Overcoming The Lacks Of Big Data Projects

Sameer has 22 years of strategy consulting, equities trading and industry experience. Prior to co-founding The Smart Cube, Sameer spent over a decade with Accenture's Management Consulting practice. He is also a Fellow of the Aspen Global Leadership network, a group of entrepreneurial leaders with a focus on creating a better society, based in Aspen, Colorado.

- Sameer Walia

Big data is characterized by a large volume of data that inundates a business on a daily, hourly and even minute-to-minute basis with very high velocity as it is generated and accessed at higher speeds. Furthermore, it is no longer just structured data, but also includes unstructured data in the form of text, videos, voice, images, etc. But it’s not the amount or velocity of data that’s important. It’s what organizations do with the data that matters. And this is where our company comes in. The Smart Cube can help – through a mélange of services, products and solutions – in collecting, managing and analyzing large volumes of data to facilitate better business decisions.

There are main challenges that revolve around notso-well-defined Big Data project objectives such as lack of preparedness at the business end to undertake a project, and an absence of the appropriate skill set in the business. Most of the organizations are still setting themselves up for big data – deploying their Hadoop stacks and what not – consequently they are in a transitionary phase where it’s difficult to access certain data sets. An agile methodology is very helpful in a big data project, as it ensures we work on bite-sized chunks in each sprint. Specifically, with respect to Agile, we get held-up by external dependencies – not all teams outside the project world would have adopted an agile framework and therefore these impact timelines.