Unlocking Value with Cloud Marketplaces

Where do you need your data most – and how easily can you access it?

I ask because getting trusted third-party data into your preferred environment has always been harder than it should be. It often involves downloading files, managing cumbersome ingestion processes, troubleshooting formatting issues, and manually stitching everything together – only to repeat the process with every new update.

Through our daily conversations with customers, it has become clear that there is a demand to access data where they already work – and increasingly, that is in the cloud.

That’s why it’s thrilling to see how cloud data marketplaces are rapidly evolving. These platforms are transforming how you discover, sample, and operationalize third-party data, and we’re proud to meet you there with high-quality, AI and analytics-ready  data products.

Ultimately, this reduces your overhead and enhances your efficiency, allowing you to move forward with greater confidence and informed insights and decision-making.

The Evolution of Data Marketplaces

First, let’s begin with some context. One of the challenges of the traditional marketplace is that, unless it’s well-structured and well-managed, it can feel overwhelming – it’s like stepping into a giant library full of options, but with no cataloging system to guide you in the right direction.

I, for example, am particularly passionate about location data that tells a story about the people and places associated with it. There are incredibly valuable insights to glean from this type of data.

However, if you’re browsing for location data in a marketplace and faced with dozens of different data providers, how do you know which one is right for your needs? Which data truly aligns with your use cases, quality standards, and overall expectations?

Even with your best attempt to choose the data that’s right for you based on limited information, you can end up going through those long onboarding processes to bring the data into your environment – only to discover that it’s not what you’re looking for after all. Then, it’s time to start the process over again.

That’s changing.

Today, modern cloud data marketplaces are becoming true points of delivery – where you can seamlessly search for data based on your use case, discover relevant and trusted datasets, view samples, and try them out instantly. The ability to sample data is especially valuable – this “try before you buy” approach is something that will continue to save you huge amounts of time, headaches, and frustration.

So, as you navigate these modern marketplaces, be sure that you understand not just what data is available, but how it can directly support your needs. And make sure you can try it out immediately.

What to Look for in a Trusted Data Product

Bringing all of this together, here are some key considerations to ensure you get the most value (quickly) from trusted data products as you explore these marketplaces:

• Try before you buy: Testing a sample helps validate structure, completeness, and relevance for your use case.
• Prioritize enterprise-grade, curated data: Look for data that’s already been validated, cleaned, and formatted for analytics.
• Check for interoperability: Products that use shared identifiers are easier to integrate and enrich – which makes our recent announcement of the Data Link partner program all the more exciting.
• Evaluate the metadata: Good listings include transparent documentation, sample schemas, an update frequency, and clearly defined intended use cases.
• Consider support and context: Well-managed listings should link to documentation, tutorials, or real-world applications.

Precisely in Your Cloud Data Marketplaces

At Precisely, we partner with leading cloud marketplaces to enable the direct delivery of data products to our joint customers’ cloud instances.

Within our extensive portfolio, you can choose from hundreds of datasets with thousands of attributes that enhance your internal data with the context you need to grow your business and reduce risk. This includes data for boundaries, demographics, places, properties, risks, and more.

Our goal is to make this data easy to integrate and access on the platforms where you already work, empowering you to make better data-driven decisions, enhance your AI models, and drive operational efficiencies.

To ensure your success, we continually collaborate with our partners – including Snowflake, Google Cloud, and Databricks – to further streamline these processes.

On that note, we’ve recently expanded our partnership with Snowflake – introducing two new Native Apps that enable you to perform geo addressing tasks and data enrichment natively within the Snowflake AI Data Cloud:

• Geo Addressing for Snowflake: Verify, standardize, and geocode addresses with high precision – down to the apartment or suite level. Autocomplete functionality makes workflows smoother, and data enrichment is streamlined with the ability to accurately connect datasets via our PreciselyID.
• Data Graph for Snowflake: This provides easy access to our extensive data portfolio. With a single API, you access flexible query capabilities, robust data enrichment, and enhanced data discovery.

We’ve also added more enterprise-grade datasets to the Snowflake Marketplace, including datasets for risk and demographics.

With these insights, you gain essential context that drives better decision-making and outcomes across industries such as real estate, insurance, retail, and beyond.

These innovations are designed to empower you to minimize your operational overhead while maximizing scalability.

Our partnership with Google Cloud is still in its early stages, but we’re already seeing some fantastic results with customers. One standout example is global residential real estate leader Keller Williams, a company that’s been leveraging our direct data delivery to power key initiatives.

Customer Highlight: Keller Williams

We’ve had a great, longstanding relationship with Keller Williams. The team had already been using several of our location-based datasets to provide consumers and agents with powerful, granular insights into details like property attributes, demographics, schools, and census boundaries.

Most recently, they reached out to inquire about receiving our data directly through Google Cloud. The team was seeking to reduce the time and friction associated with managing their data – large volumes of data that were frequently updated and required a lot of manual work and overhead.

They knew that cloud delivery had the potential to enhance their efficiency, which in turn would benefit their customers and agents with those critical insights, faster.

Cliff Miller, Enterprise Data Architect at Keller Williams, summed it up nicely: “The receipt, delivery, and processing of data is only valuable insofar as that it actually gets to where you want it to be to deliver the insights – to deliver the value that you want to derive from it.”

After evaluating their options, the team landed on Google Cloud as the best fit for their needs, and we’re incredibly energized about their results so far.

“We are leveraging this cloud compute ability to deliver large datasets in a much more friction-free manner. I think that’s a huge win,” Miller says. “That journey is really about helping our team members become more effective and more efficient with how we’re able to get data from point A to point B.”

Keller Williams’ move to cloud-native delivery is a win for consumers, agents, and the business as a whole. I think this is a great success story that speaks to the increasing demand for analytics-ready data available wherever and whenever it’s needed.

Meeting You Where You Work

It all comes down to this: high-integrity data should be accessible, usable, and delivered with the end user in mind. That’s why we’re expanding our presence in the world’s leading cloud marketplaces – and why we’re constantly investing in better delivery experiences, native apps, and seamless integrations.

Don’t hesitate to reach out to us if you’d like to learn more – and in the meantime, explore our offerings in Snowflake, Google Cloud, and Databricks.