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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

The typical pharmaceutical organization faces many challenges which slow down the data team: Raw, barely integrated data sets require engineers to perform manual , repetitive, error-prone work to create analyst-ready data sets. Cloud computing has made it much easier to integrate data sets, but that’s only the beginning.

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The Rise of the Data Engineer

Maxime Beauchemin

The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

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Ripple's Centralized Data Platform

Ripple Engineering

  A lack of a centralized system makes building a single source of high-quality data difficult. The key aspect of any business-centric team in delivering products and features is to make critical decisions on ensuring low latency, high throughput, cost-effective storage, and highly efficient infrastructure.

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Creating Value With a Data-Centric Culture: Essential Capabilities to Treat Data as a Product

Ascend.io

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.