April 14, 2024
Switchboard recipe authoring


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Switchboard recipe authoring
Switchboard recipe authoring. Credit: Switchboard Software

Switchboard, a company focused on data product development for business users, is announcing today a $7 million series A round of funding led by GFT Ventures and Quest Venture Partners. Switchboard, founded by Google BigQuery launch team members Ju-kay Kwek and Michael Manoochehri, offers a platform designed for the creation and operation of data products that does not require the talents of specialized data teams. The company’s goal is to level the playing field so organizations beyond the tech giants can own and wield their data as competitive assets. Switchboard cites such companies as DotDashMeredith, OrangeTheory Fitness, and the Financial Times as using its platform to do just that.

Data products, a concept popularized by the “data mesh” approach to business domain-oriented data and analytics, are applications, APIs, data feeds or simple datasets that are owned, supported and internally marketed by enterprise business units, and made available to other such groups. Developing data products has, for the most part, required the work of data engineers and analytics specialists, a fact that has stymied the decentralized approach to data-driven business that the data mesh paradigm seeks to enable. It’s that problem space that Switchboard seeks to address.

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Democratizing data product development

Switchboard’s unique value proposition is making data product development accessible to the business users who typically possess the contextual knowledge of the data in the first place. Additionally, Switchboard is a SaaS platform that avoids the need to provision and manage dedicated infrastructure, and it’s focused on production hosting and management of the data products, in addition to their development and testing. That enables business users to handle the entire lifecycle of data products, allowing highly specialized data engineering teams to focus on more strategic, enterprise-wide projects and efforts.

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Switchboard is not just a tech platform — it’s focused on specific business use cases, with a template- and automation-based approach to implementing them. To begin with, the company is concentrating on digital media revenue and marketing scenarios and offers detailed templates for digital media campaign analytics. Switchboard plans to move on to other domains as the platform establishes itself.

Building blocks

The gist of Switchboard’s approach is to encapsulate industry best practices, and to bundle in SOC-compliant data management; proactive insights through such assets as out-of-the-box dashboards; and support for standard data sources paired with a high degree of customizability. Switchboard facilitates data transformation, blending, cleansing, verification and normalization, and can publish data products to cloud data warehouse platforms including Snowflake, Amazon Redshift and, of course, the Google BigQuery platform that the company’s founders helped launch.

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The Switchboard platform allows business users to encode their requirements and proprietary business rules as low-code polices; stores all necessary data source credentials in an encrypted key store; and facilitates authoring and re-use of data “recipes” (shown in the image at top of this post) for acquiring the required data. Switchboard also provides consolidated management of all relevant data sources and partner systems, including monitoring operational activity and providing centralized exception reporting.

Switchboard says it will use the funding round monies to invest in the platform and enable business users to do more with features enabled by machine learning. A next phase is to take the data products the company has worked on with some of its more advanced customers, and turn them into new templated data products included in the system, joining the digital media RevOps, campaign analytics, and programmatic reporting solutions that are already there.

Power to the business

The notion of putting data product development and even production DataOps into the hands of business users is a break with entrenched precedents. But even low-code specification of business rules, and understanding which data feeds to use and how to connect with them, is not for the faint of heart. Cofounder Kwek told me Switchboard typically dispatches a small team of “success engineers” (who are essentially data scientists) to its new customers, who typically take four to eight weeks to get up and running.

But even if some professional services and power-user skills are needed, leveraging automation and reusable business process specs to enable self-service data product development is both shrewd and laudable. If the approach works, it’s something other analytics platform vendors would do well to adopt.

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