Most businesses are aware of the concept of big data. A fair number have begun using it. But big data hasn’t yet permeated all businesses and industries, because there are still many questions to answer. Why do we need it? Where do we get it? How to we get the answers we need out of it? Here are the most crucial questions to ask and get answers for before delving into a big data initiative. Continue Reading
You’ve read a lot about big data, and are probably familiar with a few ways it is used in the real world. For instance, most people are aware that big data is useful for marketing purposes. But big data is actually doing really cool stuff! Check out these interesting uses for data analytics. Continue Reading
Have you ever seen the American television show ‘Hoarders: Buried Alive?’ If not, it’s an interesting sight to behold. The show chronicles homeowners who keep everything they can get their hands on, regardless of its worth or significance. Some people hoard a particular item, such as milk cartons or bottle tops. Others just hoard anything and everything they can get their hands on: items bought from shopping channels, collectibles, old clothing, and even garbage.
The average data scientists commands considerably more than $100,000 per year. At top employers like Twitter and Facebook, that figure is well over $135,000 per year. Since there are so few of these elusive creatures, they can command high salaries and be incredibly selective in who they work for. That means that most businesses are left without. So, if you can put together the skill set necessary to become a data scientist, you too can make great money and work for the world’s top companies — or, you can simply stay and power your organization to new heights. Here are the skills it takes to become a data scientist. Continue Reading
Almost every business is aware of the growth of data and is trying to figure out ways to deal with it. Some organizations have begun a “big data initiative” while others are simply trying to determine the best way to store, process, and secure increasingly large sets of data. Continue Reading