# data analytics Published articles for data analytics. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Beyond the data: what a Business Analyst does at Nubank DevFeed: [Beyond the data: what a Business Analyst does at Nubank]() Original publisher: [Read original article]() Author: Nubank Editorial Published: 2026-09-15T12:14:41Z Content type: opinion Language: en Sources: [Nubank]() Topics: [Data analysis](), [decision-making](), [context](), [Tech Lead]() Tags: [adoption](), [business-analyst](), [data](), [data-analysis](), [data-analytics](), [data-science-machine-learning](), [decision-making](), [manager](), [tech-lead](), [user-experience]() ### AI overview A first-person account of the Business Analyst role at Nubank, describing how BAs connect data analysis, context, and experimentation to product and business decisions. The article emphasizes clarifying trade-offs, investigating metrics, and collaborating with product and technical roles. ### Source excerpt Understand how Business Analysts at Nubank use data, context, and experimentation to guide product decisions. The post Beyond the data: what a Business Analyst does at Nubank appeared first on Building Nubank. ## Linux Patched For Silent User-Space Data Loss Bug That's Existed Since 2023 DevFeed: [Linux Patched For Silent User-Space Data Loss Bug That's Existed Since 2023]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-14T10:13:45Z Content type: news Language: en Sources: [Phoronix]() Topics: [Linux](), [bug](), [DataOps](), [Code]() Tags: [bug](), [c](), [code](), [data-analytics](), [desktop-linux](), [kernel](), [linux](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [open-source-graphics](), [phoronix](), [phoronix-test-suite](), [production](), [release](), [ubuntu-benchmarks](), [ubuntu-hardware]() ### AI overview A Linux kernel bug introduced in July 2023 can silently discard user-space writes when transparent hugepages are enabled, cgroup limits apply, and memory reclaim pressure is high. The issue has caused production data loss, including for users of the Polars data analytics library. A one-line fix was merged into the x86/urgent branch and marked for backporting to supported stable kernels. ### Source excerpt Being merged after yesterday's Linux 7.3-rc3 release was an important fix for addressing a silent, user-space data loss bug that has existed in the kernel the past three years... ## How we built Datadog Experiments DevFeed: [How we built Datadog Experiments]() Original publisher: [Read original article]() Author: Chas DeVeas; Aaron Silverman; Tyler Buffington; Jonathan Fulton; Taylor Overturf Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [experiments](), [real user monitoring]() Tags: [a-b-testing](), [acquisition](), [data-analytics](), [data-engineering](), [experimentation](), [experiments](), [metrics](), [observability](), [product-analytics](), [real-user-monitoring]() ### AI overview Datadog describes rebuilding its experimentation platform to speed up confident A/B-test decisions. The article explains a flexible CUPED approach that reduces metric variance and can be applied to segments. ### Source excerpt Datadog Experiments shortens the time from result to decision with CUPED on percentiles, verifiable warehouse results, and near real-time RUM metrics. ## NFR Brain: challenging the status quo of risk management with data DevFeed: [NFR Brain: challenging the status quo of risk management with data]() Original publisher: [Read original article]() Author: Nubank Editorial Published: 2026-09-04T14:18:41Z Content type: article Language: en Sources: [Nubank]() Topics: [risk-management](), [data](), [Resilience](), [incident]() Tags: [business](), [complexity](), [data](), [data-analytics](), [data-science-machine-learning](), [management](), [resilience](), [risk](), [risk-management](), [service]() ### AI overview Nubank is building NFR Brain, a platform that combines data, modelling and expert judgement to create a comparable and actionable view of non-financial risk. The article explains how the platform is intended to support clearer, more consistent prioritization across operational failures, customer complaints, third-party dependencies and other risk signals. ### Source excerpt Author : Mayara Zenati At Nubank, we believe the most meaningful problems for customers and for the business rarely come with ready-made answers. That is why we challenge the status quo: not to innovate for innovation's sake, but to remove complexity and build solutions that make important decisions simpler, faster and better. This mindset also [...] The post NFR Brain: challenging the status quo of risk management with data appeared first on Building Nubank. ## The Art of Simplifying Decisions. DevFeed: [The Art of Simplifying Decisions.]