ElevationData Blog


APN endorses ElevationData Service Delivery for Amazon Redshift customers

The AWS Partner Network (APN) has now certified ElevationData by Bekitzur as a Designated Service Provider for Amazon Redshift, the fastest-growing cloud data warehouse offering. This recognition is the fourth such award extended to Bekitzur in as many months . These APN service provider designations demonstrate the versatility of our end-to-end software development for data-driven and SaaS applications. They also represent the breadth of collaboration with our clients across sectors, use cases, and business models. 

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APN awards ElevationData Amazon Kinesis Service Designation for advanced data architectures

The AWS Partner Network (APN) has endorsed ElevationData, the Bekitzur company specializing in data engineering and data science pipelines, as a Designated Service Provider for Amazon Kinesis. Our client use cases span IoT telemetry data, social media feeds, video, audio, application logs, website clickstreams, and more. The end result is a reliable system with ultra-reliable scalability and a high level of security – at a surprisingly affordable price.

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Beyond Big Data for Health Care with Data Science Pipelines

Big Data

By now, the consensus view of Big Data is that bigger doesn’t translate into better. It’s a more subtle irony that in the face of bigger and faster data, data science...

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From DevOps to DataOps

Integration

Modern software development runs at a faster pace than ever before. As cloud computing divides winners and losers in the data-driven marketplace, converging applications and their data with the...

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Data-Driven Personalized Medicine: ElevationData Case Study

Process

ElevationData built and deployed a coherent data architecture to data across sources to be harvested by machine learning models. It enabled an advanced personalized healthcare platform to provide tailored advice to people suffering from chronic disease. Assuring the flow of data to models ensures every single patient always gets the best data to better manage her disease.

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The Data Science Myth is not about Data Scientists

Process

Should your data scientist build and run the data platform? In a small startup with less than a dozen people, it might be a good place to start. But is it sustainable? Just as science and engineering are unique, complementary domains, data science needs data engineering to succeed. A good look at the division of labor helps explains why.

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The Data Engineering Checklist for Data Science

Process

What comes after Big Data? Bigger data. Demands on data scientists are growing even faster. They need to the resources and tools to make ever more effective use...

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