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Author
Daniel Kuperman Daniel Kuperman
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2020년 05월 04일 3 min read

How Weather Data Can Improve Data Analytics

  • 제품 및 기술
    • 데이터 공유 및 데이터 마켓플레이스
How Weather Data Can Improve Data Analytics

We had the pleasure of talking with Mark Gibbas, CEO of Weather Source. Justin Langseth, Data Exchange CTO at Snowflake, interviewed Gibbas and discussed how different types of weather datasets are helping companies with their data analytics.

Weather Source provides hyper-local weather and climate data, distinguishing it from other weather data providers. While others provide data based on information from a singular input (such as an airport observation station), Weather Source creates a series of virtual weather stations at customer points of interest using multiple inputs such as airport observation stations, NOAA and NWS data, satellites, radar, and IOT. 

Different data products help customers understand a variety of use cases. Whether they need detailed hourly and daily weather history or detailed forecasts for anywhere in the world, Weather Source has the data. Snowflake customers can access these rich datasets in Snowflake Data Marketplace directly from their Snowflake accounts.

To provide an example, Weather Source offers Snowflake customers a free data listing, “Global Weather & Climate Data For BI,” which contains:

  • Daily historical weather data from 2016 to the present
  • 15-day daily forecast weather data
  • Daily 15-year climatology data (weather statistics)

In addition, Weather Source is offering complimentary weather and climate data for organizations researching potential connections between weather and COVID-19 viability and transmission. This dataset includes global historical weather data dating to October 2019, current data, and forecast data out to 15 days. The data includes temperature and humidity, both specific and relative, at the daily level.

For more details, check out the entire Weather Source video interview below.

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