Various sources feed data into demand planning software such as SQL/NoSQL systems, ERP or CRM systems, other SaaS applications, file shares, and streaming data sources such as social media, smart devices, and logs. Data from these sources can be ingested into the o9 SaaS solution using native o9 native APIs and SFTP. Data can also be ingested into a customer's AWS account. The service selection depends on the source. Customers can use AWS Data Migration Service for SQL/NoSQL, Amazon AppFlow for ERP, CRM, or SaaS, AWS DataSync for a file share, and Amazon Kinesis, Amazon MSK, and AWS IoT Core for streaming data feed from variety of sources. Customers can store ingested data in Amazon S3 into their AWS accounts. Streaming data can also be fed to the o9 SaaS solution using o9-native REST APIs, or stored in Amazon S3 via Amazon Kinesis Data Streams through AWS SDK or AWS Lambda. Data from a third party (such as TransUnion, IMDb, or Reuters) can be subscribed to and used in the AWS Cloud using AWS Data Exchange. The AWS customer account data in S3can be batch-ingested into the o9 SaaS solution using AWS Glue through AWS SDK or AWS Lambda. Data within the o9 SaaS solution and the AWS customer account can be shared using o9-native APIs and optional use of AWS Lambda. Customers can collect outbound data from the o9 SaaS solution in S3 in their account using standard S3APIs or AWS Lambda, and use it in other AWS services for analytics and artificial intelligence/machine learning (AI/ML) workloads. Customers can use AWS AI/ML services such as Amazon Forecastand Amazon SageMaker to build, train, and deploy ML models to complement o9 SaaS solution ML capabilities. Customers can use AWS analytics services such as Amazon EMR and Amazon RedShift for big data processing and warehousing. Customers can integrate data from the o9 SaaS solution to a data lake in their account. The data lakes are created using services such as Amazon S3, AWS Glue, AWS IAM, and A
