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Most organizations working on artificial intelligence (AI) and advanced analytics projects tend to use data from existing systems like Google Analytics and CRMs. These sources offer plenty of information to work with, but they are also disparate in nature, which means the data they provide comes with varying structures (imagine different field types) and different levels of granularity, quality and completeness. 

This makes it difficult for the organization to use the data as-is and adds the technically challenging and time-consuming element of data wrangling to the process – where teams have to work to clean, organize and transform the data into a standardized format for use. Plus, it also creates compliance issues since it is very difficult to track data lineage from a collection of black-box SaaS applications.

Creating data with Snowplow

To solve the problem, London-based Snowplow Analytics is offering enterprises a platform to generate structured behavioral data assets (describing the behavior of customers, the actions and decisions they make, and the context of those actions and decisions) that are customized to suit specific AI and BI applications and remain fully compliant at the same time. The company today announced it has raised $40 million in a series B round of funding.

“Behavioral data generation is about connecting the events together that a customer, machine, or application might witness throughout time. This allows the behavior to be analyzed in a highly accurate and secure manner, including being compliant with European third-party privacy rules,” Alex Dean, the cofounder and CEO of Snowplow, told VentureBeat.

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The platform delivers AI/BI-ready data directly to the data warehouse or lakehouse of the customer, complete with a common schema that can be used to train models, streamed for real-time applications or enriched with third-party data and systems to meet future use cases. This means no more hefty investments in finding, cleaning and preparing data for analysis. 

Users handle every aspect of the platform through a dedicated console, including defining policies on how to create this data in the first place and enabling its sharing and management. According to the company, more than 10,000 enterprises, including Strava, CNN and Software.com, are already using Snowplow to create data for various AI and analytics applications. 

“Snowplow is unique in the way that it solves the problem with informative, accurate data. Other companies create behavioral data (e.g., from web and mobile) but typically to power their own applications in their own schema — examples include digital analytics solutions (e.g., Google Analytics) and CDPs (e.g., Segment, mParticle). However, unlike these solutions, Snowplow technology is focused on delivering the best AI and BI-ready data directly into the data warehouse (or lakehouse) to power data applications in a universal data language — this is not an export of a dataset that is powered to do something different,” Dean added.

Plan ahead

With this round of funding, which was led by global venture capital firm NEA, Snowplow will focus on growing its footprint, both in its home market and abroad. As part of this, the company plans to expand its team and bring support for ever-increasing data types.

“There are a number of unique industry use cases that benefit from this type of data approach … We’ll be making further announcements on the roadmap in the fall,” the CEO said.

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