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Home»How To»Looking Inside Data Management
How To

Looking Inside Data Management

Michael JenningsBy Michael JenningsJan 3, 2022Updated:Oct 21, 2024No Comments3 Mins Read

Today’s modern businesses require big data. However, you can only use valuable data once it is properly managed, meaning the company should have an efficient way to collect, store, organize, verify, process, and protect vital information. 

Your organization needs an effective data management solution to access and utilize data for creating high-quality and accurate datasets. If you are looking for an effective and feature-rich tool for data management, check out https://dataloop.ai/platform/data-management/ to know more about the platform and how you can invest in one. 

Looking Inside Data Management

Contents hide
1 Effective management of big data
2 How do you define data management?
3 Why is there a need to manage unstructured data?

Effective management of big data

It does not matter if your business is small or large. You will still generate data and need data, too. It is vital to manage the data correctly and use it as an efficient tool for data annotation and machine learning.

Most of the additionally useful data you can extract come from unstructured data, meaning various data from different sources. It is not just the customer records and other information you source outside the company, which are categorized as structured data. Unstructured data includes text, videos, images, SMS, emails, media content, social media activities, etc. The data may be easy to come by, but it takes a lot of work to convert it into usable information. Checking and sorting various types of data is time-consuming. It will be too tedious to check incorrect information and duplicate records manually. You need to have a robust program to manage all available data.  

Read More: how to double down on digital transformation for your small business?

How do you define data management?

According to a pool of data management professionals, data management is the development and execution of various architectures, practices, procedures, and policies to manage the cycle of an enterprise’s need for information. 

Data management organizes data in a usable and practical way. It ensures that the company’s data collection is consistent and accurate, secured, and accessible. Aside from cleaning up the data compilation, data management prepares your company for data analytics to ensure that you have reliable and precise data whenever you need it. 

On the other hand, you also have unstructured data management platforms that store and manage various types of uncategorized data. The type of data in the unstructured category, which comprises a more significant amount than structured data, can be an excellent source of information that will be vital in creating more accurate data tags for machine learning. 

Looking Inside Data Management

Check Out: How Technology Is Changing The Legal Sector For Experts And Their Clients

Why is there a need to manage unstructured data?

Managing unstructured data can help you hurdle the challenges of improving the quality of the data, gathering them in one accessible place, and managing your data storage costs.

With proper management, you can increase your productivity as it is easier to find the data they need to build better datasets. In addition, if your team is using machine learning tools for data management, it can reduce response times and speed up internal processes. 

A data management platform can provide high-quality and reliable data, leading to better decision-making. In addition, you can use tools for real-time analysis of unstructured data, allowing you to find urgent issues and respond to them quickly.

You can easily keep up with compliance regulations and follow standards for data handling and storage. Moreover, you have a more secure place to store and process data.

A data management platform allows you to store, process, and give high-quality data you can use for business growth or provide data annotation teams with tons of useful and informative data they can correctly label for machine learning. 

Michael Jennings

    Michael wrote his first article for Digitaledge.org in 2015 and now calls himself a “tech cupid.” Proud owner of a weird collection of cocktail ingredients and rings, along with a fascination for AI and algorithms. He loves to write about devices that make our life easier and occasionally about movies. “Would love to witness the Zombie Apocalypse before I die.”- Michael

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