() Original publisher: [Read original article]() Author: David Pereira Published: 2026-08-20T12:27:37Z Content type: opinion Language: en Sources: [Untrapping Product Teams]() Topics: [decision-making](), [data analytics](), [Artificial Intelligence]() Tags: [ai-agents](), [analysis](), [data-analytics](), [decision-making]() ### AI overview The article argues that decision-making has become a bottleneck as coding becomes more scalable. It compares AI-supported options, additional meetings, and decision-making within limited scope, while emphasizing the need for context, evidence, and empowered product decisions. ### Source excerpt Decision-making is the bottleneck today. ## Data pipeline monitoring 101: Tracking health and performance across the data stack DevFeed: [Data pipeline monitoring 101: Tracking health and performance across the data stack]() Original publisher: [Read original article]() Author: Aaron Kaplan; Ryan Warrier Published: 2026-08-14T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Monitoring](), [data observability](), [observability](), [data](), [data streams monitoring](), [Kafka](), [Apache Spark](), [event driven](), [Streaming]() Tags: [ai-ml](), [analytics](), [data](), [data-analytics](), [data-engineering](), [data-observability](), [data-streams-monitoring](), [event-driven](), [kafka](), [learn](), [monitoring](), [observability](), [performance](), [spark](), [streaming]() ### AI overview This article introduces end-to-end monitoring for modern data pipelines. It explains how to track pipeline health, performance, data quality, and availability across varied architectures and technology layers, with examples including Kafka, Flink, Apache Spark, data lakes, warehouses, and lakehouses. ### Source excerpt Learn about monitoring the end-to-end health and performance of modern data pipelines. ## The CI/CD moment for data analytics DevFeed: [The CI/CD moment for data analytics]() Original publisher: [Read original article]() Author: Gaurav Nanda Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [data analytics](), [DataOps](), [real-time](), [data-engineering](), [CI/CD](), [Kafka](), [apache-flink]() Tags: [ai](), [analytics](), [apache-flink](), [architectures](), [bridging](), [cost](), [data-analytics](), [data-engineering](), [engineering](), [event](), [fraud](), [google](), [insights](), [kafka](), [latency](), [real-time](), [scale](), [streaming](), [systems](), [tools]() ### AI overview The article argues that data analytics is approaching a CI/CD-like transition toward continuous analytics. It describes how multi-step pipelines introduce latency, operational risk, and maintenance burden, and explains why real-time insight is becoming a baseline platform capability for applications such as personalization, fraud detection, reliability, and AI-driven features. ### Source excerpt How converging OLTP and OLAP architectures are driving 'Continuous Analytics', the CI/CD moment for data to deliver real-time, unified insights and operational simplicity. ## NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI DevFeed: [NVIDIA Vera CPU: Olympus Cores Built for Maximum Single-Thread Performance in Agentic AI]() Original publisher: [Read original article]() Author: Praveen Menon Published: 2026-07-21T18:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [cpu]() Tags: [agentic-ai](), [agentic-ai-generative-ai](), [agents](), [ai-factory](), [ai-infrastructure](), [architecture](), [code](), [concurrency](), [cpu](), [data-analytics](), [data-center-cloud](), [featured](), [latency](), [memory](), [nvidia](), [nvidia-vera](), [performance](), [reinforcement-learning](), [sandboxes](), [tools](), [top-stories](), [vera-cpu](), [vera-rubin]() ### AI overview The article explains how NVIDIA's Vera CPU and its Olympus cores are designed for the single-threaded performance, memory bandwidth, and predictable latency required by concurrent agentic AI workloads. ### Source