IBM Cognos Analytics documentation
https://www.ibm.com/docs/en/cognos-analytics/11.1.0?topic=manuals
- by Saif AdilFrom : Blog Entry >> Saif's Blog EntryDeploying Medical Diagnosis AI on IBM Fusion with Red Hat Validated Patterns Building on-premises AI inference pipelines for healthcare with complete data sovereignty and regulatory compliance Introduction Healthcare organizations face a fundamental tension: deploying AI-driven diagnostic systems at scale while maintaining strict data privacy, regulatory compliance, and cost […]
- by PAUL BASTIDEFrom : Blog Entry >> PAUL's Blog EntryMany IBM customers run IBM Power workloads in secure environment, where the convenience of a direct internet connection for the workload is restricted or strictly prohibited. For OpenShift Container Platform clusters in these Disconnected environments , the clusters are configured to retrieve release images from a registry or […]
- by YOICHIRO NISHIMAKIFrom : Blog Entry >> YOICHIRO's Blog Entry皆さんこんにちは。IBM Data PlatformでデータサイエンスTech Salesをしている山下です。 このリレー連載ブログは第一線で活躍するデータ分析者に、データ活用を進める上で忘れられない教訓をインタビュー形式で伺い、これからデータ分析に取り組む皆様に参考にしていただくことを目的にしています。 今回インタビューをお願いしたデータ分析者は 株式会社朝日新聞社でデータソリューション部に所属する木村様にインタビューをお願いしました。 木村 慎太郎 様 株式会社朝日新聞社 メディア事業本部 データソリューション部 データマネジメント担当次長 -日頃のデータ活用業務について教えてください 私はメディア事業本部データソリューション部で、データ基盤に格納された会員データやメディア閲読データなどを横断的に管理しながら、各事業部の意思決定をデータで支える役割を担っています。 日常業務は、事業部からの非定型の分析依頼対応や、 KPI ダッシュボードの管理、 CRM 施策改善などが中心です。 これらのうち、非定型の分析依頼対応は分析結果をレポートに落とすだけでは価値が生まれません。事業部と対話を重ね、ネクストアクションに落とし込める形で示唆を提示するところまでが、私たちデータ分析者の仕事だと考えています。 [More]
- by Jose Luis Señas CuestaFrom : Groups >> Planning AnalyticsHi All, We have PAW on IBM Cloud. I have this cube, years, months, days, products, metrics dimension (dias_inv) and a placehoder dimension with one element, Valor, numeric.: Then, I select product 0071328, for instance, and ask the assistant for Outliner analysis. And this is what I have got: Is […]
- by SAMI EL CHEIKHFrom : Blog Entry >> SAMI's Blog EntryThe Planning Analytics Assistant is constantly evolving. Our strategy includes leveraging new and improved features as well as updated support for large language models. As IBM moves away from Granite 3 models in support of Granite 4, Planning Analytics Assistant now supports Granite 4-small for all it’s features […]
- by Ankit BargaleFrom : Blog Entry >> Ankit's Blog EntryBy bridging SaaS convenience with on‑prem flexibility, QRadar continues to redefine what secure, intelligent, and compliant SIEM looks like in the age of AI. In May 2025, IBM launched the QRadar Investigation Assistant app that helps security teams accelerate investigations by integrating generative AI into IBM QRadar SIEM, […]
- by Bruce McKnightFrom : Blog Entry >> Bruce's Blog EntryWhitepaper: Applying Evolutionary Computation to SMF-Derived Enterprise Insights on z/OS Author: Bruce McKnight Teaching decades-old mainframes some new AI tricks. Executive Summary This paper presents a prototype methodology of genetic algorithms (GA) and cellular automata (CA) to show how AI can extract insights from legacy mainframe data and […]
- by Vitalij RusakovskijFrom : Groups >> Planning AnalyticsDear all, some days ago, we had an issue with the conditional formatting in PAW for 2 dimensions: like, current value for the actual and dependency to the account dimension, e.g. for costs account there should be a different condition than for revenue accounts. With help and some hints from […]
- by Jason KahnFrom : Blog Entry >> Jason's Blog EntryFNCM on Containers: GCS Fuse Storage on GKE Introduction Welcome to another installment in our FNCM on Containers series! This guide provides step-by-step instructions on how to set up Google Cloud Storage (GCS) Fuse on Google Kubernetes Engine (GKE) for FileNet Content Manager deployments. By leveraging GCS Fuse, […]
