DataWalk Graph Analytics


Unique DataWalk graph-based technology enables performing no-code graph analysis at scale without building new graph technology competencies in your organization.

​​DataWalk is relationship-oriented software that enables graph analysis at scale through a set of analytic techniques based on how business entities such as people, places, and things are related to each other. DataWalk’s graph analysis foundation uniquely enables you to connect data, understand structures, and identify patterns in large highly-connected datasets through a highly-efficient knowledge graph.

Fuse All Your Data To Capture Business Knowledge


Datawalk enables you to quickly integrate and link all your internal and external data in a business representation through connections between business entities, processes, and events. This graph analysis foundation allows you to derive new insights and patterns from vast amounts of existing data and metadata quicker than ever.

Answer Complex Business Questions Through A Knowledge Graph


Being able to formulate and answer complex business questions is a crucial DataWalk graph analytics capability. DataWalk uniquely meets the challenge for big data query tools, enabling you to quickly generate complex no-code queries that quickly complete, even across vast amounts of data. The knowledge graph query facility enables visual exploration and interaction with graph data structures allowing insights to be found without the need for any query language. Unlike alternative solutions built around joining multiple tables, with the DataWalk knowledge graph you walk through business data sets using persistent and available links. Queries can be saved and easily modified or re-run by casual users - with reproducible results - and if desired, you can combine saved queries into flexible scores.

Graph Analysis Enablements


DataWalk graph analysis enhances human intelligence through several graph algorithms. These include finding optimal paths between two or more data objects, community detection to identify clusters, and connectivity algorithms prioritizing what to look at first in a network.

Efficient Artificial Intelligence (AI)


DataWalk graph analytics improves the process for creating efficient machine learning (ML), explainable artificial intelligence (xAI), and other types of AI solutions. Graph analysis enables data scientists and data engineers to create a richer set of features and training sets based on relationships between data points. Embedded AutoML and xAI engines enable data scientists and analysts to automate the generation and explanation of machine learning models. All ML models can be developed with real data and then be instantly deployed in production without re-coding. This enables data scientists, data engineers, and developers to accelerate the deployment cycle and quickly get to production results.
 

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