Data has become relatively easy to capture and store, but like most businesses, you still may be struggling to extract value from it. Converting data into meaningful information requires a system of tools and technology that can overwhelm even the most experienced data scientists. We leverage this data infrastructure architecture model (courtesy of Andreessen Horowitz) in conversations with clients and partners to help define new data services that leverage proprietary and third-party machine learning models.
This architecture diagram shows how today’s data tools and systems fit together. The standardized terminology and system descriptions help accelerate and clarify our conversations so we can immediately start building the data service and create customer value.
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Converting data into meaningful information requires a system of tools and technology that can overwhelm even the most experienced data scientists.