Understanding data and how it influences your business strategy is a straight-up necessity in today’s world, and chances are you have a pretty good idea of how your data works. Big data is a common topic of discussion in the business intelligence world, and you may have had discussions within your organization about how to leverage big data in your strategy. But when was the last time you thought about big data’s little sibling, small data?

Sure, most organizations understand the importance of data, but fewer truly grasp the relationship between the two different types: big data and small data. For many people – even those with years of experience in data analysis – the phrases “data” and “big data” carry similar weight and meaning. In reality, small data is just as important. In fact, both small and big data have the power to influence the bottom line of your organization. The key is understanding the difference between the two and finding value in both.

The Three V’s: Volume, Variety, and Velocity

Before we can understand how your business can use both types of data, let’s start with the nitty gritty, technical difference between the two. Typically, data experts define big data by the “three V’s”: volume, variety, and velocity. In actuality, the three V’s aren’t characteristics of big data alone; they’re what make big data and small data different from each other.

Volume – Data volume is the sheer amount of data you have to process. Big data involves larger quantities of information while small data is, not surprisingly, smaller. Here’s another way to think about it: big data is often used to describe massive chunks of unstructured information. Small data, on the other hand, involves more precise, bite-sized metrics.

Data volume is the sheer amount of data you have to process. Big data involves larger quantities of information while small data is, not surprisingly, smaller. Here’s another way to think about it: big data is often used to describe massive chunks of unstructured information. Small data, on the other hand, involves more precise, bite-sized metrics. Variety – Data variety refers to the number of data types. The easiest way to understand data variety is through example. If you’re analyzing traffic to your company’s website, “big data” might refer to the whole number of visitors, regardless of how they reached the site or their demographic qualities. Small data tends to focus on one type of data, so your “small data” could be an analysis of all visitors who found your businesses through social media posting.

Data variety refers to the number of data types. The easiest way to understand data variety is through example. If you’re analyzing traffic to your company’s website, “big data” might refer to the whole number of visitors, regardless of how they reached the site or their demographic qualities. Small data tends to focus on one type of data, so your “small data” could be an analysis of all visitors who found your businesses through social media posting. Velocity – Data velocity describes the speed at which information is acquired and processed. Typically, big data involves huge chunks of information brought in and analyzed in periodic batches. If big data were to enter your reports in real-time, you might end up with an insurmountable volume of information. On the flipside, small data can be processed quickly and tends to involve real-time or near real-time sets of information.

Big Data, Big Hype

Big data has its place, but don’t fall into the trap of assuming “big” means “better.” Depending on your organization’s type and goals, big data could mean massive social media statistics, machine data, or customer transactions every day. On the surface it is intricate, complex, and difficult to manage. Because of this, big data can be understood as “raw” data.

In order to understand how big data can help your organization, you’ll need to pull it from multiple sources, clean it, and organize it in one space. Unfortunately, this can be a challenge for many companies – especially ones without the data organization and visualization tools needed to get the job done. This doesn’t mean you shouldn’t use big data; it simply means you’ll need to organize it properly before you can turn it into something more valuable.

Why Should You Care About Small Data?

If big data is difficult, does that make small data easy? In a way, the answer is “yes.” On the other hand, small data requires the right tools and a data-savvy mindset to make it work for you. It is, in some cases, a little bit easier to get your hands on and whole lot easier to translate into actionable insights.

The benefits of using small data:

Small data is everywhere. Social media alone offers an array of small data about buyer decisions and the customer lifecycle. In fact, anyone with a computer or smartphone creates small data every time they log into Facebook and click an ad or search for a product they saw on an influencer’s Instagram account.

Social media alone offers an array of small data about buyer decisions and the customer lifecycle. In fact, anyone with a computer or smartphone creates small data every time they log into Facebook and click an ad or search for a product they saw on an influencer’s Instagram account. Small data immediately translates to business intelligence. The bridge between small data and “how can we use this to reach more customers” is short. By nature, small data is easier for humans to comprehend. It is actionable. This means you can – generally speaking – use small data to benefit your business almost immediately.

The bridge between small data and “how can we use this to reach more customers” is short. By nature, small data is easier for humans to comprehend. It is actionable. This means you can – generally speaking – use small data to benefit your business almost immediately. More businesses are using small data. More than ever, companies are beginning to understand the value of data-driven marketing decisions. By using small data, you can stay ahead of the curve in your marketing and business intelligence strategies. Big data is still important, but combining big and small data is the first step to reaching customers in a meaningful way.

More than ever, companies are beginning to understand the value of data-driven marketing decisions. By using small data, you can stay ahead of the curve in your marketing and business intelligence strategies. Big data is still important, but combining big and small data is the first step to reaching customers in a meaningful way. Consumers are on board, too. Whether they realize it or not, your customers also value small data. Whether they want the lowest price on plane tickets home for Christmas or enjoy the ease of a personalized shopping experience from their favorite store, the people your organization wants to reach are already actively engaged in marketing initiatives that use small data.

Whether they realize it or not, your customers also value small data. Whether they want the lowest price on plane tickets home for Christmas or enjoy the ease of a personalized shopping experience from their favorite store, the people your organization wants to reach are already actively engaged in marketing initiatives that use small data. Small data focuses on the end-user. It’s no secret that focusing on the end user is one of the best ways to understand what they want and need from your business. Small data is closer to the end user and focuses on individuals’ experiences with your company. Thus, small data can help you achieve an “end users come first” approach.

It’s no secret that focusing on the end user is one of the best ways to understand what they want and need from your business. Small data is closer to the end user and focuses on individuals’ experiences with your company. Thus, small data can help you achieve an “end users come first” approach. Small data is simple data. When you turn big data into small data, you make it easier for stakeholders and decision makers to understand. Big data often requires expert interpretation, but anyone can understand small data. This means small data can help your company reach its audience by helping stakeholders understand how to turn that data into a real strategy.