---
title: "Analytics"
description: "32 posts about Analytics, summarised, each linking to the original."
---

# Analytics
> 32 posts about Analytics, summarised, each linking to the original.

## Articles

### [OLTP vs. OLAP: Choosing Between Transactional and Analytical Databases](https://yomu.fyi/post/oltp-vs-olap-choosing-between-transactional-and-analytical-databases.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Oct 14, 2026
- Type: Explainer

OLTP handles high-volume, low-latency transactions on current operational data for online banking, e-commerce, and inventory, while OLAP handles complex analytical queries on large historical datasets for financial analysis and business intelligence. OLTP databases ensure data integrity through ACID compliance and use normalized row-oriented tables; OLAP systems use denormalized dimensional models and columnar storage for efficient scans and aggregations. Data pipelines such as ETL or CDC tools like Debezium connect OLTP and OLAP systems, but latency and pipeline complexity rise with analytical freshness requirements. For mixed workloads, HTAP or lakehouse architectures can reduce synchronization overhead and analytical lag. The choice between OLTP and OLAP depends on the workload’s read-write pattern, latency needs, and data volume, with TPC-C and TPC-H as reference benchmarks.


### [Databricks is a Visionary the Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms](https://yomu.fyi/post/databricks-is-a-visionary-the-gartner-r-magic-quadranttm-for-analytics.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Chao Cai, Kayli Berlin, Miranda Luna
- Published: Oct 13, 2026
- Type: Announcement

Databricks debuted as a Visionary in the 2026 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms, achieving the highest debut performance in the report’s 20+ year history. The company also received one of the highest Completeness of Vision scores among all vendors evaluated. Databricks attributes this recognition to its ability to deliver on three major trends reshaping businesses: data and AI platform convergence, agentic analytics, and semantics at the core. The Databricks lakehouse integrates BI directly, eliminating data silos and the need for extracts, so agents can reason over complete, governed context. With Genie and AI/BI, the platform automates complex workflows and provides a unified semantic layer through Unity Catalog Business Semantics and Genie Ontology.


### [Built for you: Custom Reports, Conversation Topics, Macros, and more to personalize customer communication - The Intercom Blog](https://yomu.fyi/post/built-for-you-custom-reports-conversation-topics-macros-and-more-to-pe.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 9, 2026
- Type: Announcement

Intercom launched a suite of new features including Custom Reports, Conversation Topics, and Macros to help teams balance personal and efficient customer communication at scale. Custom Reports lets teams tailor dashboards in just a few simple steps by building custom charts from user and conversation data attributes and exporting them. Conversation Topics provides a machine-learning powered engine that visually represents what customers are talking about and how often, giving teams an at-a-glance view of top concerns. Macros automate common inbox actions like tagging, assigning, snoozing, and closing conversations with a single click, boosting efficiency by up to 43%. Additional updates include Series targeting and split testing, enhanced Articles, mobile app tagging, permissions, and custom return paths for email deliverability.


### [Does your support team know more about your product than you?](https://yomu.fyi/post/does-your-support-team-know-more-about-your-product-than-you.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 9, 2026
- Type: Problem & solution

Customer support teams interact with customers daily and possess valuable product and customer insights that product teams often overlook. Treating support as an outsourced function or ignoring their conversations wastes unsolicited feedback that differs from survey data. Intercom tags every support conversation with team and category tags to make feedback actionable, enabling product teams to create dashboards, spot trends, and explore conversations for insights. For example, tagging ‘product confusion’ revealed an onboarding issue where customers saw nothing if they only completed one of two setup steps, leading to a pop-up that told customers exactly what they needed to do and reduced those conversations. Product teams also use tags like ‘unaware’ to improve feature discoverability, track bug reports via a GitHub integration, and compile quarterly ‘customer voice reports’ of top feature requests while closing the feedback loop with customers.


### [Revealing The 3 Customer Service Trends to Act on in 2022](https://yomu.fyi/post/revealing-the-3-customer-service-trends-to-act-on-in-2022.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 8, 2026
- Type: Explainer

Klaus 2022 Customer Service Quality Benchmark Report, based on a survey of 300 support leaders, identifies three key trends. First, support teams are measuring impact more than ever: average CSAT rose 14% to 89%, and average NPS increased from 45 to 51; 10% more teams track CSAT, and NPS tracking jumped from 28% to 48%. Second, maintaining quality at scale is the top challenge, with 40% citing reducing repetitive queries; teams use first-party data, chatbots, and automation to deliver personal, fast support while scaling. Third, proactive and self-serve support are growing priorities: 70% plan to invest more in proactive support, and 73% found self-service reduced workload; knowledge bases compound in value over time. The report recommends focusing on the right metrics, collaborating with sales and marketing, and continuously learning and optimizing to elevate support’s business role.


