Are you as tired of the term “big data” as I am? Here in Silicon Valley, it is everywhere you turn and a new definition is offered in every discussion. In working with over 350 eCommerce brands in my time at Baynote – one thing is for sure: Big Data is less about bringing large amount of data together and more about what you do with it.
What does big data aim to accomplish?
It seems to me that the goal of big data is simple: gather and synthesize as much information as possible (or as needed) to make better, more informed business decisions. Sounds simple right? If we look at ecommerce as one domain where big data is already being used to better understand customers, there are some large hurdles that prevent many retailers from ever getting to the promised land of big data insight.
Specifically, what are the hurdles?
First is the issue of legacy systems. While lots of retailers have re-platformed in recent years, many still face the challenge of upgrading legacy systems built in a time before distributed, open source database technology. Given the business models of most retailers, there is little time, budget and people resource for building big data infrastructure in addition to re-platforming. And if you are not Apple, Walmart, Nordstrom or BestBuy, you probably don’t have your own think tank full of data engineers, analysts and architects. That’s where software solutions companies come into play. The onus is on those of us who have built big data infrastructures and already have teams of data science experts to make these technologies available to business users, in a more business-friendly way.
In the end, it’s about accessibility and usability. In the case of retail, we are combining the talents we possess in the big data arena with our deep knowledge of eCommerce personalization in order to make the benefits available to the other 99% of retailers who need it, but cannot afford to build it themselves. Again, the data is only valuable if you do something with it.