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SaaS (software-as-a-service) products are ubiquitous in the modern enterprise. SaaS is great for cost control and ease of management for both the vendor and the customer, but those advantages come with trade-offs around data security models, primarily due to commingling of data in the multi-tenant architectures of SaaS vendors. In this blog, we claim that you can have your cake (cost/ease of management) and eat it (security) too! We explore changing the software delivery model of SaaS products to solve for security while maintaining the traditional advantages of SaaS products by leveraging serverless offerings from cloud vendors (AWS, Azure,
Building Serverless Data Pipelines on Amazon Redshift By Writing SQL with Datacoral
This blog post originally appeared in the AWS Partner Network (APN) Blog. Amazon Redshift is a powerful yet affordable data warehouse, and while getting data out of Redshift is easy, getting data into and around Redshift can pose problems as the warehouse grows. Data ingestion issues start to emerge when organizations outgrow the COPY command that imports CSV files from Amazon Simple Storage Service (Amazon S3) buckets. And, of course, these issues take shape at the worst possible time—when the warehouse becomes popular with analysts and data scientists as they increase demand for more data, sources, and targets. When

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