On the surface, it sounds as vague as familiar organizational catchphrases like corporate synergy, core competency or bleeding edge.
But big data is more than just a fashionable phrase. It’s a genuine business strategy that aligns with today’s (and tomorrow’s) information-hungry society.
How does one define big data? And how can it help you and your business in the information age? First, let’s understand what big data is.
What Is Big Data?
As you’ve probably guessed, big data is just that—large, complex volumes of data. To get an idea of what is meant by big data, let’s look at an extreme, but no less insightful, comparison.
Consider a business incorporated in the 1960s, 70s or 80s. These businesses generated data. Only they used paper. A so-called paper trail could include transactions like written or printed purchase orders, handwritten receipts, customer forms or business contracts kept in a filing cabinet.
Now, consider business processes today. When was the last time a filing cabinet was your first stop when looking for a piece of information?
That paper trail model has now been digitized. For many, records are now kept in online databases and communicated across various platforms. Email or text messages and posts on websites or social media platforms like Facebook, Twitter, Instagram or LinkedIn are all digital and are all big producers of data.
Also, the data generated through digital advertising, and those engaging with that advertising, is astonishing. It’s an online search. It’s on a Google My Business site which means it pops up in Google Maps. The organization shows up on Apple Maps, and also in Bing or Yahoo. Transactions and the exchange of information occurs across all of these mediums.
All of that activity involves lots of data. It includes every single organization, every single industry and the legion of customers that engage with all of these groups and each other.
Everyone—and we mean do mean everyone—has a digital footprint. That footprint is filled with data—lots and lots of data. Consider this mind-boggling list of stats:
- As of 2018, the earth’s population was roughly 7.5 billion people.
- 5.1 billion are unique mobile phone users.
- 4 billion of those people use the Internet, leaving traces of data in their wake.
- 3.1 billion people are active social media users, adding to their pages with data point after data point.
All of these individuals are generating data every single time they log onto the internet or activate their smartphones. This includes contact info, photos, messages, social media posts, purchases, transactions, online help chats, gaming and more. It’s all data.
Types of Big Data
Big data itself can be structured or unstructured.
- Structured data is information such as names and addresses, phone or credit card numbers, stock information and geolocations. Think of it as the highly organized info you would find in a database. It’s quantifiable data that you can easily organize, understand, and search, especially when using machines to discern it.
- Unstructured data is not as plainly defined. It encompasses sources that you won’t be able to fit neatly into a spreadsheet or database. Things like audio and video, mobile or social media activity and most forms of image-based data are all considered unstructured data. This type of data also includes the text and information that resides in emails, text messages, digital files or PDFs.
Analysts have estimated that unstructured data makes up for more than 80% of big data.
While data may not be a resource on the level of water or oil, it is just as valuable a commodity. Those who best understand how to use big data will gain a clear advantage over their competitors.
Need examples? Look no further than companies you engage with on an almost daily basis, like Amazon, Apple, Facebook or Google.
To figure out how to push for that upper hand, let’s first look at the building block of big data—the five Vs.
The Five Vs of Big Data
Big data is, well, big. Its concepts can get confusing, especially as it continues to grow and evolve. To make it more accessible, big data is broken down into more manageable buckets—volume, variety, velocity, veracity and value. Collectively, these are known as the five Vs.
The first of the five Vs is volume. The amount of data produced in today’s society is massive. Email, social media, websites you search, purchases you make, the car you drive, industrial assembly lines, retails stores you visit—practically everything you touch or do produces data.
To make sense of the sheer volume of it all, this list provides a small measure of our data-generating society. Depending on the size of your business, the data you collect and process could be small, like measured in gigabytes or terabytes. Or, your business could be processing an amount far more significant like measuring in the petabytes.
Variety often references the more unstructured side of today’s data processing. As noted earlier, roughly 10% to 20% of data is structured. This is the stuff that is easy to make sense of and from which you can derive some intrinsic value. Basically, the information that you can fill a spreadsheet with.
The rest of it, such as audio and video, images or different levels of text, requires deeper processing to understand its meaning and usefulness.
Velocity speaks to how fast data is received. More than just the speed at which the data streams and gets captured, velocity also refers to how quickly a firm can analyze and act upon the data.
For an organization to remain competitive in a given industry, this often means the whole process is happening in real-time and practically instantaneously—data acquisition, analysis and action, all the blink of an eye.
Every bit of data a company processes can fall into one of two categories—clean and consistent or messy and disorganized. This is big data’s veracity. With streams upon streams of data to sort through, the quality of that data can often be questionable, as that data originates from both trusted and untrusted sources.
The nature of big data sometimes makes it hard to classify the good from the bad. You might pull in vast amounts of data, but that can lead to uncertainty in quality. Grabbing too little and your lack of quality lies in the potential incompleteness of it.
The final and perhaps most critical V is value. Value looks at whether the data is beneficial to the company that possesses it. Data on its own is relatively worthless. What is valuable is when an organization takes a multitude of data streams, both structured and unstructured, and converts it into something beneficial for the company.
Much of the value of big data originates from a company understanding it enough to fulfill their goals. Start with an uncertain path or set of initiatives and the value of any data deemed usable will be equally as lackluster.
Why Does Big Data Matter and How You Can Use It?
The importance of big data is what it represents for companies hoping to take advantage of new opportunities. Regardless of the amount or quality of your company’s big data or how quickly you can acquire it, it’s useless if you can’t discern meaning from it.
If you think it can’t work for your firm, think again. Industries as varied as banking, education, health care and retail all harness the power of big data. They use big data to minimize risk and fraud, help increase student performance, better organize patient records and improve customer relations.
So What Can It Do for Yours?
Operationally, big data helps you improve and streamline efficiencies. In retail, you can examine customer returns and identify patterns that help to reduce them. In software, customer feedback leads to your building more meaningful software platforms and updates to meet their actual needs instead of those that are just perceived.
Manufacturing companies can certainly suffer when breakdowns occur in machines or tools that drive that production forward. Big data makes sense of the data output from these machine systems, many of which are automated. The resulting predictive maintenance addresses concerns before they occur which keeps the company and its industrial tools humming along.
No matter your industry, there’s little doubt that your customers want more attention, more service, more engagement or more of a product. Big data keeps you ahead of your customers to maintain their level of satisfaction.
Leveraging data from social media, engagement content or consumer surveys helps you build products and services consumers will want to use. Data promotes engagement with customers at the places they want to connect. It also allows you to craft a personalized experience in your marketing and sales channels. It transforms your brand into one that speaks to your consumers, instead of at them.
When it comes to innovation, big data plays a crucial role in helping organizations take the next step forward. It makes large ideas achievable for even the smallest companies.
Finally, protecting the security of your employees, partners, vendors and consumers is paramount to building a firm that is not only successful but trustworthy. The more value you place on security, the more applauded your organization’s image can become.
Big data produces plenty of patterns which upon scrutiny can reveal instances of fraud or corruption. The proper analysis helps to promote systems more adept at protecting information and improving the channels to communicate the activity faster should it occur.
For big data to have a positive impact on your organization’s success, invest in the technologies that will make the most of the data you capture. An appropriate amount of inexpensive data storage, systems to support the culling of data, cloud platforms and open source processors all provide you a foundation on which to acquire and analyze your big data.
No longer a buzzword, but a legitimate business strategy, big data is here to stay. If you hope to make it work for your company, you need to think even bigger.
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