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Amazon Web Services

Data Science Virtual Expert Panel Presented by AWS

Join the virtual AWS expert panel about data science

Join us and our partner Amazon Web Services (AWS) for a virtual Q&A session on Wednesday, April 15. AWS will feature one of our experts to speak on a panel about the evolution and progress being made to solve critical business problems such as customer personalization and forecasting through the use of data science.

Perficient and the panel will be ready to answer questions about machine learning, services such as Amazon Personalize and Amazon Forecast, and more.

Leveraging Innovations in Data Science

Data science can add value to any business in any industry. Here are two ways AWS is bringing value to data through data science.

Amazon Personalize

Amazon Personalize allows developers with no prior machine learning experience to easily build sophisticated personalization capabilities into their applications, using machine learning technology perfected from years of use on

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Amazon Personalize can:

  • Keep the data it analyzes private and secure, and only uses it for your customized recommendations
  • Deliver personalization to individuals at scale with high-quality recommendations
  • Blend real-time user activity data with existing user profile and product information to identify the right product recommendations for your users at that moment

Use Cases:

  • Personalized search recommendations – Tailor content to a user’s behavior, history and preferences.
  • Personalized search – Using behavioral data from past application interactions, search results consider a user’s preferences and intent to surface products that are relevant to them and not just the search term.
  • Personalize notifications – Align marketing promotions to users’ behavior, interests and context to increase conversion rates.

Amazon Forecast

Amazon Forecast uses machine learning to combine time series data with additional variables to build forecasts. Amazon Forecast requires no machine learning experience to get started. You only need to provide historical data, plus any additional data that you believe may impact your forecasts.

Amazon Forecast can:

  • Produce a forecasting model capable of making predictions that are up to 50% more accurate than looking at time series data alone
  • Reduce forecasting time from months to hours
  • Create virtually any time series forecast
  • Secure your business data and peace of mind

Use Cases:

  • Product demand planning – Using your forecast information, Amazon Forecast will produce a model that accurately forecasts customer demand for products at the individual store level. You can then export your forecasts in batch in CSV format and import them back into your retail management systems so that you can determine how much inventory to purchase and allocate per store.
  • Financial planning – Forecast key financial metrics such as revenue, expenses, and cash flow across multiple time periods and monetary units using your historical financial time series data. This service can also visualize forecasts with graphs.
  • Resource planning – Maximize revenue and control costs by planning for the right level of available resources, such as staffing levels, advertising inventory, and raw material for manufacturing.

Find Value in Your Data – Register Today

Ask questions and learn more about the AWS services mentioned above and how you can leverage data science by registering for the AWS virtual expert panel Q&A session today.

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Meghan Frederick, Marketing Manager

Meghan Frederick is a Partner Marketing Manager supporting Perficient's Adobe and digital experience partnerships. In her spare time, she enjoys spending time with family and friends, traveling to EDM festivals, and coaching CrossFit.

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