As the manifestation of technology that uses prior observed data to train computers to predict future outcomes, machine learning is often framed as the end-game, putting traditional statistical modeling in the shade. But that’s not where it belongs.
Truth in measurement has never been more important than it is today. Therefore, truth is our only agenda. But arriving at that truth has never been more complicated. While many view big data as a panacea for measurement in a digitally rich world, we know it’s not that simple.
For much of the big data era, businesses have held the power. With immense grassroots advocacy and legislation such as the EU’s GDPR and the California Consumer Privacy Act, the pendulum of power has swung toward consumers.
While some may equate data science as pulling rabbits from hats, this thinking is misguided. But this is largely because the vast majority of people don’t understand the workings of data science.
It’s not practical, feasible or necessarily a good idea to try measuring consumer behaviors by engaging with as many people as possible. That’s where sampling comes in.
Data science is the field of study that focuses on obtaining insights and information--anything of value--from data. Data science, when applied to different fields, can lead to incredible new insights for all business units.
At Nielsen, we believe that our panels make our company stand out. We devote a great deal of time and resources to ensuring that our panels produce high-quality data. By combining big data with smaller data sets from carefully chosen and measured households, we believe that we provide a higher...
You don't have to look far to see rapidly growing or already mature 'disruptors' in retail and manufacturing, but the long tail of market disruption goes way beyond that in today's age of consumer disloyalty.
The data generated by our day-to-day activities can help brands and marketers understand consumer needs and drive growth for their businesses. But first, they need to make sense of all the data.
The cloud can save enterprises time and money while improving agility and scalability, all of which are important factors you need in today’s competitive landscape.