What is Synthetic Data?
Unlike traditional data, which is often restricted by a range of accessibility issues, synthetic data is artificially generated, providing extensive opportunities for data-driven insights.
AI DATA CLOUDFUNDAMENTALS
Learn about some of the most relevant topics around cloud data warehousing, AI, data lakes, data engineering and other areas of interest related to cloud data analytics, AI and cloud data platforms.
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What is a data clean room?
Data clean rooms enable secure, privacy-compliant data collaboration. Learn how they work, their benefits, and how businesses use them to drive growth.
Data sharing and integration tools in the modern data ecosystem
Organizations are adapting to the fast-paced information landscape by utilizing data integration and data sharing to optimize the value of data.
Data warehouse architecture and design
Explore best practices for data warehouse architecture and design to optimize storage, retrieval and analytics for scalable, high-performance data management.
Connected and native applications: a modern approach to data-powered app development
Through connected and native applications, organizations and software providers can build secure, scalable and intelligent tools that run directly within the data environment, eliminating unnecessary movement and complexity.
DataOps for data speed and quality
Explore the meaning, benefits and key components of data operations (DataOps), an agile methodology that enables teams to access data-driven insights quickly, reducing the gap between data needs and business decisions.
What is RBAC?
Delve into the essentials of RBAC, its various benefits and challenges, and learn about best practices for the implementation of RBAC models.
Understanding data lineage
Data lineage tracks the lifecycle of data, showing its journey from origin to final destination and detailing every transformation it undergoes.
Data Lake vs. Data Warehouse vs. Data Mart
Explore the unique characteristics and differences between data lakes, data warehouses and data marts, and how they can complement each other within a modern data architecture.
What is sentiment analysis?
Sentiment analysis uses advanced techniques such as natural language processing (NLP) and machine learning algorithms to identify and categorize the emotional tone or sentiment of textual data.
MLOps
MLOps is a discipline that merges machine learning, software engineering and operational practices to streamline the deployment, monitoring and management of ML models in production.
AI for Business Intelligence
AI augments BI so any user can analyze data without needing to be proficient in writing SQL, the language of analytics and databases where data is stored.
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