Guide: Data Management

Metadata Management

Metadata is a term used a lot by businesses throughout multiple industries. It makes sense that the more prominent the management of metadata becomes throughout the company, the more it will show up.

Although, it is sometimes difficult to decipher what Metadata Management is, especially outside of the function you know it entails.

Therefore, this article will explore the full use of the term and opportunities inherent in Metadata Management using the following breakdown:

This is part of our complete data management guide.

Metadata Definition

The simplest way to explain Metadata is as a set of data that describes and provides information about other data.

 

Admittedly, offering information about other information doesn’t define much, though. So, here are a few examples of data that is considered metadata, to clarify this explanation:

 

  • Author
  • Date created
  • Date modified
  • Size in bytes
  • How data came to get created
  • Why you’ve entered the data into the database
  • Relation of data to larger data set
  • Tagging

 

These are all categorical options, which can add description to a data object (column, table, file,  etc).

What is Metadata Management?

So, now that you have a better understanding of what Metadata is let’s delve into Metadata Management.

 

The management of metadata is when you create and organize the metadata in a big data system. Metadata Management organizes files and portions of data so that users can find the information they seek quickly.

 

Without Metadata Management, your company would have no direction for finding data. It would just be a big guessing game, which would waste time, resources, and loads of money. (Plus, it would be frustrating for everyone involved.)

Metadata Management Benefits

Metadata Management can offer many benefits to a business. Here are some of the biggest benefits you can expect from correctly setting up a workable Metadata Management system:

Improves Data Staging

The improvement of data staging through Metadata Management is apparent through the most basic function of the system. When you organize your metadata correctly, you are laying the positive groundwork for a sound and reactive system from the moment data is entered into the system.

 

Therefore, you are setting the stage for building big data success.

Provides Reliable Big Data Management

Reliability is exceptionally important in every aspect of every business. If you cannot rely on a portion of your business, or your customers cannot rely on a portion of your business, you won’t survive. Simple as that.

 

So, one of the major benefits of metadata management is that it provides reliability, regardless of how much data your system contains, processes, and takes in. If your system gets set up correctly, you can build that system infinitely and still have an easy, reliable categorization of your data.

Enhanced Data Quality

Data quality is always a concern for businesses. However, the more avenues and the higher volume of data ensure a more increased need for data quality. That is where Metadata Management comes in.

 

With the correct Metadata Management system, you can see each time a person accesses the information in the database. Therefore, you always have a record of what happened. You will always know when it happened and who completed the action without having to search through thousands of logs.

Excellent Delivery Speed and Affordability

When your Metadata Management system is a well-oiled machine, you can receive information, answers, and solutions much quicker than if you had to search for data and connections to that data manually.

 

So, the time, effort, and skills saved result in excellent delivery speed and affordability.

Scalability

Another one of the benefits of Metadata Management is scalability. If your system is built solidly and managed properly, scalability is never an issue because the system will scale right along with the influx of data.

Helps Governance and Security

Data governance and data security are always the main concerns for businesses, especially when working with big data. Having an organized Metadata Management system allows your company to always have your finger on the pulse of your security. With an organized system, you should notice anything amiss right away and fix it before it has a chance to wreak havoc.

Types of Metadata Management

Considering that Metadata Management encompasses a vast array of different data taxonomies, it makes sense that there are different types of Metadata Management.

 

Here is an explanation of the three main Metadata Management types you need to be aware of and incorporate into your system:

Structural Metadata

This type of metadata is the bare-bones, most basic form of metadata. Structural metadata is the skeleton of the data. It paints a wide brush stroke and encompasses all the data but returns very basic information.

 

Here are the different categories for structural metadata:

 

  • Page numbers
  • Sections
  • Chapters
  • Indexes
  • Table of contents

 

Even though this first type of metadata seems vague, it is important. It starts the spiral of information, giving the system many different indicators to latch on when it begins its search.

Administrative Metadata

Administrative metadata is more specific and winds its way deeper into the information spiral found within a Data Lake. The information inherent within this type of metadata still has a summary or clerical feel. Nevertheless, there are a few delineations that are important to note within the category of Administrative Metadata:

 

  • Technical Metadata: This metadata gets reserved for any information necessary for decoding and rendering files.
  • Preservation Metadata: This metadata is great for information used in the long-term management and archiving of the data.
  • Rights Metadata: This metadata categorizes information about intellectual property and usage rights.

 

When you look at the different types of Administrative Metadata, it is easy to see how these specific offshoots can be necessary for a business to take the time to include in a data system.

Descriptive Metadata

If you are looking for ultra-specific information, you want to understand the Descriptive Metadata type. This type helps users find unique items within the data set and have the most singularly identifying markers.

 

Here are a few of the ways Descriptive Metadata gets used:

 

  • Unique identifiers (such as a book’s ISBN or eBooks ASIN)
  • Physical attributes (such as file dimensions or Pantone colors)
  • Bibliographic details (such as the author or creator, title, and keywords)

 

Even though these Metadata Management types are very different, a well-rounded data system should incorporate all of them to ensure the return a search receives is as informed as possible.

Metadata Management vs. Master Data Management

Metadata Management and Master Data Management work together, but they focus on two very different aspects of data organization. While Metadata Management is finite and singular, dealing specifically with every individual data set, Master Data Management focuses on the bigger picture.

 

Here is a breakdown of differences between Metadata Management and Master Data Management:

Metadata Management
Master Data Management
  • Categorize individual data sets.
  • Lays the groundwork for a searchable system.
  • Provides the building blocks for big data inclusion and organization.
  • Aids governance.
  • Unifies information throughout the big data system.
  • Provides the whole picture to users.
  • Adds reliability and cohesiveness to the system.
  • Offers a solution to discrepancies in data.

Master Data Management Explained

Master data management (MDM) is the best way for a business to ensure its information is cohesive, uniform, and reliable throughout all data assets.

 

When big data is coming in quickly, especially to a large company with many different information input methods, some details can get skewed. Whether it is that different inputters have a different perspective or use different terminology, data can become confusing.

 

So, MDM organizes multiple data sets to clarify the story. It collects all relevant information and presents it in the truest version of the cumulative data.

What is a Data Catalog?

A Data Catalog is an organized inventory of data assets available to the company. It uses the metadata that your company inputs and data management tactics and search tools to make finding data even more accessible.

 

While metadata works specifically with the file, a Data Catalog combines different capabilities within the system to ensure it returns the most complete and accurate information available.

 

A Data Catalog is different from metadata, but it works to return desired results quickly.

 

Here are the main functions of a Data Catalog:

 

  • It collects metadata.
  • It serves as an inventory for your categorized data.
  • It provides information to evaluate data for the intended use.

 

For more information, read our dedicated guide to data catalogs.

Conclusion

Ultimately, Metadata Management uses data to help companies organize their big data. When you implement a clear, concise, and easy-to-follow Metadata Management system into your data system, you can ensure that you are setting yourself and your company up for success.

 

Satori, The DataSecOps platform, provides capabilities such as continuous sensitive data discovery (including integration with data catalogs). Satori also builds a continuously updated data inventory as data is being accessed. To read about what Satori does, read about some of our key capabilities::

 

 

To learn more about Satori, go here.

This article was originally published at

January 19, 2022