Traditionally, big data was defined by the 3 Vs: volume, velocity and veracity. As the big data analytics field grew, veracity and value joined the list to make up the 5 Vs.
This is where we put the "big" in big data. The amount of data in the world is growing at staggering rates, with the world's global data sphere expected to reach 125 zetabytes by 2025. Every video uploaded, MRI conducted, timesheet filled or other in adds to the data produced.
Data doesn't just magically grow big. As more information is accumulated from computers, IoT devices, mobile phones, online applications and other sources, data grows until it reaches the volume expected to become "big."
Naturally, the variety of data sources results in a variety data types. There are three main categories of data:
Big data analytics efforts are only as good as the data's quality. Establishing data veracity requires conversations about how complete data is, how appropriate the sources are, how accurate the information is and more. Even data's relevance contributes to its overall veracity!
This is the crux of all an enterprise's big data analytics efforts. An enterprise must know why it collects data and how it plans to transform it into business value.
At Infomatics Corp, we create systems that enable our clients to reveal the patterns and trends throughout your enterprise that impact your business priorities. With enterprise-wide analytics platforms like Dataiku and expertise in tools and processes used across the data analytics industry, Infomatics is ready to serve your data needs.