A great definition of Big Data is “our ability to collect and analyze the vast amounts of data we are now generating in the world” stated Bernard Marr in a recent article, but he also references that ‘Big Data’ is the biggest buzzword in technology right now. A much more complicated definition using the 3Vs of big data is high Volume, high Velocity, and high Variety information assets that require processing to enable enhanced decision making, insight discovery and process optimization.
Big Data Snapshot
A simple view of Big Data is Facebook’s rollout of 15 second videos on Instagram. Kevin Systrom, CEO and cofounder of Instagram was quoted earlier in the year saying that “Instagram isn’t necessarily a photo company or a communication company; as I like to say, we’re also going to be a Big Data company.” Prior to the video introduction, Instagram had 130 million monthly users that had uploaded 16 billion photos. The Big Data snapshot consisted of friends, favorites, hashtags, location data and over 1 billion ‘likes’ added every day.
Greta Roberts, CEO of Talent Analytics Corporation, was recently asked about the hype of the term Big Data and if it was getting old. “That’s what we’re starting to hear,” said Greta. “Big data continues to be extraordinarily important. We’re seeing some backlash in focusing on value over the long term.” Evaluating data in the long term is looking at the historical shelf life of Long Data over a lifetime as opposed to a short term snapshot of Big Data. The historical value of Long Data, 5 to 20+ years, provides a much greater potential of learning about people rather than 5 years or less but the amount of information that is stored even 2 years or older is much less.
Long Data 15 Second Video
Instagram unveiled the 15 second video feature on Thursday, June 20th and in the first 8 hours there was more content, or should I say Long Data, uploaded than the previous YEAR of uploading photos. After the first 24 hours there were over 5 million videos uploaded. Combining 15 seconds of video data with the social data of friends, favorites, hashtags, location data and ‘likes’ changes Instagram from a Big Data Company to a Long Data company. The average number of hashtags per pic on Instagram is 3 to 4 but a person can easily speak and understand 40 words in 15 seconds. Simply using speech recognition technology to auto-hashtag can determine a person’s accent, language and mood by crunching the data on 40 spoken words and most importantly get a much deeper view of the context of the video opening up the door for individualized ad targeting.
One year ago Instagram hadn’t made a profit, had a valuation of $500 million with 30 million users and Facebook purchased the photo sharing site for $1 billion. Currently, Instagram has 130 million users but still hasn’t turned a profit. The 15 second Long Data being uploaded vastly improves Instagram’s leverage to provide targeted and individualized ads for advertisers. Companies are also joining in as 59 of the top 100 brands now have accounts compared to 40, one year ago.
Whether Instagram is considered a Big Data or communications company, it is definitely not just a photo-sharing site anymore. Instagram is now packed with Big Data, Long Data, Social Data and Video Data, giving Facebook all of the data they need to monetize their traffic and get a return on their $1 billion investment.