Understand The Difference Between Big Data And Small Data

In this scenario, two concepts stand out: big data and small data. Data collection has become an essential weapon in the race for customer preference.

After all, the more information a company has about its target audience, the easier it is to offer solutions that meet their needs. A lot of people confuse them, but they are different. While one is focused on analyzing a large volume and variety of data, the other focuses on a smaller amount of information to connect the customer to buying opportunities.

In this post, you will better understand the difference between these two tools that, if used correctly, can leverage your business. Check out!

What Is Big Data And Small Data?

Big data refers to analyzing and interpreting a large volume of data of all varieties. Its purpose is to help companies that work with data that does not have a defined structure.

For this, the concept is based on capturing, storing, and analyzing each piece of data, making it helpful information for the business in developing strategies and improvements for its services.

In turn, small data is characterized as a small amount of data that aims to promote the connection between customers and opportunities for companies. The resource aims to decode specific data that impact the company’s decision-making.

It is worth mentioning that the data collected by small data is usually much leaner and more objective. Consequently, it is also easier to access and interpret them. The information obtained through this process can serve several functions, such as increasing sales conversion.

What Are The Differences Between Them?

Now that you know big data and small data concepts, it’s time to delve into the differences between the two features. At first glance, if we only talk about the purposes of both, you can confuse them. Follow the factors that differentiate them below.

Place Of Origin Of Information

Big data can come from the most varied locations, such as databases, ERP tools, CRM, cloud, company platforms, and even external environments. In the case of small data, data is collected only from the organization’s database.

Data Volume

As we said, big data encompasses a massive volume of data. In this respect, small data works with a small, point-in-time volume of data, so it’s a more straightforward process.

Data Format

In both cases, the company mines the data it wants to analyze. Big data can deal with structured or unstructured data collected from the most varied locations, which requires a thorough interpretation. On the other hand, small data uses only structured data that is prepared for analysis.

Data Interpretation

Because it handles a massive volume of data, big data needs more robust solutions designed specifically for analysis. On the other hand, the interpretation of small data follows a simple pattern precisely because it deals with little data.

How To Apply Them In Your Company?

To choose between the two options, it is necessary to consider the real needs of the business and the volume of data to be analyzed. Generally, big data is suitable for large companies and can be applied in operations from logistics to marketing to help understand the results obtained in a given period.

Small data, on the other hand, because it sticks to a reduced volume of data, is more appropriate for smaller companies. But nothing prevents larger companies from also using it. The tool fits like a glove to analyze customer profiles and interests to understand purchase behavior and convert more sales.

The choice between big data and small data must be made based on the particularities of the business. Bearing in mind that the two methodologies can be adopted in a complementary way, they can make your team’s decisions more accurate and generate valuable insights that increase your competitiveness in the market.

Also Read: Big Data: Understanding The Power Of Data Analytics

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