Businesses must understand the differences between structured and unstructured data. While some data gathered by a company is structured, some aren’t. This means there are differences in the ways the data is sourced, collected, and scaled. Furthermore, structured data sits in a different database than unstructured data. How can a business use this information to make the most of the data it gathers?
Structured Data
Data that can be contained in a fixed field within a file or record falls under the category of structured data. Think of a spreadsheet and the information it contains. This is structured data. It can be entered, stored, analyzed, and queried. Any business that has a customer records database has structured data. An employee enters the data using a uniform format. The program then organizes it, so the data can be accessed and analyzed by the business. To learn more about structured data, go to this website.
Other examples of structured data include airline reservations, inventory control, and sales transactions. In addition, point of sale data and weblog statistics fall into this category. A person often uses SQL to enable a query on this data contained in a relational database.
Unstructured Data
Unstructured data, in contrast, has no fixed format. Computer programs cannot use this data easily, as it lacks a structure that can be easily identified. This data comes from diverse sources. As a result, the business must use specialized tools and data science talents to manage it. As a result of the volume of unstructured data collected as of today, many data lakes and the Hadoop platform have grown significantly.
According to Realtimecampaign.com, email serves as one type of unstructured data. Presentations, chats, social media posts, and more also fall into this category.
How to Tell the Difference
A company such as ResoluteAI wants to help users distinguish between structured and unstructured data. A person needs to know how and where the data will be stored.
The user needs to know what preparation is required before the data can be used or stored. The answers to these questions make it easier to determine which category the data falls under.
Artificial intelligence and machine learning will play a large role in the future of data. With the help of this technology, people find it easier to analyze digital communications or track customer communications on social media. Furthermore, they get new insight into marketing and customer behavior.
When comparing Structured Data vs Unstructured Data: Differences & Examples, consider whether the data is simple or complex. Can a person easily search and analyze it thanks to the uniform format? If so, it is structured data. In contrast, unstructured data is complex, making it difficult to search and analyze. The formats are too diverse. Furthermore, look at the data. If it contains letters, numbers, and symbols, it is likely structured data that can easily be contained in databases.
Every business, regardless of size, needs to handle all types of data to receive these benefits. Learn more today about both types of data and how they are of use.
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