Greg Villain is a network architect who is passionate about technology and innovation. He has worked for operators and internet service providers, and also start-ups, including Dailymotion and Netflix… always on the technical side. Today, he is responsible for product delivery at Kentik (opens in a new window), a Californian start-up that provides a network traffic analysis platform offered as a service to help customers better understand their data. As an expert in digital innovation and Big Data, Greg gives us his vision for this technology and how it can apply to companies. Here are his 8 tips that help demystify Big Data!
Put Big Data in its place!
Big Data is about analysing the behaviour of data to see how it is flowing within a company. It’s also a buzzword that covers different technologies. Technology shouldn’t be the goal in itself, rather it should be a tool to support your analysis.
Understand the potential of data…
Companies should realise that they can get many answers from analysing the data they already have access too: looking at activity history and understanding how it’s evolving, making future projections, simulating use cases. However, they will soon see that they need to collect new data and orchestrate new activity.
… and about Big Data
Big Data offers companies a recurring health check so they can improve operations or identify unprofitable tasks for example. It also enables them to model their activities, predict new transformations and simulate the impact of a new event.
Watch out, the main risk is designing “all-encompassing” Big Data projects and then constantly increasing their scope. This type of grand project, seen as “the magic solution to everything” never succeeds! On the contrary, it’s best to start with a small project, deploy it gradually and move on to the next one. Every step forward has to be immediately useful. The scale of the project can be increased little by little.
Recognise that you’re all concerned
Big Data involves all companies, activities and job lines within an organisation. Any business wishing to better control its activity can collect statistical, marketing or social data, or data that’s reported via industrial or IT systems.
It’s often said that a Big Data project has to come from the top. This simplifies how it’s adopted. You shouldn’t block projects that start within teams or that are not initially part of the top-down business strategy. When Cloud technologies first emerged, we saw IT managers discovered that their developers were using resources in the Cloud to gain agility… so they defined a dedicated policy afterwards.
In the same way, Big Data can come from people out in the field: it’s up to the company to capitalise on these successes and accept that employees can influence the technical strategy.
As previously noted, Big Data isn’t the end goal in itself. It has to have clearly defined objectives that are communicated within the company to avoid disappointment.
Bring the right skills together
A company can explore the possibilities of Big Data via an outside provider. If it becomes a strategic issue it can then be internalised and new skills can be recruited in. These skills are still rare, so some companies are going ahead and hiring talent even if they don’t have an immediate need, simply to maintain their level of expertise… and then they’re trusting these employees to bring in future alternatives.
Greg Villain © DR