### [Building Reliable Data Analytics Agents: Lessons from the KDD Cup](https://yomu.fyi/post/building-reliable-data-analytics-agents-lessons-from-the-kdd-cup.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Jiwei Liu
- Published: Oct 8, 2026
- Type: Explainer

The NVIDIA KGMON team placed second in the KDD Cup 2026 Data Agents competition by building a reliable agent system around a small, fixed LLM. The system constrained the agent’s action space through a harness that normalized data access by converting CSV and JSON files into SQLite tables, exposed a limited set of custom functions for schema inspection, SQL queries, and answer writing, and seeded the agent with schema context before analysis. Documents and videos were handled through targeted tools like prose\_helper for extracting rules from documents and keyframe extraction with aligned transcripts for video evidence, keeping the main LLM context focused. The team emphasized inspectability by recording execution traces and running repeated attempts, using evaluation and trajectory review to identify failures and refine the harness. The key lesson is that reliability for data analytics agents often comes from the harness design, not the model’s capabilities.


### [How Customer Service Metrics Are Changing in the Age of AI - The Intercom Blog](https://yomu.fyi/post/how-customer-service-metrics-are-changing-in-the-age-of-ai-the-interco.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 8, 2026
- Type: Explainer

Customer service metrics must evolve as AI chatbots become the first point of contact for support teams. Traditional metrics like first response time and average handle time now need separate reporting for bot and human interactions, since AI delivers near-instant responses and handles simpler queries. Cases handled loses relevance as support reps focus on more complex issues and tasks such as help center content creation; automated resolution rate becomes a key productivity measure. New emerging metrics include bot involvement rate, bot engagement rate, and AI-powered conversational insights that analyze customer interactions at scale. Leaders should reset SLAs and benchmarks while tracking both bot and human performance to get a true measure of success, as 69% of support leaders plan to increase AI investment.


### [Identify AI model overuse with User Insights](https://yomu.fyi/post/identify-ai-model-overuse-with-user-insights.md)
- Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md)
- Author: Frank Meszaros
- Published: Sep 30, 2026
- Type: Announcement

Cloudflare AI Gateway’s User Insights now provides context beyond model names and request counts, using a dedicated Worker to classify conversations by task type such as coding, research, summarization, or formatting. The “model overkill” view identifies conversations where a high-capability reasoning model is used for simple tasks, showing which users or agents are driving that usage and the associated cost. Teams can analyze conversation turns to see how many back-and-forth exchanges a task requires, helping uncover inefficiencies in prompts or workflows. The Potential Savings view and Auto Router (closed beta) use task and model-fit signals to automatically route requests to appropriate models without a separate rule for each workload. These features are free for AI Gateway users and require stable user\_id and session\_id for analysis, with optional Access integration.


### [7 new Brandwatch AI updates that make your life easier](https://yomu.fyi/post/7-new-brandwatch-ai-updates-that-make-your-life-easier.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Nesibe Zirzakiran
- Published: Sep 29, 2026
- Type: Announcement

Brandwatch introduced seven AI-powered updates to help analysts, marketers, and social media managers keep pace with fast-moving online conversations. Iris AI features like Query Writer and Query Fixer streamline building comprehensive research queries by allowing a user to describe a topic through chat. The Ask Iris AI chat on the homepage and dashboards delivers instant summaries and topic breakdowns without requiring a pre-built query. Enhanced Alert and Signal emails now include AI-generated summaries so users can assess breaking stories or issues without reading individual mentions. Other updates include AI-generated categories for segmenting datasets, industry benchmarks for social performance, semantic search for YouTube creator discovery, and automated message classifiers in Engage.


### [Is your domain using post-quantum encryption? Now you can see for yourself](https://yomu.fyi/post/is-your-domain-using-post-quantum-encryption-now-you-can-see-for-yours.md)
- Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md)
- Author: Sharon Goldberg
- Published: Sep 29, 2026
- Type: Announcement

Cloudflare introduced new post-quantum cryptography visibility tools in its Application Security and Logs products, including Logpush, Log Explorer, and the HTTP Traffic Analytics dashboard, to help customers monitor encryption adoption. These tools surface the key exchange algorithm negotiated on every incoming request, enabling customers to audit their post-quantum posture, assess compliance, and identify cryptographic gaps across their domains. The primary post-quantum algorithm in TLS 1.3 is X25519MLKEM768, a hybrid of classical ECDHE over curve X25519 and the post-quantum ML-KEM, which provides belt-and-suspenders security against harvest-now-decrypt-later attacks. Cloudflare Radar data shows about 70% of browser-generated traffic uses post-quantum encryption on the visitor-to-Cloudflare connection, but only 15% of origin connections to Cloudflare use hybrid ML-KEM. For legacy origin servers that cannot support modern post-quantum cryptography, Cloudflare Tunnel can tunnel traffic over TLS 1.3 with X25519MLKEM768 without requiring any upgrade to the origin server itself.


