A well-architected infrastructure blueprint designed to adapt to the continuous iteration that data science demands.
Your team has the skills — business knowledge, statistical versatility, programming, modeling, and visual analysis — to unlock the insight you need. But you can’t connect the dots if they can’t connect reliably with the data they need.
The Data Science Pipeline by CloudGeometry gives you faster, more productive automation and orchestration across a broad range of advanced dynamic analytic workloads. It helps you engineer production-grade services using a portfolio of proven cloud technologies to move data across your system.
Built from the leading AWS technologies for data ingest, streaming, storage, microservices, and real-time processing, it gives you the versatility to experiment across data sets, from early phase exploration to machine learning models. You get a data infrastructure ideally suited for unique demands of access, processing, and consumption throughout the data science and analytic lifecycle.
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Data-science projects can go sideways when they get in over their head on data engineering and infrastructure tasks. They get mired with a Frankenstein cloud that undermines repeatability and iteration.
We’ve solved for that with a generalizable, production-grade data pipeline architecture; it’s well-suited to the iteration and customization typical of advanced analytics workloads and data flows. that provides much more direct path for achieving real results that are both reliable and scalable.
