Data Ethics
This will become a priority for businesses that want to protect customer privacy and trust.
Data Integrity
This will require more investment and attention to prevent data breaches, tampering, and manipulation.
Data Quality
How Data Quality will be improved by using AI and machine learning workflows to automate data cleaning, validation, and enrichment.
Data Regulation
It defines how to keep pace with the change on focus with responsible data use and governance, ensuring compliance with laws and standards such as GDPR, CCPA, and ISO.
Big Data Principles
Ensuring the goal is clear Big data can be very descriptive while uncovering the multiple layers of information flow that affect businesses.
Data Processing
This will be enabled by AI and machine learning tools that can handle large volumes, variety, and velocity of data, as well as provide insights and recommendations.
Data Architecture
Integrate your platform portfolio into newer microservice design principles to enable scalability, flexibility, and interoperability of data systems and applications.
Data Democratization
Empower more users across the organization to access, analyze, and act on data-driven insights, using self-service tools and augmented analytics.
Big Data Insights
Data Observability
Looking to help to enable data systems to be monitored and understood in real time, enabling faster and more accurate problem diagnosis and resolution.
Data Sharing
Making a safe reality leading to new opportunities for collaboration, innovation, and value creation.
