Systems | Development | Analytics | API | Testing

Cybersecurity is a data problem at its core. Yet, security teams haven’t achieved tremendous success in utilizing the modern data stack that data analytics teams have enjoyed for years. Security teams face constant pressure from vulnerabilities and breaches in their infrastructure and supply chains because they remain on a proverbial island with antiquated technology. Cybersecurity leaders must uplevel their strategies by implementing a modern security data lake.

How we eat, exercise, work, and rest play an important role in influencing our health outcomes. It’s been established that healthcare and life sciences (HCLS) organizations can improve health outcomes when they have access to this type of data on patients to inform real-world evidence.

Machine learning (ML), more than any other workflow, has imposed the most stress on modern data architectures. Its success is often contingent on the collaboration of polyglot data teams stitching together SQL- and Python-based pipelines to execute the many steps that take place from data ingestion to ML model inference.