There’s no denying that data is one of the most critical assets for an organization. When data is trustworthy–and used in the correct context to help make better business decisions–it can change the way companies interact with customers, comply with regulations, make informed decisions, create smoother workflows, and beyond. Unfortunately, data is sometimes viewed through the scope of an overwhelming influx of information rather than your company’s product.

What do we mean by this? 

Today, we’ll dive into the idea of why treating data as a product can be infinitely beneficial for companies, their data citizens, end-users, and beyond.

What exactly does it mean to treat data like a product?

For a moment, think about data in different terms. Instead of complex numbers and figures, view each data set as an ingredient or product sitting on the shelves in a grocery store. When you walk into a grocery store as a consumer, there are a few things you’d hope to see.  First and foremost, you’d hope that your groceries are organized and easy to find, right? If you go looking for oranges at the store, it’s expected that those oranges are on the right shelves. That’s just an anticipated part of your grocery store consumer journey. Further, you want to make sure your ingredients are correctly cared for, too, right? You’d hope you wouldn’t see a giant pile of bruised, dirty oranges somewhere in the middle of the store. You want your oranges (and all your groceries, really) to be clean, trustworthy, ready for consumption, and easy to access. 

The same goes for your data. 

Productizing data is about looking at the data you collect and understanding it as something that will impact those downstream from it–your data citizens, your end-users, and more. Treating data like a product is about understanding it and is just like treating your grocery ingredients as products. You need to care for your data, organize it, make it easy for data citizens and end-users to find, trust, and use. 

And as an organization, it’s up to you (and your appropriate data teams) to organize that data and treat it like a product. Just like you wouldn’t dump a massive collection of oranges in the middle of a grocery store and ask your customers to come in and pick through to find an ideal orange, you’d deliver it as a product that’s easy to access, easy to find, streamlined, and trustworthy. 

Accessibility is also a big part of treating data as a product. Elements of that include making someone’s experience with data welcoming, intuitive, and positive. So, going back to that grocery store metaphor, you’d want to make sure that buying oranges at the grocery store wasn’t just streamlined, it was accessible. If it was ultimately confusing to buy oranges, every other effort you put into stocking your store with oranges would be moot. 

The benefits of treating data as a product 

Productizing data can benefit both your organization at large, individual departments, data citizens within your organization, and of course, your end-users. How, exactly? Here are just a few ways data-as-a-product practices can elevate your organization’s data strategy. 

Empowers data citizens 

It’s no secret that data citizens, especially those who aren’t experienced in data, can sometimes feel overwhelmed by influxes of data sets. Productizing data can take some of this complexity out of data implementation because, when done right, it boils down data sets into bite-sized chunks that are easy to govern and even easier to understand. 

Governing and managing data all at once can be an insurmountable task. Data-as-a-product allows your organization to put a manageable box around your data, offering something valuable to your data citizens that empowers their data literacy. Translation? You’ll make accessing, trusting, and using data more straightforward than ever for your data citizens, meaning you’ll empower more wins along the way. 

Improves data quality 

The sticking point of data lakes and influxes of data is that all that data is often conglomerated in a single location–but it’s impossible to tell if that data is high-quality or trustworthy. One of the cardinal rules of data is that it’s only truly useful if it is trustworthy and provides real insight you can rely on. 

Let’s go back to that data-as-an-ingredient analogy. If you’re trying to create a delicious recipe that includes oranges, it makes sense that the quality of those oranges will directly impact the recipe as a whole. This means the finished product depends heavily on the ingredients’ quality, or rather, the downstream impacts will either be negative or positive based on the ingredients. When you treat data like a product, you organize it, identify governance, improve the quality and usability of that data, and improve and impact any data project as a whole. So, the quality of that data is going to impact everything that happens downstream of that data. 

Enhances context and streamlined accessibility 

Data, though helpful, can complicate things when the context isn’t properly included. If your department (let’s say marketing) requests marketing data sets from your data team without context for your campaign, you’ll likely end up with a chunk of data sets that don’t translate, don’t make sense to you, and don’t provide you with the insight you’re looking for. When data is treated as a product, the proper context is assigned to it, making it easier to understand, access, and use–especially for data citizens who might not be experienced in the data world. Additionally, domain ownership context and cross-functionality of data become more streamlined, and data becomes easier to interpret, ensuring that departments can use the data they need for their purposes within a context that makes sense. 

Changing the way you use and incorporate your data

Extracting all the value out of your data is crucial for not only setting up an insightful data strategy but also for ensuring that your data culture is accessible and streamlined for your data citizens and end-users. Productizing your data is a big part of that. 

With the right tools and partners, like Collibra and Google Cloud, your organization can unlock the benefits of productizing data and learn how to resolve data governance. Ready to learn more right now? We can help. Listen to our Google Summit session to discover how to treat data as a product and incorporate these best practices into your organization’s data strategy.