Tech Insights

Visual Analytics

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What is Visual Analytics?

Visual analytics combines data analysis with interactive visualizations. It aims to enable users to gain insights, discover patterns, and make informed decisions from complex data sets. It is commonly used in business intelligence, scientific research, and data exploration.

What other technologies are related to Visual Analytics?

Visual Analytics Competitor Technologies

Microsoft Pivot is a tool for visual exploration of large datasets, making it a direct competitor in the visual analytics space.
mentioned alongside Visual Analytics in 95% (195) of relevant job posts
Palantir provides a suite of tools for data integration, analysis, and visualization, making it a direct competitor.
mentioned alongside Visual Analytics in 2% (199) of relevant job posts
SAS Viya offers advanced analytics and visualization capabilities, making it a competitor in the visual analytics space.
mentioned alongside Visual Analytics in 2% (61) of relevant job posts
Business Intelligence encompasses many of the same technologies and processes as Visual Analytics. It is therefore a competitor.
mentioned alongside Visual Analytics in 0% (62) of relevant job posts

Visual Analytics Complementary Technologies

Entity identification and tagging are used to prepare and enrich data for visual analytics, making it a complementary technique.
mentioned alongside Visual Analytics in 77% (115) of relevant job posts
LSI can be used to transform unstructured data into a more useful format for visualization. It can improve the insights derived from visual analysis by creating better data.
mentioned alongside Visual Analytics in 82% (55) of relevant job posts
Mahout provides machine learning algorithms that can be used to preprocess and analyze data for visual analytics, which makes it complementary.
mentioned alongside Visual Analytics in 23% (192) of relevant job posts

Which job functions mention Visual Analytics?

Job function
Jobs mentioning Visual Analytics
Orgs mentioning Visual Analytics
Data, Analytics & Machine Learning

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