PredictHQ Partners with Snowflake to Make Demand Intelligence Accessible
November 03, 2021 at 11:00 am EDT
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PredictHQ has announced a partnership and integration with Snowflake, the Data Cloud company. Snowflake customers will now be able to access PredictHQ's forecast-grade event data in their preferred, supported cloud environment. Through this partnership, Snowflake customers will be able to access PredictHQ's Demand Intelligence offering via Snowflake Data Marketplace, enabling them to identify which events impact their demand so they can forecast and plan more accurately. Customers can choose from the sample listings such as attended and non-attended events including sports, conferences, concerts, school holidays and many more or unscheduled events such severe weather. Customers can also request a custom offer via the personalised marketplace listing. Companies such as Uber, Domino's and Accor Hotels use PredictHQ's intelligent event data to identify their demand drivers in advance so they can prepare to meet it. Snowflake's customers will be able to quickly and easily access PredictHQ demand intelligence through its integration with Snowflake Data Sharing, without the hassle of any ETL processes. This means they can easily access local insight at scale through PredictHQ's 19 event categories in order to prepare for anomalies in advance, and reduce their forecasting error rate.
Snowflake Inc. enables every organization to mobilize their data with Snowflakes Data Cloud. The Companyâs platform powers the Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful business insights, apply artificial intelligence (AI) to solve business problems, build data applications, and share data and data products. Its platform supports a range of workload, including data warehouse, data lake, data engineering, AI/machine learning (ML), applications, collaboration, cybersecurity, and Unistore. Its cloud-native architecture consists of three independently scalable but logically integrated layers across compute, storage, and cloud services. The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency. The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data to create a unified data record.