News & Opinions
The latest news and insights from Hanley Wood’s outspoken experts and key thought-leaders throughout the residential and commercial design and construction industry.
5 Myths (and Truths) About Big Data
Stephanie Miller / ClickZ / September 16, 2013
“Big data” has become a catchall term for the vast amount of information generated by our digital lifestyles, and the analytics techniques for dealing with it all to improve marketing, products, and business intelligence. It’s become very fashionable to decry the value of “big data” for marketing, with many pundits and consultants calling it “no big deal.”
I believe in “big data” just like I believe in the power of all data to transform our lives. Just look at the powerful applications already emerging in healthcare, world hunger, global economics, and even for those for whom hockey is more important than life itself, sport competiveness.
The opportunity in marketing and business intelligence is just as strong. Our digital lifestyles generate a tremendous amount of personal and behavioral data – in fact, IDC estimates that by 2020, the number of commercial transactions on the Internet (both B2B and B2C) will reach 450 billion per day. McKinsey forecasts that demand for “big data” in the U.S. will create up to 190,000 high-paying jobs requiring deep analytical skills by 2018.
Used responsibly, all that data has a very meaningful impact on our lives and the economy. It’s time to clear up some of the myths surrounding big data and what it can do for marketers.
No. 1 Myth: “Big Data” Has a Universally Accepted, Clear Definition
Truth: Not so! Lots of people have trouble with what criteria to use in defining “big data.” That makes it easy to use in all kinds of contexts – including contexts where another term might be more appropriate. Size alone is not big data, but also scope and how it’s processed. Akamai analyzes more than 75 million events per day to better target advertisements.
To help you form your own internal definition, “big data” is usually thought of in these terms:
- The dramatic increase in the quantity of data available to be stored and analyzed in today’s economy.
- The inclusion of “unstructured” data (meaning it is non-numeric, “free-form,” qualitative data such as text, video, social content, and click-stream patterns), which requires sophisticated new data extraction and analytic techniques in order to be usable for business purposes.
- The growing role of automation in the use of data, e.g., creating and delivering marketing messages in real time.