Taking Data to New Heights with a Modern Data Architecture

PinIt

As the market for cloud data warehouses continues to grow, so does the value of data as an asset.

Since the introduction of their diagram positioning the cloud data warehouse (CDW) in the center of a company’s “modern data architecture,” the Andreessen Horowitz model has become an important topic of discussion among those in the data and analytics sphere.

More experts are viewing the model as the ideal standard for the storage and usage of data for modern enterprises. However, the most provocative undercurrents of what the model presents relate to current and potential data analytics platforms looking to provide clients with ways to use their data for product analysis, testing, campaign management, and more.

These impacts are far-reaching.

Simplifying Cloud Database Access and Why It Is Important

Data platform providers who fail to adapt and work within the framework of the CDW are quickly falling out of favor and becoming dated technology. These outdated models include companies that do not support direct access to data in a CDW, requiring proprietary storage and software that relies on replicating data before it can be made available to analytics platforms, dashboards, or other uses. Clients are moving away from these outdated models to revolutionize antiquated ideas and shift the tide away from traditional structures to ultimately break the facade that clients can’t break free from previously imposed data constraints.

With current company structures catching up to the idea of the necessity of a data warehouse, the adoption rate is growing as more enterprises are introduced to new ways to approach their data. This adoption will continue to threaten the current providers who do not support direct access to the CDW or accept it as the single source of truth.

Building the colonnade

Clients utilize their data in three distinct ways. They collect it, they store it, and they use it. While this process is straightforward and linear, the influx of vendors with complicated systems has added an unnecessary layer by requiring proprietary storage systems or data replication. The entrance of new vendors cutting out this storage and replication requirement is pushing back against the status quo.

To further the juxtaposition between the complicated systems and the linear pathway to data utilization, vendors frequently lack any sense of data integrity. This lack of data integrity leads to failure in adhering to data reporting standards. The introduction of unhindered access to data through the CDW serves as a warning for these vendors.

With vendors increasingly using their proprietary standards and requirements, clients constantly have to adapt their existing information to fit new platforms and fit into new structures. This constant adaptation has deterred many clients from switching vendors should they not be happy with the value and quality. The defining difference of the CDW? Data governance tools used within the CDW can quickly identify and address any quality concerns that a client may encounter.

In addition to transforming existing data to fit within the constraints of a vendor’s requirements, not having direct access to that data means having the additional time-consuming task of cleaning up the data to prepare it for goal-driven analysis. The mitigation of these roadblocks comes from a central organizational structure whereby the cloud data warehouse is positioned at the center of the organization’s data architecture.

The CDW, therefore, creates a competitive advantage over those vendors that continue to require data to be collected and stored within proprietary databases.

See also: Data: The Competitive Differentiator for Innovation

Shifting the framework

What are the repercussions of offering products that are incompatible with the structure of the CDW? When viewed in terms of the Andreessen diagram, the value of these enterprises will shift up and to the right. All roads lead to (and from) the CDW.

The winners in the cloud data space will be those who streamline their processes and eliminate data replication with unnecessary steps. Like BigQuery and Snowflake, these solutions will continue to lead the charge and yield tremendous value from their innovations.

Simplifying Cloud Database Access and Why It Is Important

In response, the shift away from the traditional big players like the ubiquitous analytics stacks and cloud data warehouse-incompatible platforms is inevitable. New players in the data warehouse space are gaining billions of dollars in enterprise value, which only solidifies their place as viable competition for the data platforms of old.

This shift has already begun.

The entrance of new companies vying to take advantage of the rise in CDWs is gathering steam. Dozens of these companies, such as Hightouch, Census, and dbt, have been rapidly growing within the past year or more. They can provide clients with the tools and ability to streamline the process of delivering data, empowering teams to access the CDW in ways not seen before. What used to require a team of engineers now offers data straight to product and marketing teams with a few simple clicks.

See also: Okay, Your Data Is in The Cloud. Now What?

Breaking the facade with a modern data architecture

The introduction of the architectural framework of the CDW has introduced a realm of possibilities when it comes to data solutions. For example, clients are relieved of their reliance and dependency on a single vendor’s proprietary storage and access solution.

Once clients are free from proprietary vendors’ constraints previously imposed upon them, data becomes easily malleable and accessible. The client will instantly realize the performance improvement when compared to the tools and processes they have previously accepted as standard.

Analytics researchers at IndustryARC have forecasted that the market for the CDW will reach over $39 billion by 2026. CDW adoption and innovation continue to become the standard in company data structures, with modern data architecture allowing customization for individual needs and preferences. The strength of this architecture falls into the enterprise’s hands. Still, the most significant consideration for modernizing data begins with the idea that data is part of a business asset list.

As the market for CDW continues to grow, so does the value of data as an asset. The more usable the data gleaned from analysis is, the more value that data has for the corporation.

The switch to CDWs over traditional data storage providers also allows for an expansion of options and flexibility within the corporation and the ways in which they support their own data. The elimination of compatibility concerns also means that vendors will need to consistently offer top-tier value to their clients since data in the CDW is easily accessible to another competitive product should the client wish to make a change. With a broken monopoly, the power is given back to the client to develop and adopt complementary technology to support strategy and increase data value.

The emergence and rise of the CDW and the growing shift toward its adoption will continue to add to enterprise value for some vendors while threatening others. By all indications, including valuations and funding rounds, the CDW will continue disrupting monolithic stacks, coming out on top in the data revolution.

Simplifying Cloud Database Access and Why It Is Important

Jeremy Levy

About Jeremy Levy

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.

Leave a Reply

Your email address will not be published.