Implications of the New Data Architecture- Winners and Losers

Implications of the New Data Architecture- Winners and Losers

Venture capital firm Andreesen Horowitz recently got people talking thanks to a diagram it developed that put the cloud data warehouse (CDW) directly at the center of what the firm characterized as the modern data architecture.

Within technical circles, the model Andreesen published is increasingly regarded as the ideal way of storing and using data within an organization. What is perhaps most interesting are the implications the model presents for data vendors, as well as the vendors that seek to become clients' preferred means to leverage data for testing, campaigns, product analytics, reporting, and more.

Those implications are profound.

This is especially true for vendors whose solutions don't work within the ideal, CDW-centric framework. This includes, for example, monolithic stacks such as Adobe that demand proprietary storage, as well as replication-dependent analytics platforms. While every client company's architecture may not match the ideal model yet, as more of them adopt a new approach to their data, vendors that can't adapt will face significant threats.

Collection, storage, and usage

What client companies do with data comes down to these three activities: They collect it, store it and use it. Over time, this fairly straightforward and linear concept has been complicated by the number of vendors that require their own storage platforms or data replication, a still-common requirement that new entrants are gradually upending.

Further exacerbating the situation is the frequent lack of data standards and data integrity. Yet, as "Game of Thrones" taught us, "Chaos is a ladder," and companies have exploited our passive compliance with data chaos to the tune of hundreds of millions in revenue and billion-dollar valuations. The rise of the cloud data warehouse is putting these companies on notice.

Clients are growing weary of taking on yet another vendor with proprietary data standards or replication requirements. It's easier than ever to begin using a CDW, and there are plenty of data governance tools, too, to help address data quality issues. Such tools should be used in concert with concise data standards and adherence across the enterprise.

By orienting the cloud data warehouse at the center of the organization's data architecture and connecting it to analytics tools or other platforms, it's much easier for clients to ensure each user is working with the same, clean data. Data maintenance after the fact is a time-consuming and expensive proposition, and keeping these issues from happening in the first place has multimillion-dollar implications to the enterprise.

Looking forward, vendors that easily connect to the CDW are much better positioned to succeed than those that don't — companies, for example, that operationalize data but first require it to be collected or imported and then stored in a proprietary database.

Value, both destroyed and created

So what happens to the enterprise value that exists among companies whose products are simply incompatible with the notion of the cloud data warehouse? Their value will shift top-center and to the right if you think of it in terms of the Andreesen diagram.

Data warehouse solutions like Snowflake and BigQuery will continue to reap benefits, and so will vendors that operationalize data directly from the CDW, without data replication or unnecessary, redundant processes.

Billions in enterprise value will move to these companies and away from legacy, monolithic stacks like Adobe Marketing Cloud; customer data platforms like Segment; CDW-incompatible analytics platforms like Amplitude and Mixpanel; and many others. The writing is on the proverbial wall.

We're already seeing value shifting to the dozens of companies that have sprung up in recent months to take advantage of the rise in CDWs — Hightouch, Census, and dbt, to name a few. They also offer the ability to deliver results that would have taken an entire team of engineers just a few years ago. Now, with the right tools, you can operationalize data from the CDW with a few clicks, empowering product teams, marketing teams, and others like never before.

Clients are the real winners

With the focus of the architecture on the CDW, it opens up a whole new realm of solutions. Client companies aren't beholden to a proprietary stack where they can only use one vendor's analytics solution or content tool, for example.

Free from these limitations, if you need an A/B testing tool, plug one right into the cloud data warehouse. If you need a messaging platform or a product analytics tool, plug one right into the cloud data warehouse. It's far easier now for a client to build a custom stack that best suits its needs.

Clients also can realize performance gains compared to what they have (grudgingly) become accustomed to.

"Cloud-based architectures and microservices-based designs using Web technologies are decoupling from the monolithic stack," Gartner analyst Jason Wong said last year. "These newer platforms and the ones that have modernized to cloud-native don't have those performance issues."

Proprietary stacks' losses are also client companies' gains because switching costs are likely to decrease. Vendors that connect directly to the cloud data warehouse will have to consistently deliver value, lest clients simply find another option since multiple tools won't necessarily fall within a single vendor's near-monopoly of in-system offerings.

While enterprise value shifts toward the CDW and the vendors that play nicely with it, control of both the data and the stack is on the fast track back to the clients.

Author

Jeremy Levy is CEO and co-founder of Indicative, the only product analytics platform for product managers, marketers and data analysts that connects directly to the data warehouse. He is a serial entrepreneur and a veteran of New York City's Silicon Alley. Jeremy co-founded Xtify, the first mobile CRM for enterprise, acquired by IBM in 2013. He also co-founded MeetMoi, a pioneering location-based dating service for mobile sold to Match.com in 2014.

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