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Apr 9, 2024

Don’t Let Architecture Terminology Get in the Way of How CDPs Can Power Your Business Outcomes

In the ongoing discourse over how CDPs fit within a Martech ecosystem, there is a divide over perceived advantages and disadvantages of a “zero-copy data” ecosystem. While we can all agree that “zero-copy data” is too vague to be taken at face value (I much prefer “data-in-place”) the argument is less about terminology than it is about which camp you fall into: CDPs working directly on a data cloud (“zero copy”), or CDPs that work indirectly with a data cloud (traditional). In the former, data-in-place or zero-copy simply refers to the CDP compiling, cleansing and making data ready for business use without having to move or copy the data, which is needed in the traditional construct.

Because the Redpoint CDP was designed from the ground up to be database agnostic, we sort of straddle both sides of the fence, advocating first and foremost for adaptability without tethering to a specific approach. We do not champion “zero-copy data” as materially better or worse than the alternatives, but we instead offer a flexible framework that aligns with diverse customer needs, offering a SaaS option, an option to run in a data cloud ecosystem, and an option for private cloud/on-premise. With a multitude of available configurations, customers have the freedom to tailor their CDP deployment according to their preferences and business requirements – both now and in the future.  Instead of worrying about where the data resides as a primary consideration, an adaptable platform allows the focus to be on cost reduction and performance. If you don’t believe a data cloud can meet your needs today, this approach allows for the adoption of a data cloud approach once requirements change in the future – or once data cloud technology “catches up” with the technical requirements that drive business outcomes.

With that said, let’s refute some of the arguments against running your CDP in a data cloud, looking at it from the perspectives of cost, security and agility.

A Careful Cost Calculation

On the cost front, the primary argument against a data cloud ecosystem is that it is more expensive because you’re running the CDP 24/7 instead of just for analytical jobs. Because data clouds charge when in use, the savings over a managed database might soon become costs. Those costs, however, are not a 1:1 comparison with a managed database, which can presumably better distribute compute cost (and hope for continued economy of scale). Because unlike a managed database, data clouds will absorb costs associated with supporting the database. This includes the need for skilled people to manage, care, feed and operate the database itself – including monitoring, keeping indexes up to data, security, governance, apps, controls, etc.

The total cost of implementation is a multifaceted consideration. By embracing a data-in-place approach within a data cloud environment, some customers may find that the flexibility, scalability, convenience and performance advantages provide a compelling, valuable long-term trade-off. The ability to scale resources dynamically, access advanced analytics capabilities, and integrate with a rich ecosystem of complementary services can translate into tangible business advantages.

Keep an Eye on Security

Turning to security, one argument against a data-in-place ecosystem is that a CDP must have keys for accessing needed data, which opens a potential line of attack for a bad actor to access data. While true, the same can really be said for any CDP. Zero-copy/data-in-place doesn’t claim to be more secure overall, but it does provide the customer – as the owner of the database – the tools to fully control data governance and monitor everything that is happening – who is using the data, how they’re using it, etc. If you’ve set up the proper security mechanisms such as ISO 2701, etc., then it will be inherently more secure than sending your data to a vendor and relying on the vendor’s security measures.

Some vendors opposed to a data-in-place framework use this security argument as an avenue to poke holes at the notion of a composable architecture, claiming that the more vendors your CDP works with, the more vendors have keys (read: access to) your data. One refutation of this point is that even a closed-system CDP has to move data in and out, with APIs, webhooks, etc. Second, in the event of a breach, it’s better to have a single shut-off mechanism than it is to ask a vendor to delete a copy of their data. Third, the whole argument about the supposed security risk is a strawman argument to begin with. May customers who choose to run a CDP in a data-in-place environment do so because the data cloud is doing the security work. That’s one of their huge selling points.

More Access, More Choice

And on the agility front, it’s important to keep in mind that ultimately a CDP is a means to an end. For closed-system vendors, the inescapable truth is that everything you need to consume data out of your CDP has to be connected to that vendor. For the sake of argument, let’s say it is less expensive to run your analytics dashboard in your CDP vendor’s managed data storage than an open data cloud. Well, what if you prefer a different analytics dashboard? Or have already invested in an analytics platform? Or, what if your data science team is already skilled in other tools that aren’t available directly within your CDP vendor? A composable architecture CDP running in a data cloud provides access to a far more robust ecosystem – hence, far greater choice – than a CDP on managed data storage. As with cost, for organizations prioritizing agility, innovation and time-to-market, the benefits of a data cloud ecosystem may justify the investment – leading to faster ROI and maintaining a competitive edge in rapidly evolving markets.

Ultimately, the decision to opt for a CDP within a data cloud environment is driven by a nuanced evaluation of business priorities, technological requirements and long-term strategic objectives. While cost considerations are important, they must be balanced against factors such as performance, scalability, security and ecosystem compatibility. Redpoint’s philosophy revolves around customer empowerment and adaptability. By focusing on use cases, performance and security, Redpoint enables customers to navigate the complexities of the CDP landscape with confidence, ensuring business outcomes remain paramount while delivering maximum value over time.

Steve Zisk 2022 Scaled

Ian Clayton

Chief Product Officer

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