WM New Zealand reduces source onboarding time from three months to days with Fivetran, unifying operational and IoT data for scalable analytics and AI initiatives<\/p>\n
Fivetran, the data foundation for AI, today announced that WM New Zealand (WMNZ), the country\u2019s leading waste and environmental services provider, has selected the Fivetran platform as its data foundation for AI. Fivetran connects operational systems, SaaS applications, and high-volume IoT data into Snowflake, with transformations managed in dbt Cloud from dbt Labs, creating a centralized, AI-ready data foundation across the business.<\/p>\n
WMNZ selected Fivetran to enable its lean data team to meet growing demand from leadership for real-time insights while addressing the scale and complexity of moving data across a fragmented environment. The company is in the midst of a digital business transformation, with data and AI at its core. With more than 900 trucks, over 100 sites, and high-volume IoT data across collections, fleet, and environmental monitoring, WMNZ sees AI and advanced analytics as central to how it operates: from route optimization and predictive maintenance to accelerating its circular economy and decarbonization goals. To get there, the company needed to rapidly unify a backlog of priority data sources and deliver reliable, timely data at scale.<\/p>\n
Fivetran has helped WMNZ reduce source onboarding timelines from months to days, enabling the company to meet an aggressive 12-week delivery target and freeing the data team to focus on the analytics and AI initiatives at the centre of its transformation. The platform reliably supports high-volume IoT data alongside on-premises, SaaS, and custom data sources, delivering predictable performance at scale without the need to build or maintain bespoke.<\/p>\n
\u201cAI only delivers value when the underlying data is reliable, complete, and available when it\u2019s needed,\u201d said George Fraser, CEO of Fivetran. \u201cMany organizations are investing heavily in AI but are still constrained by fragmented systems and brittle pipelines. By automating data movement across complex operational and IoT environments, WM New Zealand is building the trusted data foundation needed to support analytics and future AI initiatives.\u201d<\/p>\n
\u201cSpeed and reliability were non-negotiable for us,\u201d said Lena Jenkins, Chief Digital & Customer Success Officer, WMNZ. \u201cFivetran gave us the speed we needed to stand up our data foundation in weeks rather than months. Our team can now focus on data and AI enablement: applying AI and advanced analytics to improve how we operate, how we serve our customers, and how we deliver on our decarbonization and circular economy ambitions. That foundation is critical as we apply advanced analytics and AI to improve operational efficiency and environmental outcomes across New Zealand.\u201d<\/p>\n
With automated pipelines feeding Snowflake and transformations managed in dbt Cloud, WMNZ now operates on a single, trusted source of data. The modern architecture enables faster, more timely access to trusted data while preserving flexibility across platforms, ensuring WMNZ can evolve its analytics and AI strategy without architectural constraints.The post Fivetran Selected by WM New Zealand to Power an AI-Ready Data Foundation first appeared on AI-Tech Park.<\/p>\n","protected":false},"excerpt":{"rendered":"
WM New Zealand reduces source onboarding time from three months to days with Fivetran, unifying operational and IoT data for scalable analytics and AI initiatives Fivetran, the data foundation for AI, today announced that WM New Zealand (WMNZ), the country\u2019s leading waste and environmental services provider, has selected the Fivetran…<\/p>\n
The post Fivetran Selected by WM New Zealand to Power an AI-Ready Data Foundation<\/a> first appeared on AI-Tech Park<\/a>.<\/p>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[4,1],"tags":[3],"class_list":["post-2135","post","type-post","status-publish","format-standard","hentry","category-ai","category-ai-and-ml","tag-ai"],"yoast_head":"\n