Automotive
Global Practices: Security Training for the Development Team
A security training program is crucial for an effective development team. See the central concepts and programs that make a successful security training program.
The Case for Modern Data Warehouses on the Cloud
Data warehouses are business intelligence systems used to enable reporting as well as data analysis. As such, they can help any data-driven business understand and improve upon the user’s business model.
Testing in Production: A New Paradigm for Shift-Right
Testing in production (TiP) lets a software development (Dev) and IT operations (Ops) team prepare for possible bugs. It’s also helpful in analyzing the user’s experience.
The Happy Data Platform: A Personified Perspective (Part II)
The objective of a data platform is to eventually enable purposeful, actionable insights that can lead to business outcomes.
6 Key Advantages of Quarterly Agile Planning
What is quarterly agile planning? Can correct quarterly planning can help you effectively accomplish all of the objectives below?
Infrastructure Security Considerations for Edge Computing
As enterprises adopt IoT concepts and edge computing, security is a top concern. See how businesses can provide infrastructure protection for edge devices.
Use of Artificial Intelligence for Customer Retention & Satisfaction in the Insurance Industry
The insurance sector faces customer dissatisfaction and an increased number of claims. See how AI-based deep machine learning can boost customer retention.
Advances in Robotics and Cybersecurity
Robotics is growing rapidly, giving rise to many security issues. See which common security problems affect robotic platforms and how they can be mitigated.
Secure Development Lifecycle: Importance & Learning
Secure development lifecycle (SDL) provides best practices to implement security during software development. Learn about the challenges and methods behind SDL.
The Happy Data Platform: A Personified Perspective (Part I)
This blog identifies the common expectations that Data Engineers and Data Consumers have for a data platform, and it demonstrates how to meet these expectations.