From the course: Knowledge Graph Data Engineering for Generative AI Use Cases
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Options for data modeling - Neo4j Tutorial
From the course: Knowledge Graph Data Engineering for Generative AI Use Cases
Options for data modeling
- [Instructor] Data modeling does not necessarily require large, monolithic ETL tool sets. While I would not necessarily suggest using an Excel sheet, although no shade if you are using that, document mappings and transformations usually go well with tool sets that are specific to that kind of work. So let's explore some examples of tools that help with data modeling. Tools such as Informatica and Hadoop and Talend, those are all heavy-duty ETL tools. They're used for large multimodal and complex data transformation, but they're not necessarily graph-specific, although many use Apache Spark for ETL into graph structures, but those are usually property graphs. Other tools, like Redshift or Databricks, allow for on-the-fly modeling and analytics, whereas there are tools that are more specific to graph modeling, data transformation and data loading, like Stardog, Neo4j, or the open source Protege. Picking the right tool for the job means gathering the requirements of your ETL and data…
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