Introduction to Unstructured vs Structured data

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Introduction

Data is the brains to every business and it’s our core here at Corva. Data exists in a wide range of formats from strictly formatted, database structured data to the last post on a reddit thread. All the data out there, including your twitter feed, can be categorized into two buckets: structured and unstructured data.

These two buckets can define data by looking at the who, what, when, where, and how. These 5 questions outline the fundamentals of structured and unstructured data:

  1. Who is the user?

  2. What data type?

  3. When will the data be prepared?

  4. Where is the storage location?

  5. How will the data be stored?

Structured data

Structured data is when data is formatted and predefined, based on a set schema before being stored. The key word here is before. This is sometimes defined as schema-on-write. An example of this would be a user database with fields such as email, phone, address which are all easy to query.

Benefits of structured data

  1. This type of data is ideal for machine learning. It lends itself to easy manipulation by being specific in nature and organized uniformly.

  2. Preferred by business users (analysis) : average user can easily query or manipulate a structured data set if they have an understanding of the data topic

  3. It is the legacy form of information. This type is how data has been stored as it has been the only option until recently

Pitfalls of structured data

  1. Structure is limiting. When data is stored in a specific structure, it is also the case that the data is stored that way for a specific purpose. Not lending itself to much flexibility

  2. Fewer storage options: structured data is stored traditionally in data warehouses. These warehouses have strict schemas and any change in that schema means all the data in the warehouse needs to be changed. This is a large undertaking and is costly. This has evolved over time and now some of this pain can be eliminated by the use of the cloud.

Unstructured Data

Simply, unstructured data is data stored in its original form without any pre-processing. This type of data comes in all shapes and sizes such as sensor data, media posts, conversation threads, etc. This type of data is also widely referred to as schema-on-read.

Benefits of unstructured data

  1. Flexibility to store any format: the data is not processed or defined until it is needed to be used which leads to a larger number of use cases for the data. It allows for the data to be cut and diced and only processes the data needed for a use case. It also does not restrict the types of files to be stored.

  2. Without the need of pre formatting or processing, it allows for faster rates of accumulation. There is no need to define incoming data in any way so data can be stored easily

  3. Most of the data storage for this type of data is cloud based and pay as you go which is a benefit to companies in the form of cost savings.

Pitfalls of unstructured data

  1. Requires a data expert to prepare or analyze the data. This data type is not usable to a regular business user as it is stored.

  2. Requires specialized tools to manipulate. Most tools are structured and were specifically built for structured data. The market of products to handle unstructured data is limited which leaves the data manager with little optionality.

Conclusion

Data is Data. The value of said data is how we use it for a benefit. Both structured and unstructured data have value and can be used in various ways for various forms of business cases. In the modern time, we can agree that data is the future. It helps make better decisions, shapes which direction a company may lean into, and certainly enriches our way of life today.