How has the recent turmoil within the OpenAI offices changed your plans to use GPT in a business process or product in 2024?
Increased uncertainty means we are more likely to evaluate alternative AI chatbots and LLMs.
No change in plans, though we will keep an eye on the situation.
With Sam Altman back in charge, we are more likely to go all-in with GPT and LLMs.
What recent turmoil?
Cloud Native Ecosystem / Cloud Services / Data

Bobsled Offers Platform-Neutral Data Sharing Service

Bobsled offers a cross-cloud data sharing service and announces a $24M Series A funding round, led by Greycroft and Madrona, to build it out.
Apr 27th, 2023 11:25am by
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Bobsled, a new venture based in Los Angeles, this week introduced its Data as a Service (DaaS) sharing platform and highlighted the data economy business requirements that are its underpinnings. The company also announced its Series A funding round, led by Greycroft and Madrona Venture Group.

Bobsled is working to make data sharing a universal prospect, providing connectivity to the major public cloud and data cloud platforms (including Microsoft Azure, Amazon Web Services, Google Cloud, Snowflake and Databricks) and providing the full plumbing necessary for dataset trial, subscription, version control, distribution and telemetry. Bobsled also supports delivery to numerous levels of the modern data stack, including data warehouse, data lake, notebook and business intelligence (BI) platforms.

Boblsed’s co-founder and CEO, Jake Graham, previously led the development of Microsoft’s Azure Data Share service, providing Bobsled with concrete knowledge of how to provide a sharing service, as well as a contextual understanding of what’s lacking in existing data sharing platforms. Additionally, as a result of the financing round, Bobsled is adding Greycroft Principal Brentt Baltimore, Madrona Managing Director Soma Somasegar, and .406 Ventures Partner Graham Brooks to its Board of Directors. Madrona was one of Snowflake’s early investors and Somasegar ran Microsoft’s Developer Division for several years, bringing even more domain expertise to the table.

A Contemporary and Legacy Need

For about as long as data has been around, there has been a need to share it, within teams, across business units and between organizations. The effort around doing so goes back decades and has engendered its own slate of acronyms and technologies. Approaches have included the generation of CSV (comma-separated values) “flat files” from the mainframe, more formal use of EDI (Electronic Data Interchange) across VANs (value-added networks), and erecting FTP (file transfer protocol) sites to allow parties to download data feeds. In addition to CSV and similar delimited text formats, data sharing provided the inspiration for longstanding formats like XML (Extensible Markup Language) and JSON (JavaScript Object Notation), as well as newer formats like Parquet that have given rise to the modern data lake.

But providing these technology nuts and bolts doesn’t constitute a true sharing service, any more than the provision of phone lines and email provides for customer service. Instead, these technologies have had to be cobbled together by technology teams, typically in an ad hoc manner, in order for data-sharing workflows to be operationalized. As a result, until recently, these efforts have been bespoke, at best.

Meanwhile, with the rise of the data mesh approach to data management, and its constituent innovation of “data products,” the demand for data sharing has grown, and budgets have materialized to make that demand a concrete business opportunity rather than a mere enthusiast wish-list item.

Efforts to Date

Critical mass has started to form in the last few years around more modern data-sharing protocols. Microsoft introduced Azure Data Share back in 2019, and has morphed it into Microsoft Purview Data Sharing. Databricks built the Delta Sharing protocol an open sourced it under the auspices of The Linux Foundation. Snowflake introduced Snowflake Data Sharing a while back, allowing a virtual warehouse interface to be built around shared data. Numerous vendors have also established data marketplaces to help organizations get to and use relevant third-party data sources.

But these protocols tend to be limited in scope and/or versatility. Purview Data Sharing works only between Azure Data Lake Storage (ADLS) Gen 2 or Azure Blob Storage accounts. Snowflake Data Sharing is, as the name would imply, something that gets implemented within Snowflake’s “data cloud.” Delta Sharing is more flexible, for a few reasons: it’s open source, it’s a protocol rather than a feature, and it can be integrated at the data lake, data governance, data developer, or BI tool layer of the modern data stack. Nevertheless, the protocol’s most concrete implementation as a full service is Databricks Delta Sharing.

Sharing Is Caring; Integration Brings Agitation

While data sharing has historically facilitated point-to-point data transfer, the modern crop of data-sharing platforms looks to provide discovery and connectivity, too. Bobsled is all-in on that reimagining of the space and it is explicitly looking to help eliminate the creation, maintenance and customization of data ingestion pipelines, in order to minimize complexity and (earnestly) compress time-to-value.

Sometimes the best new technology categories aren’t the ones that bring about some raw, novel innovation, but instead create adoptable platforms around things that numerous organizations have been building themselves, repeatedly and informally, often driven by urgent requirements that don’t leave time or budget for fit, finish and resiliency. A solid data-sharing platform looks like it falls into this latter category. And, as a data-sharing provider that operates independently of any particular cloud or data platform, Bobsled may bring the neutrality necessary to provide cross-platform versatility, in addition to base functionality.

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