### [ClickHouse Workload for Microsoft Fabric: sub-second analytics on OneLake, now in public preview](https://yomu.fyi/post/clickhouse-workload-for-microsoft-fabric-sub-second-analytics-on-onela.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Sep 29, 2026
- Type: Announcement

The ClickHouse workload for Microsoft Fabric brings ClickHouse as a native acceleration layer for OneLake, now in public preview. It provisions dedicated ClickHouse Cloud services on Azure via the Fabric Extensibility Toolkit, using a ClickHouse item in the workspace. Users sync OneLake tables through ClickPipes as point-in-time snapshots with no ingestion charges. The embedded SQL console and external tools (Power BI, Copilot Studio, GitHub Copilot) can then query billions of rows with sub-second response times at high concurrency. Planned future features include write-back to OneLake, continuous sync, permission sync, and deeper Power BI integration.


### [How fast is the web? Explore billions of real-user measurements with BEACON](https://yomu.fyi/post/how-fast-is-the-web-explore-billions-of-real-user-measurements-with-be.md)
- Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md)
- Author: Nic Jansma
- Published: Sep 28, 2026
- Type: Announcement

Cloudflare has released the BEACON dataset, an anonymized collection of billions of real-user performance measurements from 10,000 of the largest websites. The dataset reports Core Web Vitals (LCP, CLS, INP) with full histograms, enabling analysis of any percentile including the long tail. It reveals that WebKit browsers underperform Blink in 46 countries, and that resource-discovery and render-blocking contribute more to slow LCP than download time. Soft navigations in single-page applications load two to three times faster than hard navigations, but landing pages remain heavy. The dataset is publicly available on Google BigQuery and includes differential privacy via the RAPPOR algorithm to protect individual user data.


### [Databricks recognized as a Gartner® Peer Insights™ Customers' Choice for Analytics and BI](https://yomu.fyi/post/databricks-recognized-as-a-gartner-r-peer-insightstm-customers-choice.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Team Databricks
- Published: Sep 18, 2026
- Type: Announcement

Databricks says it was recognized as a Customers’ Choice in Gartner Peer Insights’ Voice of the Customer for Analytics and Business Intelligence Platforms, based on verified reviews from customers using platforms in production. The post reports a 4.8 out of 5 overall rating and 94% willingness to recommend, while noting that the designation reflects customer adoption and overall experience meeting or exceeding market averages. It presents Databricks AI/BI, AI/BI Dashboards, Genie Spaces, and Genie as a unified architecture combining governed live data, AI, business intelligence, and Unity Catalog controls without moving or duplicating datasets. The described use cases include conversational exploration, dashboard and visualization development, consolidating fragmented reporting, and expanding governed analytics access, with the company positioning these capabilities as a foundation for agentic analytics.


### [What is Agentic Analytics?](https://yomu.fyi/post/what-is-agentic-analytics.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Sep 18, 2026
- Type: Explainer

Agentic analytics is an approach in which autonomous AI agents continuously monitor data, detect patterns and anomalies, generate contextual insights, and take actions with minimal human intervention. Unlike traditional business intelligence, which relies on people to query dashboards and interpret reports, these systems operate as goal-directed decision loops that can recommend or trigger alerts, forecasts, workflows, and system changes within defined boundaries. Their architecture combines data access, agent orchestration, LLM-based reasoning, a semantic layer, action integrations, and feedback signals. The source identifies faster insight, lower reporting overhead, reduced analytics backlogs, and potentially better forecasting as benefits, while stressing governance, auditability, security, monitoring, and human oversight to control errors and unintended outcomes.


### [Why agentic analytics starts with a well](https://yomu.fyi/post/why-agentic-analytics-starts-with-a-well.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Catherine Brown
- Published: Sep 18, 2026
- Type: Explainer

Agentic analytics increases the need for trustworthy semantics and governance because AI systems must interpret business definitions, trace outputs, and support follow-up questions beyond static dashboards. Nick Eayrs argues that fragmented metrics across BI tools, proprietary semantic layers, and duplicated pipelines erode trust, slow decisions, and increase engineering cost. The proposed foundation is an open, interoperable semantic layer where certified metrics such as revenue, churn, and customer lifetime value are explicitly defined, reusable, and accessible through SQL to BI, AI interfaces, notebooks, and agents. Organizations should establish governed data foundations and a catalog first, certify metrics next, then add AI and evaluate its outputs. Examples include NTT Docomo reducing manual log-analysis time from 66 hours to 6 hours and Net One Systems cutting support response time by 75 percent.