- by Enikő HusztiováFrom : Blog Entry >> Enikő's Blog EntryIBM Technology Lifecycle Services (TLS) is pleased to announce the availability of IBM Data PreQualification Service, a customizable on-prem data cleansing service designed to help clients prepare data for external sharing while supporting compliance with data security and privacy regulations. IBM Data PreQualification Service enables clients to securely […]
- by Vitalij RusakovskijFrom : Groups >> Planning Analyticsthanks for sharing, Wim! —————————— Vitalij Rusakovskij ——————————
- by George TonkinFrom : Groups >> Planning AnalyticsIn a recent session with IBM there was reference made to O365 and PAfE for 2026 – no timelines and yes, not on the roadmap but maybe someone from IBM can clarify further. http://ibm.biz/pa-roadmap Microsoft Excel PAfE support for Office 365 on the web, centralized control —————————— George Tonkin Business […]
- by Subhash KumarFrom : Groups >> Planning AnalyticsIt has been about a year since we moved away from Perspectives/Architect and fully on-boarded to PAfE. MacOS users are still asking when they will get it. I recall hearing PAfE coming for web Excel, but I don't see anything mention in the roadmap. Is it already released or not […]
- by Ben ThompsonFrom : Blog Entry >> Ben's Blog EntryIn December 2024 IBM published a Statement of Direction regarding our future plans for supporting different versions of Java within ACE 13. Since that time, more than a year has now passed and a new Statement of Direction has recently been published, so this is a great time […]
- by John AlexanderFrom : Blog Entry >> John's Blog EntryOur ongoing investments in engineering, roadmap innovation and hybrid ecosystem integration reflect IBM’s focus on delivering a powerful, future‑ready analytics engine. Netezza brings simplicity, speed and reliability across deployment models—from fully managed cloud to BYOC, on‑prem appliances, and software‑only—so organizations can run analytics where it makes the most […]
- by Bruce McKnightFrom : Blog Entry >> Bruce's Blog EntryWhitepaper: Applying Evolutionary Computation to SMF-Derived Enterprise Insights on z/OS Author: Bruce McKnight Teaching decades-old mainframes some new AI tricks. Executive Summary This paper presents a prototype methodology of genetic algorithms (GA) and cellular automata (CA) to show how AI can extract insights from legacy mainframe data and […]
- by Venkata Vamsikrishna MeduriFrom : Blog Entry >> Venkata Vamsikrishna's Blog EntryAuthors : Venkata Vamsikrishna Meduri, Justin Haakenson, Lisa Huston, Umesh Deshpande, Eric Erpenbach, Jose Ortiz, Swaminathan Sundararaman This blog details how the search capability in IBM Fusion Content-aware Storage (CAS) surpasses state-of-the-art information retrieval systems on the widely adopted BEIR ( Be nchmarking I nformation R etrieval) […]
- by Shawn RobertsonFrom : Blog Entry >> Shawn's Blog EntryCo-authors: Shawn Robertson, @KATIE LE Iceberg, Right Ahead! Today’s organizations require fresh, reliable data that can be easily consumed across multiple systems and regions to power analytics and AI workloads. At the same time, they are consolidating data onto low-cost, scalable storage to reduce infrastructure expense while still […]
- by Allison GaynorFrom : Blog Entry >> Allison's Blog EntryIBM watsonx Assistant for Z is transforming how enterprises interact with the IBM Z platform—introducing powerful agentic AI capabilities that accelerate outcomes, simplify complexity, and drive new levels of productivity. Mainframe teams today face mounting pressure to expand their talent pools while meeting rising productivity expectations. IBM watsonx […]
- by Eric WalkFrom : Blog Entry >> Eric's Blog EntryThanks to everyone who joined our user group meeting today! Generated by AI. Be sure to check for accuracy. Meeting notes: User Group Purpose and Meeting Format: Eric Walk led a discussion with the user group about the purpose, structure, and desired outcomes of the Q126 Enterprise Records […]