excerpt Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with... ## Running Low-Latency Analytical Workloads with GPU-Accelerated Presto on NVIDIA GB200 NVL72 DevFeed: [Running Low-Latency Analytical Workloads with GPU-Accelerated Presto on NVIDIA GB200 NVL72]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-07-08T16:05:25Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [GPU](), [benchmarking](), [SQL](), [Open Source](), [datasets](), [Nvidia](), [GPUDirect](), [NVIDIA DGX](), [NVLink](), [parquet](), [C++](), [Optimization]() Tags: [benchmarking](), [benchmarks](), [c-plus-plus](), [cache](), [communication](), [cpu](), [data](), [data-analytics](), [data-science](), [datasets](), [developer-tools-techniques](), [featured](), [gb200](), [gpu](), [gpudirect](), [latency](), [low-latency](), [multi-gpu](), [nvidia](), [nvidia-dgx](), [nvl72](), [open-source](), [performance]() ### AI overview This article presents GPU-accelerated Presto for low-latency analytical SQL workloads on large datasets. It compares single-node multi-GPU execution on NVIDIA DGX B200 and multinode NVIDIA GB200 NVL72 systems with CPU-based Presto, highlighting NVLink communication, GPUDirect Storage, cuDF algorithms, Parquet data, and benchmark results. ### Source excerpt Presto is an open source, distributed SQL engine for running fast, interactive queries on very large datasets. On NVIDIA GPUs, Presto delivers peak performance... ## How Visa went from multi-day reporting to conversational analytics agents with ClickHouse Cloud and LibreChat DevFeed: [How Visa went from multi-day reporting to conversational analytics agents with ClickHouse Cloud and LibreChat]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-06-24T15:12:01Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [data analytics](), [Conversational AI](), [MCP Server](), [Model Context Protocol (MCP)](), [Amazon Bedrock](), [Cloud](), [Amazon Web Services](), [Security](), [SQL](), [Open Source]() Tags: [ai](), [analytics](), [apis](), [aws](), [clickhouse](), [cloud](), [conversational-ai](), [data-analytics](), [mcp](), [mcp-server](), [open-source](), [security](), [sql]() ### AI overview Visa used ClickHouse Cloud on AWS, LibreChat, and the ClickHouse MCP server to build conversational BI agents for Authorize.net payments data. The system enables natural-language analysis across roughly 40 petabytes and reduced multi-day reporting to sub-second answers, while materialized views improved analysis speed and reclaimed 8-10 hours per user each week. ### Source excerpt Visa paired LibreChat with ClickHouse Cloud to build conversational BI agents on Authorize.net payments data, cutting multi-day reports to sub-second queries and reclaiming 8-10 hours per user each week. ## Get reliable answers to business questions with Bits Data Analysis DevFeed: [Get reliable answers to business questions with Bits Data Analysis]() Original publisher: [Read original article]() Author: Jonathan Morin; Jonathan Parisot; Harel Shein Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Data analysis](), [data observability](), [semantic-layer](), [SIEM, Security, Observability](), [Model Context Protocol](), [ai-coding]() Tags: [ai](), [ai-coding](), [analytics](), [bits-ai](), [data-analytics](), [data-engineering](), [data-observability](), [digital-experience-monitoring](), [mcp](), [observability](), [root-cause-analysis](), [semantic-layer]() ### AI overview Bits Data Analysis, now in Preview, helps teams answer business questions with governed context from their data stack and Datadog telemetry. It uses metric definitions, lineage, freshness, quality signals, application telemetry, and source code to select appropriate data and provide confidence indicators with links to the definitions and tables used. ### Source excerpt Learn how Bits Data Analysis answers business questions using governed data context from Datadog. ## Codex for every role, tool, and workflow DevFeed: [Codex for every role, tool, and workflow]() Original publisher: [Read original article]() Published: 2026-06-02T09:00:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [codex](), [Artificial Intelligence](), [software-development](), [data analytics](), [dashboards](), [Incident response](), [Machine learning]() Tags: [ai](), [codex](), [dashboards](), [data-analytics](), [developers](), [incident-response](), [machine-learning](), [product](), [software-development](), [workflow](), [workflows]() ### AI overview OpenAI introduces role-specific Codex plugins, annotations, and a preview of shareable interactive websites and apps. The plugins connect Codex to existing tools and workflows for analytics, creative production, sales, and other knowledge-work roles, including data exploration, dashboards, campaign assets, customer-context workflows, and machine-learning infrastructure experiments. ### Source excerpt Discover new Codex plugins, sites, and annotations that help analysts, marketers, designers, investors, and other teams get more done with AI. ## From SSH to REST: A Security-Driven Modernization of Slack's EMR Data Pipelines DevFeed: [From SSH to REST: A Security-Driven Modernization of Slack's EMR Data Pipelines]() Original publisher: [Read original article]() Author: Mahendran Vasagam Published: 2026-05-05T14:00:01Z Content type: article Language: en Sources: [Engineering at Slack]() Topics: [Security](), [OpenSSH](), [Amazon Web Services](), [airflow](), [DataOps](), [Architecture & Design](), [Kubernetes]() Tags: [airflow](), [architecture](), [aws](), [big-data](), [data-analytics](), [data-engineering](), [data-infrastructure](), [kubernetes](), [modernization](), [security](), [ssh](), [uncategorized]() ### AI overview Slack describes migrating more than 700 SSH-based data pipeline jobs to a REST-based architecture across eight data regions, eliminating SSH access to production AWS EMR clusters without downtime. The article explains the security and operational problems that motivated the modernization, including attack-surface exposure, key-management overhead, resource contention, broken connections, zombie jobs, and unreliable job-status detection. ### Source excerpt Excerpt By 2024, Slack's data platform had accumulated 700+ SSH-based operators orchestrating critical data pipelines. We're talking daily search indexing that processed terabytes of data, analytics jobs powering business intelligence, the whole shebang. Every single one of these jobs required direct SSH access to production AWS Elastic MapReduce (EMR) clusters. We had a massive security... ## Gala supercharges analytics performance with ClickHouse on AWS DevFeed: [Gala supercharges analytics performance with ClickHouse on AWS]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-05-04T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Amazon Web Services (AWS)](), [data analytics](), [Data Infrastructure](), [data-platforms](), [telemetry](), [databricks](), [Blockchain]() Tags: [aws](), [blockchain](), [clickhouse](), [data-analytics](), [data-infrastructure](), [data-platforms](), [databricks](), [telemetry]() ### AI overview Gala migrated from Databricks to ClickHouse on AWS to address growing data volumes and improve analytics performance. The article reports a threefold increase in analytics capacity, a 30% cost reduction, and query times reduced from minutes to sub-second. ### Source excerpt Learn how Gala migrated to the ClickHouse to improve analytics performance and cut costs ## Smarter Ad Spending: 5 Marketing Analytics Strategies to Optimize Your Budget DevFeed: [Smarter Ad Spending: 5 Marketing Analytics Strategies to Optimize Your Budget]() Original publisher: [Read original article]() Author: KHALIL KAFROUNI, MARKETING EXPERT @ TOPTAL Published: 2026-04-15T04:00:00Z Content type: article Language: en Sources: [Toptal Blog]() Topics: [data analytics](), [Optimization](), [databricks]() Tags: [advertising](), [analytics](), [data](), [data-analytics](), [marketing](), [optimization]() ### AI overview This article presents five marketing analytics strategies for optimizing advertising budgets, reducing wasted spend, and improving marketing ROI through data-informed decision-making. ### Source excerpt Learn expert-backed strategies to optimize your advertising budget, avoid wasted spend, and drive higher marketing ROI through data-informed decision-making. ## ClickHouse achieves AWS Financial Services Competency DevFeed: [ClickHouse achieves AWS Financial Services Competency]() Original publisher: [Read original article]() Author: Aditya Chidurala Published: 2025-12-12T00:00:00Z Content type: news Language: en Sources: [ClickHouse Blog]() Topics: [data](), [Temporal data](), [Security, Privacy and Abuse Prevention](), [AI, ML & Data Engineering]() Tags: [analytics](), [aws](), [clickhouse](), [data-analytics](), [financial-services](), [fraud](), [machine-learning](), [partners](), [real-time](), [scalability](), [time-series]() ### AI overview ClickHouse announces its AWS Financial Services Competency and describes how financial organizations use its analytics platform for high-volume, low-latency workloads. ### Source excerpt ClickHouse has achieved AWS Financial Services Competency, joining a select group of AWS Partners recognized for deep expertise in serving financial services organizations. ## Mixpanel security incident: what OpenAI users need to know DevFeed: [Mixpanel security incident: what OpenAI users need to know]() Original publisher: [Read original article]() Published: 2025-11-26T19:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [incident]() Tags: [analytics](), [api](), [chatgpt](), [company](), [data](), [data-analytics](), [datasets](), [frontend](), [incident](), [openai](), [security]() ### AI overview OpenAI describes a Mixpanel security incident involving limited analytics and customer-identifiable information for some API users and a limited number of ChatGPT users. It says OpenAI systems were not breached and that chats, API requests, credentials, API keys, and payment details were not exposed. ### Source excerpt OpenAI shares details about a Mixpanel security incident involving limited API analytics data. No API content, credentials, or payment details were exposed. Learn what happened and how we're protecting users. ## October 2025 newsletter DevFeed: [October 2025 newsletter]() Original publisher: [Read original article]() Author: Mark Needham Published: 2025-10-15T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [real-time](), [data analytics](), [migration](), [PostgreSQL](), [Apache Iceberg](), [observability]() Tags: [2025](), [clickhouse](), [data](), [data-analytics](), [data-processing](), [migration](), [newsletter](), [observability](), [postgresql](), [real-time](), [tools](), [training]() ### AI overview The October 2025 ClickHouse newsletter covers a new text index, request logging at billion-event scale, messy-data modeling for OLAP, lakehouse queries from ClickHouse Cloud, and related community and training events. ### Source excerpt Welcome to the October 2025 ClickHouse newsletter, which will round up what's happened in real-time data warehouses over the last month. ## SEON Achieves 80% Faster Database Performance for Anti-Fraud Platform with ClickHouse on AWS DevFeed: [SEON Achieves 80% Faster Database Performance for Anti-Fraud Platform with ClickHouse on AWS]() Original publisher: [Read original article]() Author: AWS Published: 2025-07-23T09:16:59Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Amazon Web Services (AWS)](), [Database](), [data analytics](), [real-time](), [Scalability](), [Security, Privacy and Abuse Prevention](), [API](), [Machine learning]() Tags: [analytics](), [api](), [aws](), [clickhouse](), [data](), [data-analytics](), [database](), [database-performance](), [fraud](), [machine-learning](), [performance](), [real-time](), [scalability](), [storage]() ### AI overview SEON worked with ClickHouse and AWS to improve the performance and scalability of its anti-fraud and anti-money-laundering platform. The solution reduced processing time by more than 80 percent while supporting near-real-time transaction analysis and large, customized rule sets. ### Source excerpt Learn how anti-fraud platform SEON worked with ClickHouse and used AWS to improve near real-time data analytics by 80% and reduce data storage costs by 30% ## Turning Spain's blackout into real-time insights DevFeed: [Turning Spain's blackout into real-time insights]() Original publisher: [Read original article]() Author: Iago Enríquez Published: 2025-07-11T10:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [data analytics](), [real-time](), [data]() Tags: [analytics](), [data](), [data-analytics](), [i-built-this](), [real-time]() ### AI overview The article examines how real-time data analytics could help understand the work of the electric grid in the context of Spain's blackout. ### Source excerpt How real data analytics could help to understand electric grid's work ## Measuring Commercial Impact at Scale at Canva DevFeed: [Measuring Commercial Impact at Scale at Canva]() Original publisher: [Read original article]() Author: Jun Ye Published: 