Big Data Analytics

Simplify your most complex problems

From enterprise-wide process enhancements to increasing customer engagement, insights gleaned from big data analytics have quickly proven necessary to businesses looking to compete in the future industrial landscape.

Make better decisions

Enhance experiences

Mitigate risk & fraud

The ‘Five Vs’ of big data analytics

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.

Volume

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.

Velocity

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.”

Variety

Naturally, the variety of data sources results in a variety data types. There are three main categories of data:

  • Structured data is what you would expect to see in an excel sheet or a relational database. It comes in an organied format and manifests in rows and columns. This is the simplest way to manage information.
  • Semi-structured data may not reside in typical rows and columns, but it still has organizational properties that makes it easier to analyze. XML data is one example of semi-structured data.
  • Unstructured data requires its own method for storing and managing. It has no predefined data model and can come in a variety of formats. Think of videos, text, PDF files, and other media as unstructured data.

Veracity

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!

Value

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.

Big data analytics with Infomatics

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.