Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) obtaining a predicted visualization definition based at least in part on abstracting the result data, and (v) generating a visualization for the result data based at least in part on the predicted visualization definition.

Abstract: A first dashboard is generated utilizing a machine learning model and user settings associated with a user. One or more follow-up prompts are received. Data needed to answer the one or more follow-up prompts is determined and obtained utilizing one or more data catalogs. One or more subsequent dashboards are generated utilizing the machine learning model and the user settings associated with the user.

Abstract: One or more data catalogs of a plurality of data catalogs that are relevant to a prompt are determined. The one or more determined data catalogs are utilized to locate one or more data files and applying one or more security policies to the one or more data files to determine one or more of the data files to which a user associated with the prompt is permitted to access. A query response is generated utilizing the one or more of the data files to which the user associated with the prompt is permitted to access.

Abstract: A first dashboard is generated utilizing a machine learning model and user settings associated with a user. One or more follow-up prompts are received. Data needed to answer the one or more follow-up prompts is determined and obtained utilizing one or more data catalogs. One or more subsequent dashboards are generated utilizing the machine learning model and the user settings associated with the user.

Abstract: A first dashboard is generated utilizing a machine learning model and user settings associated with a user. One or more follow-up prompts are received. Data needed to answer the one or more follow-up prompts is determined and obtained utilizing one or more data catalogs. One or more subsequent dashboards are generated utilizing the machine learning model and the user settings associated with the user.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) obtaining a predicted visualization definition based at least in part on abstracting the result data, and (v) generating a visualization for the result data based at least in part on the predicted visualization definition.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) obtaining a predicted visualization definition based at least in part on abstracting the result data, and (v) generating a visualization for the result data based at least in part on the predicted visualization definition.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) abstracting result data to obtain a data abstraction, the result data being responsive to the one or more data requests, and (v) generating a visualization for the result data based at least in part on the data abstraction.

Abstract: A system, method, and device for generating data visualizations are disclosed. The method includes (i) obtaining a natural language query, (ii) determining an intent for the natural language query, (iii) generating one or more data requests to one or more selected data sources, the one or more data requests being based at least in part on the intent, (iv) obtaining a predicted visualization definition based at least in part on abstracting the result data, and (v) generating a visualization for the result data based at least in part on the predicted visualization definition.

Abstract: Techniques for an Application Access Analyzer are disclosed. In some embodiments, a system/process/computer program product for an Application Access Analyzer includes monitoring access to an application over a network; automatically determining a root cause of an issue (e.g., an anomaly in network connectivity, performance degradation, and/or a permission denial and/or policy blocking) associated with the access to the application over the network for a user (e.g., or a group of users) using an application access analyzer; and performing an action in response to determining the root cause of the issue associated with the access to the application over the network.

Abstract: According to one embodiment, a method includes receiving, by a first edge device at a first site, a first site overlay control plane message including control plane information. The first edge device translates the first site overlay control plane message into a core overlay control plane message. The first edge device sends the core overlay control plane message over a core network to a second edge device at a second site.

Abstract: According to one embodiment, a method includes receiving, by a first edge device at a first site, a first site overlay control plane message including control plane information. The first edge device translates the first site overlay control plane message into a core overlay control plane message. The first edge device sends the core overlay control plane message over a core network to a second edge device at a second site.

Abstract: According to one embodiment, a method includes receiving, by a first edge device at a first site, a first site overlay control plane message including control plane information. The first edge device translates the first site overlay control plane message into a core overlay control plane message. The first edge device sends the core overlay control plane message over a core network to a second edge device at a second site.