### [Social Media Management & Consumer Intelligence | Brandwatch](https://yomu.fyi/post/social-media-management-consumer-intelligence-brandwatch.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Published: Sep 7, 2026
- Type: Explainer

Brandwatch describes an all-in-one social media suite that combines AI, analytics, channel management, consumer intelligence, and specialized tools for enterprise teams. Its consumer-intelligence offering provides access to the world’s largest archive of consumer opinion and uses proprietary and generative AI to identify emerging trends, while threat monitoring covers more than 100 million sources with real-time alerts. A collaborative content calendar supports channels, teams, workflows, approvals, and campaigns, and a unified social inbox handles community management and customer support across networks. The stated goal is to help organizations make better decisions, align content with their brands, respond quickly to threats, and produce measurable results and return on investment; the page also cites recognition by industry analysts and customer trust.


### [Measuring campaign impact with social and search data](https://yomu.fyi/post/measuring-campaign-impact-with-social-and-search-data.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Ksenia Newton
- Published: Aug 14, 2026
- Type: Explainer

Campaign post-mortems often report reach, engagement, impressions, and sentiment without establishing whether a campaign changed perception or behavior. It argues that social listening should measure sentiment, themes, mention volume, and audience conversation shifts, while search intelligence measures category and branded demand, promoted benefits, and share of search. A client example contrasts a campaign that generated strong social buzz while category search declined with a later campaign that reversed declining demand, captured two-thirds of share of search, and grew search intent 134%. The difference was attributed to combining socially engaging creative with media strategy and messaging designed to drive search demand. The proposed framework aligns measurement with campaign goals and uses gaps between social sentiment and search intent to identify awareness without demand, existing intent without audience expansion, or stronger market impact.


### [Which brand won the football tournament footwear battle](https://yomu.fyi/post/which-brand-won-the-football-tournament-footwear-battle.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Ksenia Newton
- Published: Aug 7, 2026
- Type: Benchmark

An analysis of footwear conversations around the 2026 World Cup compares how sponsorship, search demand, social attention, and sentiment shaped the competition between Adidas, Nike, Puma, New Balance, and other brands. Consumer Research tracked tournament-related mentions from June 11 to July 19 and paired them with search queries across the US, UK, and Canada. Adidas led tournament-specific footwear conversation with 63% of mentions, while Nike led broader brand discussion with 995k mentions, brand search momentum, and 78% positive sentiment. Nike’s cultural activations, including LISA’s “Rip The Script” campaign and Ronaldo’s Mercurial moments, generated shareable attention, whereas Adidas benefited from official sponsorship, the Trionda match ball, and player storytelling. Pink cleats became a cross-brand liability, attracting more than 5.5k mentions with nearly 70% negative sentiment, showing that visibility did not automatically produce favorable attention.


### [5 non-sponsor brand moments during this football summer](https://yomu.fyi/post/5-non-sponsor-brand-moments-during-this-football-summer.md)
- Company: [Brandwatch](https://yomu.fyi/company/brandwatch.md)
- Author: Ksenia Newton
- Published: Jul 16, 2026
- Type: Explainer

This analysis examines how five non-sponsor brands used football-related moments to gain attention without buying official tournament partnerships. Consumer Research tracked brand mentions in public social and news content from June 11 to July 8, identifying responses to clean-stadium rules, fan travel, beer shortages, and rising ranch interest. Levi’s covered-logo campaign generated 20.1k mentions, while Heinz’s taped condiment packaging produced 5.1k; Miller Lite and Delta reacted to the Tartan Army with a beer barge and airport welcome. Kraft followed a TSA post with a limited-edition “TSA-Compliant Ranch” kit, recording over 4k mentions and a 3,998% increase over the previous timeframe. The examples support a model based on speed, authenticity, and real-time listening, with social and search signals helping brands act while trends are building.


### [Welcoming Matt Gilbert, our new Data Analyst](https://yomu.fyi/post/welcoming-matt-gilbert-our-new-data-analyst.md)
- Company: [Resend](https://yomu.fyi/company/resend.md)
- Published: Jul 9, 2026
- Type: Announcement

Resend announces Matt Gilbert as a Data Analyst on its Trust & Safety team. He spent 10 years as a Deliverability Engineer at Mailchimp, handling Delivery-team data and maintaining sending infrastructure that pushed around a billion emails a day, after earlier work on the Mandrill transactional mail service. Gilbert describes email delivery as a multidisciplinary field spanning MTA operations, data engineering, analytics, mail-queue performance, and troubleshooting delivery and inbox-placement problems, which led him to specialize in data engineering and analytics. He says he joined Resend because email remains an open, globally available way for services to communicate, and plans to help build data-driven capabilities and intelligence that enable customers to send better and reach inboxes quickly.


[Older posts](https://yomu.fyi/topic/analytics/page/2.md)