2025-06-20T00:00:01Z Content type: article Language: en Sources: [Canva Engineering]() Topics: [experiments](), [Streamlit](), [data analytics](), [App](), [Software as a service]() Tags: [data-analytics](), [development](), [experiment](), [experimentation](), [metrics](), [product](), [streamlit]() ### AI overview Canva describes its IMPACT app, an internal data product built with Snowflake, Streamlit, Snowpark, and Cortex. The app provides self-service estimates of commercial impact for experiment analysis using standardized logic aligned with Canva's finance model. ### Source excerpt How We Built Canva's IMPACT App with Streamlit in Snowflake ## OpenTelemetry Basics on Heroku Fir DevFeed: [OpenTelemetry Basics on Heroku Fir]() Original publisher: [Read original article]() Author: Alex Arnell Published: 2025-05-27T14:59:43Z Content type: tutorial Language: en Sources: [Heroku]() Topics: [Heroku](), [OpenTelemetry](), [telemetry](), [Cloud]() Tags: [cloud](), [cloud-infrastructure](), [cloud-native](), [data-analytics](), [developer-tools](), [engineering](), [fir](), [go](), [guide](), [heroku](), [observability](), [opentelemetry](), [telemetry](), [traces]() ### AI overview This tutorial explains OpenTelemetry and how Heroku built it into the Fir platform. It describes OpenTelemetry's role in collecting logs, metrics, and traces for observing, troubleshooting, and improving distributed applications. ### Source excerpt Heroku recently made the next generation platform - Fir - generally available. Fir builds on the strengths of the Cedar generation while introducing a new modern era of developer experience. Fir leverages modern cloud-native technologies to provide a seamless and performant platform. One of the goals we set out to achieve with Fir is to [...] The post OpenTelemetry Basics on Heroku Fir appeared first on Heroku. ## Introducing Heroku-Streamlit: Seamless Data Visualization DevFeed: [Introducing Heroku-Streamlit: Seamless Data Visualization]() Original publisher: [Read original article]() Author: Anush DSouza Published: 2025-05-01T08:00:09Z Content type: release Language: en Sources: [Heroku]() Topics: [Heroku](), [Streamlit](), [Template](), [Python](), [web applications](), [Cloud](), [Data visualization](), [Data Science](), [Open Source]() Tags: [ai](), [data-analytics](), [data-visualization](), [deploy](), [deployment](), [developer-tools](), [dockerignore-usage](), [getting-started](), [heroku](), [news](), [open-source](), [prototyping](), [python](), [streamlit](), [web-applications]() ### AI overview Heroku announces Heroku-Streamlit, a ready-to-deploy template for deploying interactive Streamlit data visualization applications on Heroku. The template combines Heroku's cloud platform with Streamlit's Python framework and includes one-click deployment, sample Uber pickup data, customization options, and manual deployment instructions. ### Source excerpt We're excited to announce the release of Heroku-Streamlit, a template that makes deploying interactive data visualization applications on Heroku simpler than ever before. Streamlit is an open-source app framework built for machine learning and data science projects. This Streamlit App brings together Heroku's scalable cloud platform and Streamlit's intuitive Python-based data application framework. Whether you're [...] The post Introducing Heroku-Streamlit: Seamless Data Visualization appeared first on Heroku. ## Anlytic.com - Big-Data Analytics at the Dutch Police DevFeed: [Anlytic.com - Big-Data Analytics at the Dutch Police]() Original publisher: [Read original article]() Author: ClickHouse Published: 2025-05-01T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [data](), [dashboards]() Tags: [analytics](), [aws](), [big-data](), [clickhouse](), [dashboards](), [data-analytics](), [data-infrastructure](), [database](), [performance](), [scalability]() ### AI overview An interview with Anlytic.com about using ClickHouse and ClickHouse Cloud on AWS for data analytics, including dashboard production work for the Dutch National Police. The supplied excerpt describes ClickHouse as faster than Snowflake for the stated workloads. ### Source excerpt "If we are looking at high-performance database systems for these types of workloads, the only two options are ClickHouse and Snowflake. ClickHouse is significantly faster." - Martijn Witteveen, CEO [Next page]()