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Visual Analytics

A hub of the site's IT directories: infrastructure and hardware, cloud and networking, software, data and AI, security, operations, enterprise IT, and careers and learning.

43 topics•6 categories•Updated November 2026

Visualization Tools & Dashboards

8 entries

Tools and guides for charts, dashboards and visual exploration.

01Data Visualization ToolsDashboards, charting libraries, Python apps and maps. 02Data & Knowledge VisualizationCharting, dashboards, graph and knowledge visualization. 03Visualization Tools for Time Series DataPlotly, Grafana, Dash and other time series tools. 04BI Tools & DashboardsPower BI, Tableau, Looker, Superset and open BI. 05Analytics & BI PlatformsEnterprise analytics and business intelligence platforms. 06Semantic Layers & Metric StoresGoverned metrics behind consistent dashboards. 07Data Science IDEsNotebooks and IDEs for exploratory analysis. 08Python for Data SciencePython libraries for analysis and plotting.

Analytics by Data Type

11 entries

Visual and analytical methods for different kinds of data.

09Video AnalyticsDetection, tracking, video AI tools and datasets. 10Video Data Analytics SolutionsVideo and camera-based analytics. 11Image Data Analytics SolutionsComputer vision and image analysis. 12Text Data Analytics SolutionsText analytics and language insight. 13Text MiningTechniques for extracting patterns from text. 14Speech Analytics PlatformsSpeech and call analytics. 15Audio AnalyticsSpeech, sound and audio analytics tools and datasets. 16Audio Data Analytics SolutionsAudio analysis and sound recognition. 17Time-Series DatabasesStorage for metrics and sensor data. 18Graph DatabasesNetworks and relationships as graphs. 19Knowledge GraphsConnected knowledge for visual exploration.

Real-Time & Operational Analytics

8 entries

Live dashboards over streaming and operational data.

20Real-Time Data AnalyticsStreaming engines, real-time OLAP and live pipelines. 21Streaming Analytics PlatformsContinuous analytics over events. 22Operational AnalyticsAnalytics that drive operational decisions. 23IoT Data AnalyticsAnalytics on sensor and device data. 24Edge Data AnalyticsAnalytics close to the data source. 25Observability ToolsMetrics, logs and traces dashboards. 26Log Analytics & Management ToolsSearching and visualizing logs. 27Security Analytics ToolsVisual analysis of security data.

Analytics, Mining & Explainable AI

8 entries

Finding and explaining patterns in data.

28Data AnalyticsHub for analytics platforms and tools. 29Data MiningTechniques, software and datasets. 30Data SciencePlatforms, notebooks and data wrangling. 31Machine LearningPlatforms, frameworks, MLOps and AutoML. 32XAI FrameworksExplaining model predictions visually. 33StatisticsStatistical methods behind visual analysis. 34Process Mining SoftwareProcess analytics from event logs. 35Customer Data PlatformsCustomer analytics and activation.

Data Foundations

6 entries

Trusted data behind every visualization.

36Data WarehousingWarehouse design, platforms and ETL. 37Data LakesObject storage, formats and query engines. 38Data QualityCleaning and validating data. 39Data Science PlatformsPlatforms for exploration and modelling. 40Digital Analytics SolutionsWeb and digital experience analytics. 41Data Analytics Courses and CertificationsCourses and credentials for analysts.

Related Pages

2 entries

Related pages on this site.

42Data AnalyticsHub for analytics platforms and tools. 43Data Visualization ToolsDashboards, charts and maps.

Frequently Asked Questions

What is visual analytics?

An approach that combines interactive visualization, data analysis and human judgement so people can explore data, spot patterns and make decisions. It goes beyond static charts by letting users filter, drill down and iterate.

How is visual analytics different from data visualization?

Data visualization presents data graphically. Visual analytics adds analysis, interaction and often machine learning so users can investigate questions, not just view results. See the Data Visualization Tools page.

How is it different from business intelligence?

BI focuses on governed reporting and dashboards for known questions. Visual analytics emphasises open-ended exploration. Many BI tools now support both. See the BI Tools & Dashboards page.

Which tools are used for visual analytics?

Power BI, Tableau, Looker Studio and Apache Superset for dashboards, Grafana for operational data, and libraries such as D3.js, Plotly, ECharts and Python tools such as Altair and Streamlit for custom work.

How does explainable AI relate to visual analytics?

Visual explanations such as feature importance and partial dependence plots help people understand model behaviour. See the XAI Frameworks page.

Can visual analytics work on live data?

Yes. Streaming engines and real-time OLAP stores can feed dashboards that refresh within seconds. See the Real-Time Data Analytics and Streaming Analytics Platforms pages.

What makes a good visualization?

A clear question, the right chart type, honest scales, restrained colour, accessible contrast and trustworthy data. See the Data Quality and Semantic Layers pages for the data side.

What does this hub cover?

It links only to pages on this site, grouped into visualization tools, analytics by data type, real-time analytics, mining and explainable AI, and data foundations. Each linked page records its own link checks.