Everything you must know about structured vs un-structured Data. What is it, why it matters, and how to move your data for better results.
In this challenging and competitive market, the one thing that has been helping businesses to strive and be relevant is data.
In fact, according to Forbes, 52% of businesses worldwide are making use of data and analytics to boost their business operation. 71% of businesses, on the other hand, believe that over the next three years and beyond, their investments in data and analytics will increase significantly.
From banking and finance to healthcare, every industry today is leveraging data to simplify their everyday operations and take better business decisions. Data steer a business in the right direction or, at the minimum, offer insights for planning future campaigns, organizing the introduction of new products, or conducting various experiments.
Organizations have benefited from the constant influx of data by making fact-based decisions that have led to growth. But every one of those decisions follows with the type of data that is being collected and moved.
You may have heard the terms structured and unstructured data, but you might be wondering what they mean. The distinction between structured and unstructured data has important implications for storing, processing and analysing data – particularly in large volumes. In this blog post, we cover what structured and unstructured data are, along with the main differences between the two.
Structured vs Unstructured Data: In a nutshell
You might be curious about the types of data being addressed given all the buzz about how organizations use it. The first thing to understand is that not all data is created equal. Although most data is unstructured, some of it is structured. Both structured and unstructured data live in many types of databases and are sourced, gathered, and scaled in diverse ways.
Structured data is well-organized, factual, and direct information. It usually takes the shape of letters and numbers that are easily inserted into table rows and columns. Unstructured data, on the other hand, exists in a wide variety of formats and without any pre-established organization. It can be anything from images and text files like PDFs to audio and video files.
What is Structured Data?
In simple words, structured data is a data type that can fit in a predefined format. It complies with a data model that has a clearly defined structure and follows a consistent order. Structured data is simple for a person or computer program to access and utilize.
Typically, structured data is kept in databases or other places with clear schemas. it is presented in a tabular manner with connections between the various rows and columns. SQL databases or Excel files are typical instances of structured data. Each of them has a set of organized, sortable columns and rows. And to manage structured data kept in databases, SQL (Structured Query language) is frequently utilized.
Pros of Structured Data
- Structured data is easier to access. Its use and existence predate that of unstructured data. Because of this, there are more tools available on the market for you to access, control, and alter it. Additionally, SQL may be used to call structured data, which further increases its accessibility.
- Structured data is simple to use with current technologies. Machine learning algorithms can understand and use structured data because of its clearly defined architecture. By using such technology, querying becomes simpler.
- Structured data is conducive to people. To understand and handle structured data, one does not necessarily need to have a thorough understanding of how it acts or performs. As a result, it is simpler for decision-makers to acquire, understand, and utilize data for corporate operations.
Cons of Structured Data
- It is essential to use the structured data in a specific way because of its predefined structure. The adaptability and versatility of structured data are therefore constrained.
- A predefined schema must be included in the storage because structured data must be stored in a specific manner. When the need arises to modify the data requirements, these data warehouses demand a lot of management resources.
Tools for Structured Data
Structured data has been here longer than unstructured or semi-structured data. Because of this, there are more tools available to manage structured data. A few of them are: