FAQs & Resources
Learn technology terms, get answers to common technical questions, and discover topic-specific resources.
Enterprise AI FAQs & resources
Agentic AI
Understand the benefits, implementation strategies, and real-world applications of agentic AI.
AI agents
Get information on the types of AI agents as well as their architectures and real-world application.
AI inference
Explore how AI inference differs from training, its significance, and best practices for deployment.
AI models
Explore the types of AI models, training methodologies, and deployment strategies.
Artificial intelligence
Learn fundamentals, practical applications, and strategies for the implementation of AI.
Enterprise AI
Dive into enterprise AI's significance, benefits, challenges, and applications across industries.
Generative AI
Navigate generative AI, its applications, and its potential to revolutionize businesses operations.
Large language models
Harness the power of deep learning and neural networks to extract meaningful insights.
Machine learning
Dig into everything machine learning—from the basics to cutting-edge applications.
Model context protocol
Connect AI applications—such as LLMs and AI agents—to external data sources and tools with MCP.
Private AI
Navigate generative AI, its applications, and its potential to revolutionize businesses operations.
RAG
Harness the power of deep learning and neural networks to extract meaningful insights.
Sovereign AI
Develop, manage, and govern AI within your own borders or control for compliance and security.
Data analytics FAQs & resources
Data analytics
Analyze complex data sets to uncover insights that help solve problems and inform decisions.
Data intelligence
Leverage advanced analytics, AI, and ML to inform decisions, optimize operations, and drive innovation.
Data visualization
Quickly and easily explore data, collaborate, and unlock insights with interactive dashboards.
NoSQL
Store, process, and analyze diverse data types with NoSQL, designed to meet the demands of all your data.
Real-time analytics
Continuously ingest, process, and serve data so actions can be taken in real time for critical use cases.
Data architecture FAQs & resources
Data fabric
Deliver access to data sources intelligently and securely across multiple clouds and on premises.
Data lake
Store data in its native format and apply structure as needed in scalable, cost-effective storage.
Data lakehouse
Process any data, anywhere, with a flexible platform for actionable insights and trusted AI.
Data mesh
Foster accountability and allow for faster, autonomous decision making with a decentralized approach.
Modern data architecture
Implement the right architecture to gain flexible, scaleable support for data processing.
Data infrastructure FAQs & resources
Hybrid data
Leverage on-premises and cloud environments, ensuring flexibility, scalability, and control over data.
Multi-cloud
Use two or more cloud providers to align workloads with the best capabilities for the job.
Private cloud
Protect sensitive workloads, meet regulatory demands, and still move fast with private cloud.
Public cloud
Get elastic capacity in minutes, pay only for what yo use, and take advantage of a global footprint.
Data in motion FAQs & resources
Data flow
Collect and move your data from any source to any destination simply and securely with Apache NiFi.
Data in motion
Ingest, process, and analyze all kinds of data anywhere it lives for real-time insights and AI.
Data streaming
Tap into Kafka and Flink to create high-performance, real-time streaming data applications.
Stream processing
Process data continuously from sensors, IoT devices, social media, and more in near real time.
Streaming analytics
Analyze real-time data as it flows in continuously from various sources like IoT devices and application logs.
Data management FAQs & resources
Data catalog
Understand and manage data with a centralized view that facilitates governance and compliance.
Data collection
Specify fit-for-purpose data with known provenance and quality to ensure trustworthy insights.
Data discovery
Ensure visibility into your data so people and machines can use it responsibly and securely.
Data engineering
Develop data pipelines and infrastructure that process and manage large datasets.
Data management
Collect, store, organize, and secure data so you can extract insights easily and comply with regulations.
Data migration
Move data from one environment to another while ensuring integrity, security, and business continuity.
Data readiness
Ensure systems can autonomously generate accurate outputs without manual intervention.
Data replication
Copy and sync data from a primary source to targets, ensuring availability and fault tolerance.
Data services
Manage, deliver, and transform data across systems, and environments with modular technology.
Data transformation
Convert data into high-quality, usable formats that are fit for defined business purposes.
Operational database
Update data in real time across many short concurrent transactions, while enforcing integrity.
Open source FAQs & resources
Apache Airflow
Author, schedule, and monitor complex workflows to manage data pipelines.
Apache Flink
Use scalable, low-latency, and high-throughput processing for real-time insights from streaming data.
Apache Iceberg
Effectively store, manage, and query large volumes of data in distributed data lakes or the cloud.
Apache Ozone
Overcome the limitations of HDFS, improve performance, and better manage small files.
Apache Ranger
Centrally monitor and manage data with fine-grained access control and auditing capabilities.
Apache Spark
Program entire clusters quickly and easily with implicit data parallelism and fault tolerance.
Trino
Run complex ANSI SQL queries against data lakes, RDBMSes, and NoSQL stores simultaneously.
Security & governance FAQs & resources
Data governance
Manage and protect data assets across an organization with formal practices and policies.
Data lineage
Capture relationships among data sources for traceability and transparency in data pipelines.
Data security
Protect data from unauthorized access, alteration, or destruction with policies and technology.
Use case FAQs & resources
Digital twins
Create a persistent, bi-directionally syncing virtual representation of a physical counterpart.
Predictive analysis
Apply ML techniques to historical data to estimate future outcomes and quantify uncertainty.
Predictive analytics
Use statistical algorithms and ML to identify the likelihood of future outcomes based on data.
Predictive maintenance
Use data to proactively service assets just in time rather than on a fixed schedule or after a failure.
Supply chain optimization
Design and monitor an end-to-end supply network to meet service goals with less cost and fewer risks.