The idea of "big data" could conjure up Turing-like images of massive cloud storage centers humming away in a dessert. It's true that up to this point, computing power has been a barrier to analytics, research, and the exploitation of big data. It takes a lot of computing power to process increasingly complicated and elaborate data sets. Companies, therefore, must make choices about which data to analyze, and the extent to which they can dive in. An incomplete view of your analytics can lead directly to false conclusions.
Fortunately, there are options. Advancements in analytics and big data software now mean that people who are interested in using big data to their advantage can run interactive queries on commercially-available laptops.
How "BIG" is big data?
The key to understanding any sort of analytics or data is not the quantity, it's the quality that can be obtained from the quantity. Very large data sets allow us to determine a correlation between two seemingly uncorrelated things. But big data sets also give us a whole lot of noise, and analysts can waste a lot of time trying to correlate two things that don't relate to each other.
If we define "big" data as all of the data you can possibly get your hands on -- integrating every data source you have -- then you will always require massive computing power, and you will spend a lot of time chasing dead ends. But it will certainly be big. The biggest companies in the world who have the time and manpower to chase all of these ideas can make some nice infographics. However, a lot of that information probably won't lead to actionable insights.
If we define "big" data as being able to use as much data as you need to derive actionable insights for your company to improve your product or bottom line, then we're actually talking about a much more manageable amount of information, one that can easily be processed on a laptop, thanks to advances in software like BigObject Analytics. Reducing the dependency on running complicated distribution systems for big data analysis means more flexibility for companies, and they can get a wider view of their overall analytics.
Big Data, Small Laptop
Data and analytics are about insights. Here at BigObject we believe that the ability to make cross-connections is the key to turning information into knowledge. In order to calculate connections and correlations, we developed something called "Cross-Link" that drives our BigObject Analytics platform. Data is captured and structured in BigObject in a hierarchical way that users can quickly have a "view" of what the data looks like in different dimensions. The language used in BigObject Shell is similar to SQL statements, which is the most commonly used query language. And it all happens on your laptop, making it possible to process billions of lines of data. Imagine that!
BigObject uses Docker to as the primary delivery method, meaning that it is kept up-to-date no matter which operating system you're running.