How to Convert Boring CSV Files to Knowledge Graphs

In this video, Tom Ferrara demonstrates how you can use https://infranodus.com AI tool to analyze spreadsheet data with a knowledge graph. The advantage is the ability to represent relations between values in columns and cells, so you can uncover recurrent patterns, reveal the key themes and topics that emerge, as well as the blind spots between ideas. You can even build a social network from an Excel file based on this method.

Try it on https://infranodus.com

(00:00) Introduction: The limitations of CSVs and the power of network graphs.
(00:54) Importing Your CSV: Choosing the appropriate import method and selecting columns for analysis.
(01:56) Defining Your Analysis Goals: Understanding the purpose of your analysis and selecting relevant columns for graphing.
(02:56) Adding Filter Tags: Choosing columns to use as tags for filtering and exploring your data.
(03:47) Exploring the Network Knowledge Graph: Understanding the layout, nodes, connections, and clusters.
(04:43) Analyzing Key Themes and Topics: Using the text analytics panel to identify main ideas and underlying concepts.
(06:43) Uncovering Blind Spots: Revealing structural gaps and potential areas for further exploration.
(08:04) Importing Additional Data: Creating a second network graph based on a different column from the same CSV.
(08:40) Comparing Datasets: Using the "intersects with" function to analyze the relationships between two graphs.
(10:35) Building a Social Network Graph: Creating entities from rows and visualizing connections between individuals.
(14:53) Advanced Text Analysis Settings: Choosing how to build the knowledge graph and creating entities from cells.
(16:26) Exploring the Social Network Graph: Filtering by tags, identifying clusters, and uncovering potential connections.
(19:09) Conclusion: Recap of key points and the importance of defining your analysis goals before importing data.

Try it on https://infranodus.com

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