Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

January 15, 2016

Data Is Not The Same As Truth:…

Filed under: BigData — Patrick Durusau @ 7:53 pm

Data Is Not The Same As Truth: Interpretation In The Big Data Era by Kalev Leetaru.

From the post:

One of the most common misconceptions of the “big data” world is that from data comes irrefutable truth. Yet, any given piece of data records only a small fragment of our existence and the same piece of data can often support multiple conclusions depending on how it is interpreted. What does this mean for some of the major trends of the data world?

The notion of data supporting multiple conclusions was captured perhaps most famously in 2013 with a very public disagreement between New York Times reporter John Broder and Elon Musk, CEO of Tesla after Broder criticized certain aspects of the vehicle’s performance during a test drive. Using remotely monitored telemetry data the company recorded during Broder’s test drive, Musk argued that Broder had taken certain steps to purposely minimize the car’s capabilities. Broder, in turn, cited the exact same telemetry data to support his original arguments. How could such polar opposite conclusions be supported by the exact same data?

Read Kalev’s post to see how the same data could support both sides of that argument, not to mention many others.

Recitation of that story from memory should be a requirement of every data science related program as a condition of graduation.

Internalizing that story might quiet some of the claims made for “bigdata” and software to process “bigdata.”

It may be the case that actionable insights can be gained from data, big or small, that your company collects.

However, absence an examination of the data and your needs for analysis of that data, the benefits of processing that data remain unknown.

Think of it this way:

Would you order a train full of a new material that has no known relationship to your current products with no idea how it could be used?

Until someone can make a concrete business case for the use of big or small data, that is exactly what an investment in big data processing is to you today.

If after careful analysis, the projected ROI from specific big data processing has been demonstrated to your satisfaction, go for it.

But until then, keep both hands on your wallet when you hear a siren’s song about big data.

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