Metrics, Logs, and Traces: A Unified View of Modern Observability (and How to Make It Work)

January 27, 2026 at 05:30 PM | Est. read time: 14 min By Valentina Vianna Community manager and producer of specialized marketing content When systems were simpler, you could often “monitor” an application by watching CPU charts and skimming a few server logs. Today, distributed architectures, microservices, serverless functions, and third-party APIs have changed the […]

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Apache Airflow Concepts Every Engineer Should Know (and How to Use Them in Real Pipelines)

January 26, 2026 at 02:28 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content Modern data and AI systems don’t run on “one-off scripts” for long. As soon as you have multiple sources, dependencies, schedules, retries, and stakeholders who expect consistent results, you need a workflow

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Tableau Performance at Scale: How to Keep Dashboards Fast as Your Data (and Users) Grow

January 26, 2026 at 01:11 PM | Est. read time: 12 min By Valentina Vianna Community manager and producer of specialized marketing content Tableau is famously easy to adopt-until your dashboards go from “one team, one workbook” to dozens of departments, hundreds of users, and data volumes that double every quarter. Suddenly, a dashboard that

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BigQuery Architecture Explained for Data Teams (Storage, Compute, and How It All Fits Together)

January 26, 2026 at 01:06 PM | Est. read time: 14 min By Valentina Vianna Community manager and producer of specialized marketing content Google BigQuery is one of the most widely used cloud data warehouses for analytics-fast, scalable, and designed so teams can run complex SQL over massive datasets without managing infrastructure. But when performance,

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Snowflake Internals Explained: How Storage, Compute, and Scaling Really Work (and How to Use Them Better)

January 22, 2026 at 12:08 PM | Est. read time: 14 min By Valentina Vianna Community manager and producer of specialized marketing content Snowflake is often summarized as “separation of storage and compute.” True-but the real value shows up in the details: how Snowflake stores data in micro-partitions, how virtual warehouses execute queries, and how

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Amazon Redshift Performance Tuning: Practical Steps to Make Your Warehouse Faster (Without Guesswork)

January 22, 2026 at 10:37 AM | Est. read time: 16 min By Valentina Vianna Community manager and producer of specialized marketing content Amazon Redshift is built for analytics at scale-but as data volumes grow and more teams run queries concurrently, performance can degrade in ways that feel mysterious: dashboards slow down, ETL jobs take

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Great Expectations in Production Pipelines: How to Build Trustworthy Data Validation from Dev to Deploy

January 22, 2026 at 10:31 AM | Est. read time: 15 min By Valentina Vianna Community manager and producer of specialized marketing content Modern analytics and machine learning live or die by data quality. A single upstream schema change, a silent null explosion, or a “helpful” ETL tweak can break dashboards, degrade model performance, and

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Grafana for Data and Infrastructure Metrics: A Practical Guide to Observability That Actually Scales

January 22, 2026 at 10:26 AM | Est. read time: 13 min By Valentina Vianna Community manager and producer of specialized marketing content Grafana has become one of the most widely used platforms for visualizing and understanding metrics across modern systems-everything from application performance to Kubernetes health, database throughput, and cloud infrastructure cost signals. When

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Docker Fundamentals for Data Engineers: A Practical Guide to Reliable, Reproducible Pipelines

January 22, 2026 at 10:23 AM | Est. read time: 11 min By Valentina Vianna Community manager and producer of specialized marketing content Data engineering lives and dies by consistency: the same job should behave the same way in development, CI, staging, and production. Yet the reality is often “it works on my machine,” mismatched

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