Behind the Buzzword: Big Data

October 20, 2017   //   Business Intelligence,

Welcome to part three of our five-part Behind the Buzzword series, where we discuss the definitions and practical application of some of the latest tech industry buzz-phrases in the world of Data Analytics.

Last week we looked at Artificial Intelligence. Today, let’s look at the next big buzzword in the series – Big Data. What is big data? Why is it so important? Is there “little data?” Let’s take a closer look!

Big Data, Big Questions

Big Data is a term that means different things to different people. To many, big data is a key to information and insights that normally wouldn’t be accessible to them. Having the most accurate information available allows for better decision making. Can we use this information to predict poverty? Consumer behavior? Health issues in our patients? The possibilities are endless. The challenge is having the tools and knowledge to obtain and analyze big data to begin with.

Simply put, big data refers to extremely large data sets, inside and outside of your company, that can be analyzed to reveal trends, patterns, and associations, especially related to human interactions and behaviors.

Organizations collect data from a variety of sources – think business transactions, social media, and machine-to-machine data. Data exists in a variety of formats in a variety of locations. Imagine a hospital – information on a patient’s vitals like heart rate, blood pressure, and temperature may be recorded in one machine, while family health history may be stored in another machine. Financial and insurance information may be stored in another machine, or in an entirely different department altogether. Not to mention qualitative notes, staff work schedules, and PTO information. The point is, there is a lot of information collected at any given time floating around the ether.

10 Trillion Swarming Ants

So what’s the difference between “big data” and, well, just “data?” The main difference depends on size, speed, and variety.

  • Size:
    When it comes to managing data, size matters. We’re talking petabytes (1 million gigabytes) and exabytes (1 billion gigabytes!) here. If there is simply too much of it to even store in one place, not to mention organize and analyze without the help of special data analytic software, then congratulations – you’re dealing with “big data!”
  • Speed:
    Not only is big data, well, big, but it’s fast. Data streams in an unprecedent rate, and trying to collect and organize it is like trying to drink from a geyser with a straw.
  • Variety:
    If size and speed didn’t make things complex enough, data also comes in all types of formats. There’s multi-structured data – like numeric data, and then there’s unstructured data – like video, audio, images, email and financial transactions. Each has its own properties that must be addressed in order to properly analyze.

Trying to pull the info you need is like trying to find a single ant in a nest of 100 trillion swarming ants. Now that’s the challenge of big data.

Luckily, the branch of data analytics has come a long way in only a few years. Specially designed computer programs scan millions of lines of text and identify the data relevant to your needs and store it in the cloud, which is also very “big,” and has an infinite amount of room to store big data. From there, data architects can organize and pull the information needed to deduce insights.

Maybe that’s the real “big” in “big data” – utilizing big technology to make sense of the information that’s out there and improve decision making as a result, which leads to big wins.

If you want to learn more about how you can get the most out of your big data, contact our Data Analytic team – We’re doing big things!

Midmarket Guide to Data Analytics