experiment, having an educated guess to what you think will happen is essential in uncovering key insights.
2. Leverage Modern Data Management
Another way to best leverage big data to your advantage is to ensure it is organized in an easy-to-sort-through manner (remember, you don’t have to be a data scientist to interpret big data).
Under most circumstances, combing through media traffic takes ages. One way of managing this is through breaking down insights into the most relevant information that has surfaced. For instance, at #DataWest16, our Zignal Command Center streamed the most popular tweets to stem from the conference conversation:
#DataWest16 – @striimteam trending on @ZignalLabs twitter monitor – also #streaming #integration – need one of these pic.twitter.com/8L1R9aB6OV
— Steve Wilkes (@BXCellent) April 21, 2016
As seen in the above photo, #DataWest16 content is visualized to easily and quickly see what matters most, expediting the interpretation process for all.
Big Data is Meaningless Without Insights; Insights are Meaningless (sometimes)…Without Action
Big Data >>> Insights >>> Action.
As explained by AirBnB’s Head of Data Science, Riley Newman, data must be “reliable, consistent, intuitive, and accessible” before any action can be taken. From there, you can make decisions that positively impact both your company and customers.
You have successfully prevented the “big data lake” from becoming a swap. You have uncovered critical insights by leveraging a modern data management system (like Zignal Labs!). And, you have ensured the data is “reliable, consistent, intuitive, and accessible” (per Riley Newman).
Now, it’s time to take action.
Action is a must. Action is essential. Action is critical.
Action may be issuing a press release, calling a customer, recalling a product or changing your marketing messaging. And, it is also important to note that action may be strategically choosing to do nothing — because the insights you derived were not worthy of action.
Are you asking the right questions? Are you pulling insights from your big data? Are you taking action?
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