Data analysis, big data, and business intelligence
Found 388 articles
BetMGM’s profit and payments to MGM rose, while lower room rates cut Strip earnings and US iGaming growth slowed to 12%.
Salt Security’s 2026 report highlights a gap in agentic AI security: valid credentials and permissions can still lead to actions an organization didn’t intend.
Databricks and Snowflake can access each other’s tables through shared ADLS storage and catalog metadata, avoiding duplicate data copies.
A small Java project can move to Kotlin in days; a monolith with hundreds of thousands of lines can turn that choice into quarters of work.
AI may ease software creation, but development still depends on available time, skilled people and the infrastructure to build and deliver applications.
A Kafka recovery utility grew to support scheduled incremental ingestion, historical data replay, and throughput control for streaming pipelines.
Copado pipelines can make Salesforce’s quick, no-code changes traceable through version control, conflict resolution and automated regression testing.
YARN’s container sizing can leave Spark nodes with idle CPU even when allocated memory looks nearly full. Executor fit depends on overhead and allocation increments.
Go can collect Reddit listings through public JSON endpoints, but the roughly 1,000-item cap and frequent datacenter IP blocks constrain scraping.
Model, data, tool, and prompt changes can shift agent behavior. CI evals can catch those regressions before users do.
A Kafdrop hackathon feature adds message search to help engineers find where records disappear across pipeline stages.
Persistent agents need separate mechanisms for recent context and long-term memory; replaying chat history alone can’t sustain continuity across sessions.
LangChainGo’s release pace has left parts of its Go AI stack broken as models, SDKs and APIs change.
Edge-to-cloud systems carry telemetry, control commands, site data and user-facing information. Matching each traffic pattern to its needs can help avoid one-size-fits-all designs.
Whole-GPU allocation and misleading node metrics hide inference waste. Queue depth and workload-aware sharing can make Kubernetes GPU use more efficient.
URL-based document imports save upload steps, but accepting any valid link can expose internal services to SSRF attacks.
Lower token prices and stronger benchmark scores don’t capture the work of revalidating business workflows after an AI model change.
VLM adoption now depends on reliable, cost-effective cloud operations as much as model advances, with observability and governance central to production.
AI agents can query databases and trigger workflows under their own credentials. Their permissions need to match their ability to act.
A Bronto review maps 64 AI SRE tools across seven categories, showing how products sharing one label tackle different operational problems.