What is a Metadata Framework?

Believe it or not, the world would completely fall apart without metadata frameworks and a data governance framework. Imagine if your local grocery store had no shelves, signs, packaging, or even a building. What if it was just a pit the size of Texas that had been filled from end to end with loose products of every category? Picture thousands of people digging through the pit, hoping to find what they need. 

It would be madness and complete chaos, but that’s what a world without metadata frameworks looks like: a gigantic pit of raw data that’s nearly impossible to navigate.

From the pit to products

Obvious though it may seem, consumers and providers don’t want a pit of raw data products. They need a successful marketplace where they can easily discover, identify, and acquire products—a marketplace with strict governance in place to enforce quality standards. 

Getting from the data pit to a product marketplace begins with metadata. Metadata takes all of that loose data and adds basic information about each asset on the metaphorical product packaging. That basic information typically includes a summary and description of the data, including things like what it contains, when it was created, who created it, and how it has been modified. Metadata helps you quickly determine whether or not an asset is something you want. 

In our imagined scenario, however, you’re still knee-deep in a big pit trying to read all of the labels. The next step is to build shelves and aisles, or, in this case, to implement a metadata management solution that organizes all these data assets in a convenient, easy-to-navigate way. Metadata management frameworks provide the tools for arranging data products in an orderly fashion that makes it convenient to find exactly what you want and which assets are relevant to your needs.

Metadata management means that instead of digging through loose products, users are now happily strolling through the equivalent of well-organized, well-stocked grocery store aisles. Users can feel confident that every item on the shelves has been manufactured and stored to meet quality standards.

Put simply, metadata takes all of the unwieldy mess of information across the systems in your organization and provides context for each data asset — just like the information on nicely packaged products at the grocery store. This context, in turn, makes it clear how the organization has structured, maintained, and used that asset.

Into the data marketplace

Metadata management software helps integrate, manage, and publish data assets so people can search for and share them. Typically, a metadata framework contains an organized repository for metadata — not unlike grocery store shelves. This framework allows people to quickly locate and manage all the various assets and data sources the company has created and stored across multiple systems. 

To use a more industry-appropriate metaphor, this repository creates a data dictionary for your assets that contains robust search functionality so users can easily find what they want. 

Metadata frameworks usually contain data lineage information that tracks a data asset along its entire lifecycle. Imagine if you picked up a box of cereal on a grocery store shelf, and, on the back, you found a description of the lifecycle of the product going all the way back to the farmer’s field where the ingredients were harvested. That’s the kind of lineage information a good metadata framework provides for a data asset, ensuring data quality.

Without data quality standards firmly in place, it’s very difficult to maintain data integrity. There’s no way to know if all of your data is accurate and consistent, and bad data leads to bad decision-making from both providers and consumers. Metadata frameworks provide both consistent data quality and robust data governance.

The power of productization

A solid metadata framework is pointless without meaningful productization. If you want to get your data assets into the hands of consumers, you have to transform those assets into products you can share externally with a target audience. Productizing your data enables consumers to access and derive value from your data. 

A grocer doesn’t simply dump a bunch of loose cereal on a shelf and set up a sign beside it that describes what it is. No, they choose neatly packaged cereal to present publicly in a way that makes it easy for consumers to find, understand, purchase, and derive value from the product. 

The data marketplace equivalent of loose cereal is bulk data providing, which puts all of the burden of finding value on the data consumer. While metadata frameworks resolve this problem by making data assets searchable, a data marketplace puts those assets in front of consumers. Consumers have to know where they can go to metaphorically stroll the aisles, follow the signs, find the products they want on the shelves, and derive value from them.

What is data marketplace?

Many providers simply dump their assets onto a cloud service like Snowflake or AWS Data Lake and assume the data-sharing features of those services will be sufficient. Doing so, however, is the equivalent of a grocer scattering products at random across a warehouse. 

If you want to productize your data assets and get them into the hands of consumers, you can’t simply dump them out into the world and hope consumers will find them. Start thinking about your data assets like a product manager. You need a data marketplace that facilitates the buying and selling of your products. This approach is key to productization.

Now, you might think, “Fine, we’ll build our own data marketplace. How hard can it be?” The answer is, “A heck of a lot harder than you realize.” It’s no different than saying, “We want to sell our brand of cereal. Let’s just build our own grocery store chain to sell it.” No sane company does that.

The complex logistics involved in creating and building a store to showcase and present available products to consumers can be overwhelming, even under the best circumstances. In the same way, trying to build your own data marketplace with built-in productization and adherence to governance and compliance is an incredibly complex endeavor — and it’s entirely unnecessary!

Getting in front of consumers

The better alternative to creating your own marketplace is to work with an existing, prebuilt data marketplace that already has native, automated productization and strict adherence to governance and compliance to keep you on the straight and narrow.

Remember, the goal of productization is to ensure consumers have everything they need to derive value from your data by making it readily available and easy to acquire. That includes all of the product’s metadata and a lineage that goes all the way back to the source systems. Creating a marketplace on your own that can accomplish these goals demands an inordinate amount of money, time, and resources, and again, it’s unnecessary. Robust, easy-to-use data marketplaces already exist, ready and able to take your data products and put them in front of consumers. 

While building your own data marketplace may give you more ownership and customization options, licensing an existing marketplace costs less to run. Additionally, it gives you access to expert developers who can troubleshoot for you and provides data product delivery mechanisms to get your product to consumers much faster.

The journey of metadata frameworks

The irony of our Texas-sized pit of raw data is that the assets in the pit had the same potential value for consumers as the products neatly arranged on the store shelf. However, consumers simply couldn’t realize the value because they had the nigh-impossible task of trying to figure out which assets were available and useful. The best data in the world does little good if the right people can’t find it, identify it, and access it. 

A metadata framework with well-built data management software tools does just that for all of your data assets. Revelate’s fully automated data marketplace creates an environment where consumers can easily discover and purchase your productized assets. 

From raw data to data products that consumers in the marketplace can readily find and use—that’s the journey made possible by metadata frameworks and Revelate’s data marketplace.

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