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Big Data: What is it?


(Big Data Term)


While it’s nearly impossible to explain what ‘big data’ is in a short blog article, I’ve attached some fantastic sources for you to dig deeper if your heart so desires.  Each week we’ll add more to the conversation which may bridge some of the gaps or answer some questions you might have formulated from week to week.

Big data is a fairly new and popular term but it describes a rich and well-practiced tradition of gathering huge amounts of data for analysis.  What is important to realize is that it’s not so much the amount of data that is essential but rather what you do with it that defines the raw power of big data and what it can do for your business.  The idea of big data can determine best possible avenues to explore as a company, it can lead to better strategic decisions and more successful outcomes, it can provide insights into trends you haven’t thought of following and it can do so much more if you simply look at what the data sets are showing you.  The wisdom is astounding in the quote, “you can’t manage what you don’t measure” which can be attributed to both W. Edwards Deming and Peter Drucker (Harvard Business Review).

Doug Laney articulated the now-mainstreamed definition of ‘big data’ by highlighting the three V’s that separate it from its common counterpart, ‘basic analytics’ (SAS):


Collect data from a variety of sources and be able to store it through new technology platforms.  More data crosses the internet every second than were stored in the entire internet just 20 years ago. (Harvard Business Review)


Data streams in at an incredible speed so it’s important to deal with it in a timely manner.


It’s imperative to collect data from a variety of sources and in different formats – structured: numeric data and unstructured: text documents, email, video, audio, etc.

There is an incredible amount of data being collected and analyzed worldwide and there are no signs of it slowing down or losing vitality.  Big data will keep taking over the industries to which we practice business and it will be on us to utilize it for success or be left behind.  Smart leaders across industries will see using big data for what it is: a management revolution. (Harvard Business Review)


Big Data: How it Works

As we’ve previously discussed, the idea of big data shouldn’t merely erase the concept of human intuition and ingenuity when making decisions or analyzing results.  It’s extremely important when handling data for your business to know the eminent questions to ask and to have the right people and tools in place to execute for the greatest possible outcome. 

  • How do we define success? A sale conversion, website click-through-rate, phone calls from an advertisement, etc.
  • Where is this data coming from? Streaming data, social media data or data from publically available sources. (SAS)
  • What do we use to measure the data? Platforms that capture the data and enable flexibility of data sets are essential. Any analytic tools that allow leadership and analysts the capability to identify key scenarios to take a deeper look into various data insights also help determine measurements. (Teradata)
  • What does this data state about how we conduct our business as of today? Have an open discussion with all personnel that should be involved that helped define the answer to question #1.

Let's do an example, shall we? The company will be called Glazed Confessions and is a bakery specializing in handmade fresh donuts.  Susan, the owner, is fairly new to social media and aims to grow her presence with her target market via various platforms. Knowing that she is starting from scratch, she consults with her stakeholders to determine success factors. They've collectively decided that website visits from specific URL's leading from her social media pages, overall customer engagement with posts and the redemption percentage of exclusive discount offers provided only to followers of Glazed Confessions on social media will be the determining factors of successful outcomes.

Susan begins by setting up Hadoop to gather all of the data and Google Analytics to help filter down the data to the sets that she's previously listed of importance. From there, she discovers that while her engagement is low on her social media pages, the customers seem to be redeeming the special offers in her bakery at a much higher rate than she was expecting. She also learned that her platforms are feeding into her website consistently but Instagram is completely outweighing her Twitter page. Talking with her stakeholders about the data that she's collected, they decide to put more of an effort into their Instagram page while focusing on publishing content that speaks to what her followers want: distinctive promotions. Susan now has the beginning tools to build her own arsenal of insights that will greatly affect the way that she conducts business and her success rate with her target market.

One tool that I mentioned in the example above happens to come up a lot when researching big data and that is a file system called Hadoop. Hadoop stores all types of data even sets that may have been likely tossed in the past. It provides data modeling that can be proven useful when integrated with an existing big data environment which can enrich business insights. (Teradata) The Hadoop system highlights the importance in 6 ways:

  1. Ability to store and process huge amounts of any kind of data, quickly
  2. Computing power
  3. Fault tolerance
  4. Flexibility
  5. Low cost
  6. Scalability

You can find out more about Hadoop and its’ offerings by clicking here.

It comes as no surprise hopefully that the companies that use the data-driven results to help make decisions within their industry were on average 5% more productive and 6% more profitable than their competitors. (Harvard Business Review)

In order to effectively work, data and analytics centricity needs to be present which means that big data’s power needs to be available to all the parts of the organization that requires them.  While some of this sounds like it could be expensive or overtly time consuming, some early adopters of big data have found that by designing the right environment, big data has actually led to cost savings for their business. (Teradata)


Big Data: Why is it Important?

We’ve discussed what big data is and how it works but now we’re going to detail why this concept is so vital to businesses today. Some people struggle with making decisions, whether personal or professional in nature. It’s often difficult to come up with an answer to a question based on your opinion alone because, most likely, many will have their own interpretations. Big data can help with this process by providing concrete and informative findings that can allow you and your team to make the best sound decision based on your desired outcome(s) for your business.

According to SAS, the importance of big data doesn’t necessarily revolve around the amount of data you collect but rather what you do with it instead. Cost and time reductions, new product development and overall smarter decision making can be achieved if you introduce big data into the overall process. 

SAS also highlighted four business-related tasks that can be executed using big data:

  • Determining root causes of failures, issues and defects
  • Generating coupons/promotions at point of sale based on customer’s buying habits
  • Recalculating entire risk portfolios in mere minutes
  • Detecting fraudulent behavior before it affects your organization

A brand most people are familiar with, Netflix, uses big data to improve their customer experience. They use it to analyze trends in program viewership, trends in content its customers are consuming, devices its clients are watching on and whether a viewer watches only a portion of media versus binging episodes back to back. Big data also helps them derive their subscription insights which rules their revenue stream and depicts what offerings they have for customers all over the globe. As General Networks highlights, Netflix has the ability to deliver the content the customer wants when they want it due to big data.


Next week: We’ll investigate who uses Big Data!

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