AccuWeather wanted to enhance its weather forecasting with digital technology but needed a way to work with its traditional weather data format. It used Azure Databricks to build a next-generation forecasting engine that converts the weather data into a usable format for AI analysis. AccuWeather also migrated its API to Azure to gain insights that help improve customer relationships. The solutions on Azure allow AccuWeather to process data faster at lower cost and use machine learning to improve forecast speed and accuracy with more localized predictions.

1. MICROSOFT AZURE
ACCUWEATHER
Enrollment number:
Debanjan Ghosh(18012011015)
Ayush Jain(18012011026)

2. What is Microsoft Azure?

3. What is Accuweather
- AccuWeather Inc. is an American media company that provides commercial weather forecasting services
worldwide.
- AccuWeather was founded in 1962 by Joel N. Myers, then a Pennsylvania State University graduate student
working on a master's degree in meteorology.
- AccuWeather provides weather forecasts and warnings and additional weather products and services, with
clients worldwide in media, business and government, including more than half of the Fortune 500 companies
and thousands of other businesses globally. It also runs the free, advertising-supported website
AccuWeather.com, an online weather provider

4. Accuweather and Azure
- “Operating on Azure, we have opportunities to improve of the speed, range, accuracy, and localization of our forecasts—it’s just a question of what
to prioritize first.”
Brad Beechler: Senior Machine Learning Scientist
AccuWeather
- AccuWeather, the most accurate provider of weather forecasts and warnings available on all platforms, wanted to enhance its combination of
superior forecasting with digital technology, but it needed a way to work with a traditional data format that makes it difficult to innovate.
- The company used Microsoft Azure Databricks and other Azure services to build a key component of its next-generation forecasting engine, which
converts the weather data into a usable format for AI-assisted analysis. AccuWeather also migrated its world-renowned API to Azure, where the
company’s team now generates valuable insights on API usage that help improve customer relationships.

5. Problem with Traditional Data of Accuweather
➢ Accuweather forecast was generally used for weather forecasting which in turn would stop
people from getting caught in rain when they go out.
➢ But the main focus for accuweather was to give an accurate forecast which can prevent rained
out sports events and performances, and costly disasters like failed project launches.
➢ Accuweather helps around 1.5 billion people across the world and people rely on the big data
which in turn helps make decision.

6. Accuweather Digital Forecast System

7. Solution for this problem
➢ To achieve its technical and business ambitions, AccuWeather uses Microsoft Azure Databricks to support its next-
generation forecasting engine and help convert GRIB data into more scalable, efficiently processed formats for AI-
assisted analysis on Azure. It used Delta Lake, an open-source storage layer, on Databricks to help create data
pipelines and make the company’s ever-growing data lake more accessible and usable.
➢ Now, it’s easier for AccuWeather teams to interact with datasets and ask specific questions about weather
parameters such as temperature and precipitation in specific locations at specific times. Then they use Azure
infrastructure and platform services to apply machine learning models to the company’s datasets and train predictive
models that will improve the speed and accuracy of AccuWeather forecasts.

8. Better API insights, stronger customer relationships
➢ Some of the world’s most well-known weather providers use the AccuWeather API. In fact, it receives more than 45
billion requests every day. Previously, AccuWeather could only measure the usage of its API keys once a month, and it
needed more accurate, timely insights to give customers greater visibility into their usage and scale infrastructure to
meet the demand.
➢ The company migrated its API edge-logging infrastructure to Azure, using Azure Data Lake Storage to capture and
store compressed log files and to convert the files into tables in Azure Databricks. The information is passed to Azure
Databricks SQL where AccuWeather finance, IT, and customer service teams build data visualizations and generate
usable business insights.

9. Faster, more localization forecasts
➢ Using Azure Databricks and other Azure services, the company can process GRIB data faster, at
lower cost, and use predictive insights as part of its forecasts.
➢ AccuWeather now has the agility to scale its compute resources up and down depending on the
needs of a project, and its teams can run models very quickly to release the company’s
forecasts before other providers.
➢ “Being first to market gives us a competitive edge, and accurate, hyper-localized forecasts are
critical for many of our customers,”
➢ Authorities may not have time to put sand on every bridge in their area, so they need to know
where to focus their attention very specifically. The sooner we can get a forecast or alert out,
the faster our customers can respond.

10. Any Questions?

11. THANK YOU