Data stopped being the sole property of the IT department the moment business users realized that technology existed that allowed them to feed themselves. If that wasn’t enough, the cloud came into vogue and mobile and social media use exploded, putting enormous amounts of data within reach of those who needed it most, without having to seek IT approval to find, store and use that data.
The Chief Data Officer
Today’s chief data officer may have roots in IT, but has enterprise-level responsibility for making sure that an organization’s data is being used as the asset that it should be. That means far more than understanding data plumbing and instead involves knowing the business, its technology and its people so that strategy can be infused with front-end thinking, rather than the perspective of IT’s traditional back-end role.
Few industries are feeling the effects of this trend more than media companies and advertising in particular. Keeping advertising clients happy today involves being able to know what’s happening, increasingly in real-time, within the customer, the customer’s customer and through the many fluctuating channels where media is purchased and consumed. There’s no time to move data around or to transform it before putting it to use. Data needs to be available immediately, from any source, as part of meaningful visualizations that allow end users to make critical decisions.
A Great Example
Sylvain Le Borgne is EVP of Data Platforms at Havas Media, one of the world’s largest global advertising, digital and communications groups. Working at the crossroads of significant media industry change, Borgne realizes that he needs to ensure wise utilization of enterprise data both within Havas and across their many customers globally. He has a laser focus on data analysis, on collaboration and efficiency.
Havas uses Alpine Chorus to meet their challenges for three primary reasons that Le Borgne describes this way:
“There’s no reason to sample data when we can use all of our data. We’re using Alpine Chorus for three main things. The first thing is that it allows us to do some very advanced data project management. From data discovery to visualization, it allows our team to collaborate but also to interact with our clients. Secondly, we love data flows and how it allows us to explain internally what we’re doing with data and again with our clients. It helps us to be extremely transparent about how we handle their data, what we do with it, and why the output is truthful and valuable. Lastly, it provides us with a layer of security by running in database on top of our data warehouse which allows us to install and run algorithms that can be developed by any data scientist team both internal and external, making sure we manage all data flows and processes and to store them in a reusable library.”
Le Borgne is not alone in needing a visual, end-to-end approach to analytic workflow or enabling predictive analytics across the enterprise — companies like Nike, Sony, and Barclays use Alpine’s products for prediction, simulation and optimization of their data, anywhere and everywhere that data is found. In-cluster analytics – running sophisticated analytical computations on Hadoop clusters or databases without having to move data around – is a rapidly growing approach to eliminate data movements and cut weeks and months from advanced analytics projects. Whether their title is chief data officer or not, a day in the life of a data-focused executive in the post-Internet, post-Hadoop world is tightly connected to the capabilities that a new generation of tech companies are bringing to the data scientist and business user alike.