The students in the USA are eligible for school bus transportation if they live beyond a particular radius of the school. The yellow school buses are largely unchanged since their debut in 1939 even though their routes are getting more and more complex in the past 80 years. This is because of the number of students, schools, road systems and the system of rules.
It is that time of the year when you take a look back and take an educated guess on what is going on to be in the very near future of data analytics. There is no doubt that in 2018 analytical industries will be not just hot but also rapidly changing. Here are the top trends that will prevail within the New Year.
Believe it or not, big data is the new gold. Poured into the fuel tank of the automotive industry, it is transforming itself into growth booster, creating new services and users` benefits. The core focus of big data and cars is not just autonomous vehicles, it is about humans and how they use their cars on an amazingly granular level.
Well, 2016 is all history and it is time to focus on the near future. That’s why we decided to share our point of view on what is going to be hot in data analytics world in 2017.
Wholesale distribution business is generating a great amount of data which is including at least thousands of products, quantities, pricing, customers, and inventory, just name it. This simple fact makes them really suitable for data analytics modeling in order to solve specific business problems or to gain efficiency within already existing processes. In this blog post, we are highlighting just 5 of the potential benefits that a wholesale business is capable of extracting from modern days data analytics.
Since we`re into all things big data & analytics we are nothing less than tempted to share our thoughts on big data myths. And smash them as hard as we can. This way we`ll feel like MythBusters, at least for a minute.
Data analytics has huge potential to predict and forecast future performance and this is already proven in big companies full of historical data. With the declining cost of computation, the mathematical wizardry of predictive data analytics is already at arm`s length for small and medium enterprises lacking the resources of the big players.