Investment Funding

Money is flowing into tools for the data market.

It is still less than two years since Snowflake floated on the New York Stock Exchange, raising $3.4billion – one of the largest flotations by a software company in corporate history.

The rapid growth of the American cloud-based data warehousing company has helped create a large tailwind of business opportunities across the industry.

The latest Technavio report in February confirmed its analysis – published in late 2021 – that the Cloud data warehouse market is set to grow by $10.42billion by 2026 – an annual growth rate of some 22.5 per cent.

As a result, investment funds have been flowing strongly into the sector, as well as Snowflake three of the other companies Datavault partners with have secured significant external funding in 2022 already.

dbt Labs – the Philadelphia-based company formerly known as Fishtown Analytics – raised $222million back in February. This valued dbt Labs, who amassed some 9,000 users in just six years, at $4.2billion, when analysts had predicted any eventual floatation could top $6billion.

We also enjoy strong relationships with London-based DataOps.Live, who raised $10.3million with Snowflake Venture and Anthos Capital.

Dataops.live helps organisations secure and govern their data in the Cloud in an agile way, by using the same methods found in DevOps for other computer software engineering.

The Dataops.live platform automates the building, testing and orchestration of data pipelines, to create full data applications based on Snowflake.

That enables data product teams to build and adapt data products much quicker than in the past, without compromising data governance or data security.

Not only can that bring new value, but also reduce the time it takes to bring new insight and value to the business.

Snowflake Ventures head Stefan Williams said: “DataOps.live enables organisations to build, test and deploy Snowflake products and applications, the

same way they do software applications.

“They increase speed of development and accelerate adoption, while maintaining governance and security.

“By expanding our partnership with DataOps.live, we offer joint customers the ability to collaborate with confidence inside their organisations and beyond.

“We look forward to supporting the DataOps.live team through the next stages of their growth.”

Software-as-a-service (SaaS) company, VaultSpeed, specialising in data warehouse automation, has raised €3.6million via Fortino Capital Partners. VaultSpeed’s data warehouse automation software also speeds up the cycle of designing, building maintaining a Data Vault.

The VaultSpeed tool integrates data from multiple sources into the Data Vault so that it can be analysed across the enterprise – reducing project risks and accelerating the time to market.

Chief Executive Piet de Windt and Chief Technology Officer Dirk Vermeiren founded VaultSpeed just two years ago backed by The Cronos Group and its seed fund CoFoundry.

The new investment will help VaultSpeed scale its business and invest in its product to serve and expand its international client base.

Fortino Capital’s managing partner Duco Sickinghe said: “We have seen a rapidly increasing traction for Data Vaults over the past years, and are truly excited to support Piet De Windt and Dirk Vermeiren in accelerating their growth.

“VaultSpeeds’ data warehouse automation tool plays a crucial role in helping customers increase their agility, while responding to strong time-stamping, auditability and traceability requirements.”[/vc_column_text][vc_empty_space][vc_column_text]Datavault CEO Neil Strange said: “Raising capital sums like these, demonstrates that the market for data platforms is showing little sign of slowing down.

“We are seeing from our clients an increased urgency in the shift away from legacy data warehouses, and the many problems and pitfalls they can create, switching to the Cloud instead, combined with the greater use of automation tools and DevOps, means the Data Vault method is increasingly popular as part of modern data architectures.

“A well-designed and operated data platform can service the needs of many different use cases including self-serve analytics and data science applications utilising machine learnlng (ML) and artificial intelligence (AI).