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Security & Compliance
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Sample Snowplow Data
Sample Modeled Data
Sample Modeled Data
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Snowflake
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Databricks
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Azure OneLake
AWS
AWS Redshift/S3
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Google BigQuery
Kafka
Apache Kafka
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About Snowplow

Snowplow, the global leader in customer data infrastructure (CDI) for AI, enables every organization to own and unlock the value of its customer behavioral data to fuel AI-driven marketing, digital products and services, customer experiences, and fraud mitigation.

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  1. Home
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  3. Data As A Product (DaaS)

Data as a product (DaaS)

Latest Articles

Data Discussions: Lodi Elaridi, Data Product Manager from Skyscanner

Data Discussions: Lodi Elaridi, Data Product Manager from Skyscanner

The Snowplow BDP management console runs on purely functional Scala and the Typelevel stack. This is how we set out to integrate with the Open Policy Agent and implement fine-grained access control.

Proving the value of your data

Proving the value of your data

Data teams are often met with cultural and communication challenges in their organization. We talk to data teams and data practitioners all the time and the same question keeps coming up: “How can we prove the value of our data, and the work we do?” [Webinar: How to get your data team a seat at […]
Future-proofing your organization with a universal data language

Future-proofing your organization with a universal data language

In our content series on Treating Data as a Product, we explored the major challenges organizations face when it comes to keeping productivity high.  In our conversations with data leaders, we learned that communication – particularly how people interact with each other around data (especially behavioral data, which is rich, voluminous and complex by nature) […]
A reporting template for data collaboration

A reporting template for data collaboration

Communication among skilled stakeholders in a project around data can be challenging. As we discussed in our post around the challenges of working in data, one of the biggest hurdles for a data team to overcome is communicating with their colleagues and stakeholders to deliver data projects that drive value. I also know from personal […]
How data storytelling can make your insights more effective

How data storytelling can make your insights more effective

So, you have done it. Your trackers are in place, your data is clean, modeled and easily available. All the information you need is at your fingertips. But what about the business side of your company? What about your colleagues in different departments and teams, who may be completely unaware of  where this data comes from […]
Reducing data downtime with data observability

Reducing data downtime with data observability

Data downtime is a hot topic in data at the moment, and for obvious reasons. The cost of data downtime – a term coined by Monte Carlo to refer to periods where data is partial, erroneous, missing or otherwise inaccurate – can be significant for companies who rely on behavioral data for decision making.  If […]
The challenges of working in data

The challenges of working in data

It’s an exciting time to be working in data. The opportunity for data teams to make an impact is huge. They have more tools at their disposal, with exciting technology hitting the market each day, than ever before.  Hiring in data, despite a slowdown in 2020, continues to be hot, with new job titles emerging […]
Breaking communication barriers with a universal language

Breaking communication barriers with a universal language

Download the full eBook Treating data as a product As companies increasingly invest in building out their data capability, it’s important to keep the ultimate goal of collecting and analyzing data front of mind: to take data-informed actions that drive business value. However, as we discovered by talking with our customers, communication barriers are the single […]
A guide to data team structures with 6 examples

A guide to data team structures with 6 examples

The business world is witnessing the rise of the data team. When companies first worked with data departments, it was in fragmented silos, with marketing teams, business intelligence (BI) teams, data scientists, engineers and analysts within product teams, each handling data individually. Since then, data has become recognized as a valuable business asset, and the […]