INTERACTIVE USER INTERFACE FOR DYNAMICALLY UPDATING DATA AND DATA ANALYSIS AND QUERY PROCESSING

• US 20180039399A1
• Filed: 10/13/2017
• Published: 02/08/2018
• Est. Priority Date: 12/29/2014
• Status: Active Application

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Kaltegaertner, Helen, Antihi, Alexandru, Krieger, Brandon, Colgrove, Caitlin, Li, Diran, Javitt, Gabrielle, O'Connor, Gregory, Schafer, Mark, Elliot, Mark, Franco, Maria, Lynch, Matthew, Biswal, Punyashloka, Chen, Phillip, Kromwijk, Sander, Scott, Shannon, Yu, Stephanie, Burgin, Walker
• Application Number:
  US15/784,004
• Publication Number:
  US 20180039399A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 3/04817 using icons graphical or visual programming using iconic symbols G06F8/34
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials

Abstract

The systems and methods described herein provide highly dynamic and interactive data analysis user interfaces which enable data analysts to quickly and efficiently explore large volume data sources. The data analysis system enables the user to investigate large volumes of data over many different paths of analysis while maintaining detailed and retraceable steps taken by the user over the course of an investigation, as captured via the user'"'"'s queries and user interaction with the user interfaces provided by the data analysis system. Data analysis paths may involve exploration of high volume data sets, such as Internet proxy data, which may include trillions of rows of data. The data analyst may pursue a data analysis path that involves, among other things, applying filters, joining to other tables in a database, viewing interactive data visualizations, and so on. The data analysis system enables a user to refresh or insert a node in a workflow. The data analysis system further provides data editing, reporting, enrichment, expression language, and charting functionality.

Claims

1. A computer-implemented method comprising:

receiving, via a user interface, a request to update a first data node, wherein a first data analysis graph comprises the first data node and one or more additional nodes;

identifying an active path from the first data analysis graph;

generating duplicate one or more additional nodes from the one or more additional nodes and the active path;

generating an updated first data node;

generating a second data analysis graph comprising the updated first data node and the duplicate one or more additional nodes; and

causing presentation of the second data analysis graph in the user interface.

2. The computer-implemented method of claim 1, wherein the one or more additional nodes correspond to a user interface visualization and comprise at least one of:

a summary node, a table node, a histogram node, a distribution node, a time series node, a grid node, a heatmap node, a pivot table node, a filter node, a column editor node, an enrich node, a link node, a set math node, or an export node.

3. The computer-implemented method of claim 1, further comprising:

identifying, in the first data analysis graph, a parent node of the first data node; and

generating a link between the parent node and the updated first data node.

4. The computer-implemented method of claim 1, wherein the one or more additional nodes comprise at least two linked nodes according to a first order, the computer-implemented method further comprising:

generating a first link between the updated first data node and the duplicate one or more additional nodes; and

generating, according to the first order, a second link between the duplicate one or more additional nodes comprising at least two nodes.

5. The computer-implemented method of claim 1, wherein identifying the active path comprises:

accessing historical user interaction data associated with the first data analysis graph;

identifying, from the historical user interaction data, a current node from the first data analysis graph; and

identifying, as the active path, one or more nodes from the first data analysis graph based at least in part on a dependency of the current node.

6. A non-transitory computer storage medium storing computer executable instructions that when executed by a computer hardware processor perform operations comprising:

retrieving a first data analysis graph comprising a plurality of nodes;

identifying an active path from the first data analysis graph;

generating duplicate one or more additional nodes from the plurality of nodes and the active path;

identifying, from the duplicate one or more additional nodes and the plurality of nodes, an insertion point between a first data node and a second data node;

generating a third data node;

generating a second data analysis graph comprising the first data node, the third data node, and the second data node; and

causing presentation of the second data analysis graph in a user interface.

7. The non-transitory computer storage medium of claim 6, wherein the operations further comprise:

receiving a node insertion request comprising data corresponding to the insertion point;

generating a first link between the first data node and the third data node as indicated by the insertion point; and

generating a second link between the third data node and the second data node as indicated by the insertion point.

8. The non-transitory computer storage medium of claim 6, wherein the plurality of nodes comprises the first node and the duplicate one or additional nodes comprises the second node.

9. The non-transitory computer storage medium of claim 6, wherein identifying the active path comprises:

accessing historical user interaction data associated with the first data analysis graph;

identifying, from the historical user interaction data, a current node from the first data analysis graph; and

identifying, as the active path, one or more nodes from the first data analysis graph based at least in part on a dependency of the current node.

10. The non-transitory computer storage medium of claim 6, wherein the operations further comprise:

identifying a non-transformation node from the active path;

identifying, from the active path, subset of nodes that excludes the non-transformation node;

identifying an abridged data analysis graph as the subset of nodes; and

causing presentation of the abridged data analysis graph in a user interface.

11. The non-transitory computer storage medium of claim 10, wherein identifying the non-transformation node from the active path further comprises:

determining a node type from a node in the active path; and

determining that the node type corresponds to a non-transformation node type.

12. The non-transitory computer storage medium of claim 10, wherein presentation of the second data analysis graph comprises a workflow visualization.

13. A computer system comprising:

one or more computer processors configured to execute software code to;

retrieve a first data analysis graph comprising a first data node and one or more additional nodes;

identify an active path from the first data analysis graph;

generate duplicate one or more additional nodes from the one or more additional nodes and the active path;

generate an updated first data node;

generate a second data analysis graph comprising the updated first data node and the duplicate one or more additional nodes; and

cause presentation of the second data analysis graph in a user interface.

14. The computer system of claim 13, wherein the one or more computer processors are further configured to execute the software code to:

receive a request to update the first data node;

identify, in the first data analysis graph, a parent node of the first data node; and

generate a link between the parent node and the update first data node.

15. The computer system of claim 13, wherein the one or more additional nodes comprise at least two linked nodes according to a first order, and wherein the one or more computer processors are further configured to execute the software code to:

generate a first link between the updated first data node and the duplicate one or more additional nodes; and

generate, according to the first order, a second link between the duplicate one or more additional nodes comprising at least two nodes.

16. The computer system of claim 13, wherein identifying the active path comprises:

accessing historical user interaction data associated with the first data analysis graph;

identifying, from the historical user interaction data, a current node from the first data analysis graph; and

identifying, as the active path, one or more nodes from the first data analysis graph based at least in part on a dependency of the current node.

17. The computer system of claim 13, wherein the one or more computer processors are further configured to execute the software code to:

identify a non-transformation node from the active path;

identify, from the active path, subset of nodes that excludes the non-transformation node;

identify an abridged data analysis graph as the subset of nodes; and

cause presentation of the abridged data analysis graph in a user interface.

18. The computer system of claim 17, wherein identifying the non-transformation node from the active path further comprises:

determining a node type from a node in the active path; and

determining that the node type corresponds to a non-transformation node type.

19. The computer system of claim 13, wherein the one or more computer processors are further configured to execute the software code to:

join a first data set and a second data set to determine a third data set; and

store the third data set as a node in the second data analysis graph.

20. The computer system of claim 13, wherein the one or more computer processors are further configured to execute the software code to:

access a data set from a node in the second data analysis graph;

access report configuration data associated with the node; and

generate, in the user interface, a report comprising data from the data set based at least in part on the report configuration data.