What is Big Data? What does it take to use Big Data to deliver Big Insights?
The volume, velocity and variety of data is high: A petabyte is one quadrillion bytes, or the equivalent of about 20 million filing cabinets’ worth of text. An exabyte is 1,000 times that amount, or one billion gigabytes. For many applications, the speed of data creation is even more important than the volume. Real-time or nearly real-time information makes it possible for a company to be much more agile than its competitors. Big data takes the form of messages, updates, and images posted to social networks; readings from sensors; GPS signals from cell phones, and more. Many of the most important sources of big data are relatively new.
The data available are often unstructured—not organized in a database—and unwieldy, but there’s a huge amount of signal in the noise, simply waiting to be released. Analytics brought rigorous techniques to decision making; big data is at once simpler and more powerful.
1. Pick a business unit to be the testing ground. It should have a quant-friendly leader backed up by a team of data scientists. 2. Challenge each key function to identify five business opportunities based on big data, each of which could be prototyped within five weeks by a team of no more than five people. 3. Implement a process for innovation that includes four steps: experimentation, measurement, sharing, and replication. 4. Open up some of your data sets and analytic challenges to interested parties across the internet and around the world.
What do the opportunities presented by Big Data suggest in terms of the skills and training that will be needed by future marketing analysts?
The future marketing analysts should understand key performance indicators (KPIs) which drives consumer behavior. Market research usually investigates on