How to Use the Network Graph?
- Arda Ülgü (Unlicensed)
You always see GEODI with the motto Search-Discover-Classify-Mask. Data discovery is often discussed in relation to regulations such as KVKK or PCI/DSS. GEODI offers much more than just the data discovery required for these regulations. Here, we will delve a little deeper into its discovery capabilities.
GEODI is an expert in uncovering hidden value in data and does so in many different ways. Discovery itself is a benefit. This allows us to better understand data leakage risks, comprehend the data we need to protect, and ultimately be more secure.
The network graph is a tool that goes a step further and shows us deeper relationships. It reveals a story that we cannot discern just by looking at lists or documents. In this article, we will discuss how to use the network graph.
It will be useful for lawyers, press advisors, independent auditors, inspectors, experts, managers, or anyone involved in digital forensics. The tools are easy to use, and the results are effective.
What is a Network Graph?
In the image, there is an example of a network graph. A network graph consists of nodes and lines connecting those nodes. You can think of it like a road network.
In the GEODI network graph, the nodes represent words (i.e., the discoveries made) or documents, and the lines represent the relationships between them.
The network graph is part of the GEODI Discovery package.
A Few Things to Know Before Starting
Network graph analysis is a complex process. Considering that GEODI performs data discovery at terabyte and petabyte levels, we cannot expect to visualize all relationships in a single graph. There are two reasons for this: first, it would not produce an understandable visual; second, performance constraints. The performance you experience with GEODI applies to the network graph as well, but within physical limitations.
Therefore, to obtain meaningful results from the network graph, you should always narrow down the data.
GEODI makes adjustments to make the visual more meaningful. You can stop it at any time or restart by changing the query.
The network graph loads the data at 1 or 2 levels; you can load other levels as described in the navigation.
It may occasionally strain your computer, so please allow it some time.
Navigation
In the network graph, similar to a map, you can zoom in and out using the mouse wheel. You can enlarge the area you are interested in.
By right-clicking on any node, you can access the documents and properties.
To load one more level in the network graph, you can use the expand function.
Document-Word Relationships
It answers the question "What is discovered in a document?"
Documents are at the center, with each name, date, place, credit card linked with lines within the document. If the same name appears in another document, it is linked to the same node. This way, you can track relationships between documents.
You can limit discovery results in the facet area, leaving only names and "credit cards."
You can perform deeper analyses using proximity operators as described in the article at Relationship Discovery .
Word-Document Relationships
It is the reverse of Document-Word analysis. There is a name at the center, with connections to documents where the name appears.
Word-Word Relationships
In Word-Word analysis, documents are not directly involved but are indirectly linked. Words appearing in the same document are connected to each other. This linkage varies as described in the article at Relationship Discovery.