Data Labs Look to Boost ‘Data Fluency’
As the role of the data scientist expands, so too does the “data lab” product category which seeks to merge data science with the enterprise plumbing required for data-driven decision-making.
Add to the list a new data labs platform from technology management consultant Kin + Carta, which seeks to meet the sharpened enterprise requirement for greater “data fluency” and accompanying analytics running on recently installed digital platforms.
Kin + Carta is releasing a data labs platform billed as a management hub that can be embedded into consulting and engineering services. Unlike current snapshot data science and engineering services, the Chicago-based tech consultant promotes its data lab as delivering integrated, real-time data analytics.
The data labs platform consists of three pillars: data product strategy and enablement; data management; and data product delivery.
The data labs rollout follows Kin + Carta’s December 2020 acquisition of Cascade Labs. Based in Portland, Ore., Cascade Labs specializes in data science services, including integration, engineering and data visualization.
Among the challenges addressed by data labs vendors is forging closer working relationships among data scientists focused on abstractions and engineering building data pipelines and other platforms designed to help decision makers. Hence, the data consultant’s push for “data-as-a-product,” not just another software service but as a way to “unlock [data] fluency.”
Among the goals is enabling the consumers of data to express their findings in a kind of data lingua franca that can help drive enterprise decision-making.
Late last year, Kin + Carta also announced the hiring of Cameron Turner as its vice president of data science. Turner is a co-founder of The Data Guild, the San Francisco-based “venture studio” that specializes in commercializing data science platforms.
“Just as agile software development changed the way enterprises deliver digital experiences, the data-as-a-product mindset changes how we all think about data,” Turner said. Greater data fluency across enterprises would ultimately improve data access and analytics, he added.