2.3 trillion gigabytes of data are being generated each day by humans and devices, becoming available as corporate and public golden assets.
In principle, current state-of the art data analysis technologies have the potential to transform these data assets into rich information and actionable knowledge meant to improve business and guide human and automated decisions.
Data Science promises to better understand business stakeholders, characterize the markets, accelerate processes, predict risk and even anticipate new business opportunities.
However, the reality is that the wealth of data in organizations is often disorganized, missing, misleading, noisy or fragmented, lacking provenance and annotation, and spread across many disconnected databases.
Data Engineering. The task of managing, sourcing, collecting, integrating, updating the data is the realm of Data Engineering. That is why Data Engineering is probably one of the most demanded and well-paid occupations. Data Engineers, also called Data Architects, are occupied with the design and building of data pipelines that support data analysis, and also tasked with sourcing the software and hardware relevant for a healthy and robust data platforms.
At Phenobyte, our team of Data Engineers and Data Scientists work closely together so that the data platforms we design and build for our clients are suitable for seamless data analysis. Raw data and data resulting from models can be updated, backed up and monitored for quality, as well as integrated and benchmarked against external public and licensed data.
For more information about our services, please contact us: firstname.lastname@example.org
We are a team of expert data scientists and data engineers committed to make an impact on human health by leveraging state-of-the-art technology to interrogate data, gather valuable information and create actionable knowledge
We're looking for advisors, investors and motivated data scientists and engineers that wish to make an impact in healthcare by leveraging data-driven technological advances.
As data science, AI and machine learning become buzzwords saturating management presentations, and companies hire data science graduates from overpromising training programmes, there is a constant overarching question among business stakeholders: where's the data?READ ARTICLE
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