Remove Data Warehouse Remove Internet of Things Remove IoT Remove Predictive Modeling
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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Amazon Kinesis Data Streams: celebrating a decade of real-time data innovation

AWS Big Data

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 55
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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

For nearly a decade, it’s provided a venue for developers, data and ML engineers, data architects, data scientists, and others to acquire or hone skills, explore provocative ideas, and network with peers. If anything, this focus has shifted to the ML or predictive model. The model has become a means to an end—i.e.,

IoT 20