Most companies use structured data, defined and searchable data, in quantitative form. Structured data is stored in data warehouses, where they are easy to search and analyze because they are available in predefined formats.
On the other hand, unstructured data is stored in its native format in data lakes. Since they are raw data that come in different formats, including text, audio, video, images, message, etc., they require additional processing before they can be used for business processes, data labeling, and machine learning.
A company’s capacity to collect the right type of data, interpret it, and act on the insights the data analysis provides often determines a company’s level of success. But since a company generates tons of data each day, managing them can be difficult. Moreover, data comes in different formats, divided into two specific categories: structured and unstructured data. Whatever data category you have, you need a data management platform to manage data and use them for your business efficiently.
Properties of unstructured data
Unstructured data does not have a predefined data model. Most of them are an assortment of various types of data. However, they come from sources that are closer to consumers and target audiences. Thus, they are a gold mine when it comes to the information they can provide. An organization can have missed opportunities if it fails to extract valuable information from unstructured data. In addition, the information from unstructured data may have an additional context that can lead to the higher accuracy of an organization’s business analytics, which, in turn, can enhance business decisions.
Unstructured data management
Data management for unstructured data involves collecting, storing, organizing, and analyzing information whose structure is not predefined. Managing this type of data requires advanced tools, techniques, and complex rules to change the qualitative information into quantifiable data.
It would mean lost opportunities for organizations to not utilize unstructured data because of the amount of vital information you can extract from them, which you can liken to insider information. Companies handle more unstructured than structured data because they collect information from various sources each day. When extracted and properly analyzed, a company can make better-informed decisions, develop data-driven business strategies, improve products and processes, reduce operational costs, and achieve a competitive advantage.
The other side of unstructured data management
Turning unstructured data into useful information for business growth is one aspect of data management. But you can use the unstructured data management platform when you handle data annotation and machine learning services.
Undeniably, it is more challenging to manage unstructured data, primarily because it is more extensive. Likewise, various challenges exist, but the data can become manageable and valuable in machine learning with the right tools.
The unstructured data needs cleaning and organization to improve its quality. As a result, there will be inaccurate, unreliable, outdated, and duplicate data in the collection. A data management platform has the necessary tools for unstructured data clean-up.
With a data management platform, the collection of data, which different teams store in various formats and systems, can be accessed and retrieved from one place.
It is easy for an organization to accumulate data because they handle it daily. Therefore the company must have a robust data management program with ample storage space and can compress data to keep your storage costs down. An ideal data management platform allows you to search, edit, and query data by annotation status, metadata, item information, which is helpful in machine learning and data annotation.
