Big Data is Big Business

Big Data is a term that describes vast volumes of data that deliver insights into organizations, products, consumers and trends that smaller scale data is incapable of offering. The concept is, at its core, very simple, but the scale of big data is nearly incomprehensible. To put big data into context, Facebook users have uploaded over 250 billion images. That’s more than the number of stars in the Milky Way. Take a moment and try to comprehend 250 billion of anything. It’s an amount that the human mind struggles to grasp. To understand big data, you must first understand the differences between structured and unstructured data. Furthermore, you must understand the Three V’s of big data: Volume, Velocity and Variety.  

Structured data is information that is highly organized and readily available. It is organized and formatted to fit into specific templates. Structured data can include numbers, dates and groups of words. Census records, library catalogues, economic data, educational databases and social media interactions (Facebook likes) are all examples of structured data. Structured data can offer an advantage over unstructured data in that it is easy to search for and, for the most part, it is widely available.

Unstructured Data is unorganized and can include a wide variety of file types including emails, word processing files, audio and video. Most unstructured data however, is simply text. When it is said that unstructured data is “unstructured” it is meant that the data may have a loose organization but is meant for human interpretation as opposed to a machine algorithm. Take a corporate email inbox as an example. The typical inbox can be organized by date received. The program organizes them in a rudimentary fashion that allows for humans to more efficiently sort through them, but does not organize emails by the information within the attachments and body text.

Volume describes the total amount of data collected. Large Organizations organically collect information from an array of sources every single day including sensors, video/audio, transactions and social media. Having more data enables models to produce more accurate estimations and allow businesses more insight into consumer behavior. Given that Facebook has 2 billion users, YouTube has 1 billion, Twitter has 350 million and Instagram has 700 million, there is a vast amount of data constantly being collected and analyzed all across the internet and real world.

Velocity is a term for measuring the flow of data input. Facebook having the capacity to store 250 billion photos is an incredible achievement but that number may soon seem insignificant in size. Receiving more than 900 million photos a day, Facebook servers must have incredible velocity of data to catalogue this immense influx of photos and then produce them when requested by a user.

Variety is the massive array of file types that we consider data. Photographs, documents, books, emails, sale receipts, credit card information, even tweets are considered a variety of data in big data. Most of this data is unstructured and may not fit perfectly in a spreadsheet like numbers or more quantifiable information. However, just because it is unstructured, doesn't mean it won't offer an insight into a possible opportunity for a business to save or make money. 

Now that we know more about the fundamentals of big data, we can take a closer look at how it is applied in the real world. Businesses across the globe utilize big data activities to collect data for analytical use, new product development or both. Netflix is one of the most popular brands in The United States began its monthly subscription model for unlimited DVD rentals in 1999. It moved into the realm of streaming in 2007 and by 2010 had 20 million subscribers “House of Cards” was introduced in 2013 and had over $100 million invested into twenty-six episodes. Netflix Originals are the result of big data content creation and “House of Cards” was the first show that Netflix produced using big data. The show was met with critical acclaim and was an exclusive to Netflix users. The production of “House of Cards” proved to be a savvy business venture as the show earned eight Emmy nominations and spurred immense accolade for Netflix. Netflix knew that “House of Cards” was going to be popular and they utilized six years of big data to ensure that success. After introducing streaming in 2007, Netflix began collecting data about its user’s interactions with the service. During their collection, they noticed that there was a significant base of people that were fans of Kevin Spacey, enjoyed David Fincher films and liked the original BBC mini-series House of Cards. They predicted that a Netflix produced “House of Cards” that starred Spacey and was directed by Fincher, would prove to be very successful. This prediction was bolstered by big data insights and began the saga of Netflix’s “data engineered” productions. To understand how Netflix effectively utilizes big data we must understand what sort of data they collect. Some of the information collected by Netflix includes: ratings, search queries, dates that the movie/show was watched, what device is a show watched on, how the nature of the show varies from device, what portions of the program users rewind and re-watch when users pause the program? These are points of data that Netflix collects and uses in its own products to hook people in. The service breaks down collected data about you, creating a user profile and then with over 76,000 “micro-genres”, Netflix offers personalized genre recommendations. A huge goal for Netflix is subscriber retention, as acquiring a new subscriber is 5x more expensive then retaining someone who is already a subscriber. Netflix’s analytical use of big data creates quality offerings that are personally tailored to each individual Netflix user. 

We have discussed the results that big data has for an enormous company like Netflix with millions of users but how does a small business utilize the incredible power of big data to improve business? Facebook offers businesses positioning in the lives of target audiences by utilizing big data insights to target more receptive consumers You do most of your business from people coming into your shop but have recently begun selling records online and want to receive more orders. Facebook can enable businesses to target ads at specific audiences, with specific interest, in specific locations. Any business can utilize Facebooks nigh infinite data stream and analytical services to reach a very specific audience. 

Facebook allows you to edit the age, location, gender and language of the people you wish to include or exclude in your audience. When entering location, a business can even specify whether they wish to include everyone in the vicinity, solely people who live in the area, people who recently were in the location or people that are currently traveling in the location. 

To better illustrate this I will use a school supply store in Atlanta as an example. The owner of a supply store knows that school is starting soon and so they want to make sure they create a Facebook ad campaign that will connect to people wanting to purchase school supplies for their children. 

First, they must specify the location of the ad campaign, in this scenario Atlanta Georgia.

Then the age, sex and language of the target audience. 

Lastly enter in the demographics and interests of the target audience.

Users can even specify audiences that they don’t want included. 

At the bottom of all of these options there is a button prompting users to save the audience. This allows users to use specified audiences in separate campaigns in order to reach the same desired audiences.

Big data is giving companies more perspective into the minds of consumers than ever before. With billions of data points being produced every single minute, products are going to be sharpened by a consumer perspective. Companies like Netflix utilize big data daily to produce products and content that have statistical data ensuring success and Facebook offers smaller businesses an opportunity to utilize the massive Facebook analytical network to connect with desired audiences. 

Images: SAS & upxacademy

John Tyler Diehl