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Metadata automation: How to harness it and evolve your company?

When you go to the supermarket, do you read the characteristics of the products you chose to buy? If you are very attentive to details, your purchase decision can take more time or lead you to compare other products in the same category.

Imagine a scenario in which you chose a soap that you saw in the personal hygiene products section. In addition to the indecision caused by the aroma, you look at the weight, the formula it was elaborated with, and if it contributes to the care of your skin, among other factors; all of this leads to the question of whether you are making a good decision or if it is better to choose another brand or another soap.

All this information will influence your decision and the health of your skin. Believe it or not, something similar happens with data, which simultaneously produces descriptive information known as metadata. It is generated in exponential quantities, which ultimately could affect the development of your company if there is no metadata automation.

According to Gartner research, their clients spend more than 90% of their time preparing data, which is later used in fields such as advanced analytics, data science, and engineering.

If you want to optimize metadata management and know its impact on other areas of your company, in this entry blog we share with you information to enhance business decisions by obtaining reliable and accurate metadata.

 

Metadata optimization

The volume of information generated around the operations of a company is increasing due to the growth of digital tools, however, the volume is not the only asset to work with in internal and external areas. In addition, there are multiple formats that complement data, and in turn, data is generated at speeds that are beyond human control.

Controlling metadata is a big challenge for specialists who work and want to extract value from it for the benefit of the company's departments and stakeholders.

However, managing metadata should not be taken lightly. Controlling it requires an automation process, which will bring benefits such as time reduction in labeling, cataloging, and tracing relationships between data. This allows for obtaining insights, which would otherwise be a slow and misaligned process.

We will describe its benefits next, which can range from something simple such as information democratization to something more complex such as data governance.

 

Metadata automation benefits

Metadata provides detailed information. This is the reason it becomes another essential asset in companies since it describes what is surrounding data and gives context about its processing. It provides specificity and answers the questions of what, how, when, where, or who is behind data. This may include some categorization, tags, storage location, descriptions, modifications, accesses, and more.

 

 

An image that shows metadata as an important agent in other strategies such as Data Governance, Data Lineage, Data Quality, unified terminology, and democratization.

 

All of the aforementioned elements bring tangible benefits when they get linked. These are the areas with the greatest positive impact:

  • Data Quality improvement: Thanks to the information that metadata brings, it is possible to detect incorrect or incomplete data.
  • Data democratization: access to information becomes easier with metadata, what you seek is what you find, thus establishing a place where data can be found and worked with can be done.
  • Unified terminology: metadata allows all your data to be unified with terminology in favor of processes; that is, a business glossary.
  • Data Governance: metadata, by having details about who works with data, allows knowing their specificities such as access and policies with which they are related. Those policies may be usage, connection, security, or lineage.
  • Data Lineage: well-structured metadata is capable of creating a relationship between past or current information, and thus knowing the link between them.

In any case, if metadata management can be automated, the chances of failure drop considerably with actions such as labeling, link generation, and cataloging data volume, which represents a very complex task for human effort if done manually.

Automating your metadata management will give you better results in process response time, reports, analysis, and decision-making. However, this is not the end of the information about metadata automation. There are different types which we describe in the following section.

 

Metadata automation types

Nowadays there are different options to implement and harness metadata automation. Knowing and analyzing them to choose the one that best suits your needs is the right path in the digital business world. Let’s check them:

  • Machine Learning: This technology and metadata automation can work very closely since it uses information from metadata to connect, understand, and streamline data organization.
  • Natural language processing1: similar to artificial intelligence, it helps to automate and extract valuable information that is in text documents such as emails, documents, sites, or social networks.
  • Image and video analysis: multimedia materials, by having tags and keywords in their metadata, become elements that can be used to create, update databases, and decide on the efficiency of the content.

These elements are differentiators in a competitive market where you and your teams must remain up to date-with innovation and different solutions.

However, to achieve your goals it is important to have tools to make your business processes easier. Therefore, you must intelligently choose the platform that will actually help in the transformation of your company.

 

Metadata automation platforms: what should you look for?

To make metadata automation effective, you must initially choose the appropriate platform to make your strategy more effective and efficient. Select one that guides you towards solving problems and thus reducing costs or strengthening the security of your information. If the following list attends to it, you are about to make the right decision:

  • Active metadata capabilities to always maintain the metadata up to date.
  • Data inventory with the capability to automatically identify similar attributes, resolve ambiguities and detect relationships with other data assets.
  • The platform should be able to scale in order to handle the amount of data and users that the organization has.
  • Data enrichment through automatic discovery and user tagging and rating
  • The tool should be cost-effective and provide a good return on investment.
  • The system should have good customer support and training resources to help the organization effectively implement and use the tool.
  • It must be able to trace data lineage for identifying data provenance.
  • The platform should be able to manage active metadata which includes the extensive use of metadata leading to significant automation through AI/ML to support broader data management activities.
  • Business rules should be visible and have the ability to identify exceptions.
  • The tool should allow metadata exchange with third-party tools.
  • The platform should have the necessary security features to protect the data and meet regulatory requirements.

As you can see, having a highly detailed plan on how to execute metadata automation in your company is a huge differentiator between doing it right and doing it great. The best path is to set goals, and review the current state of your data and its metadata, the resources it needs, and the development you want.

Once implemented, you need to look at the strategy performance, measure KPIs and obtain reliable metrics, which will guide you on the profitability of the project based on the return on investment, or make some adjustments on the go.

In addition, taking this path implies keeping your metadata updated by doing periodic analysis. This is known as Active Metadata, let’s talk about this concept.

 

Use case: What is the role of Active Metadata?

Your organization must have processes and information that are periodically reviewed to find out if they are being done correctly or not. This works the same when we are talking about data, and it is known as Active Metadata.

Active Metadata is, in Gartner's words, the continuous analysis of all available data (users, government, architecture, systems, and reports). These keep your entire information ecosystem alive, which translates into reliable data and a favorable return on investment.

Maybe you are wondering how metadata automation and active metadata are related, and it is explained here in great detail. Check it out! 

We do not want to end this section without putting into perspective the importance of metadata and how some companies have been able to harness it, always in favor of empowering the company.

In Netflix's case, to determine which cover images have a better impact on the reproduction of their content, they test them with different parameters. The use of metadata is essential in this case, since each cover contains different characteristics such as color correction, title treatment, and text size, among others. In the end, the image that yielded the best results in the reproduction of a series or movie is the one that will be on the platform worldwide. We know, it's awesome!

 

Conclusion

The case that we present to you is a clear example of how metadata is a differentiator in the business world. For this reason, we invite you to make metadata part of your business strategies. It provides a complete picture of what your company is doing, but it also helps you compete and set your sights on the future.


Metadata Automation already powers thousands of organizations, so why not do it in yours? At Arkon Data we have an efficient platform that will help you automate the status of your metadata and keep updating it to become one of your main and most valuable business assets.

 

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1.  Ben Luktevich, 2023.