Conversational database analysis

1. A method for use in a low-latency database analysis system, the method comprising:

obtaining data expressing a usage intent with respect to the low-latency database analysis system, wherein the data expressing the usage intent includes a current request string expressed in a natural language, a current context associated with the current request string, and a previously generated context associated with a previously generated resolved-request;

identifying, from the current request string, a conversational phrase corresponding to a conversational phrase pattern from a defined set of conversational phrase patterns;

generating a resolved-request based on the identified conversational phrase;

including the resolved-request in the current context;

obtaining results data responsive to the resolved-request from a distributed in-memory database;

generating a response including the results data and the current context; and

outputting the response.

2. The method of claim 1 , wherein generating the resolved-request comprising:

in response to a determination that the conversational phrase is a data-request phrase, generating the resolved-request based on the data-request phrase, wherein generating the resolved-request omits using the previously generated context.

3. The method of claim 1 , wherein generating the resolved-request comprising:

in response to a determination that the conversational phrase is a request-transformation phrase, generating the resolved-request by modifying the previously generated resolved-request based on the request-transformation phrase.

4. The method of claim 3 , wherein the request-transformation phrase includes one or more of remove a column from the previously generated context, add a filter, remove a filter on a column, remove all filters, change a filter value, sort on a set of columns, sort columns in an ascending order, sort columns in a descending order, change date bucketing, limit to top N, exclude one or more value, drill down by an attribute, and drill down on a particular filter value by an attribute.

5. The method of claim 1 , wherein generating the resolved-request comprising:

in response to a determination that the conversational phrase is a serial-request phrase, generating the resolved-request based on the serial-request phrase such that the resolved-request identifies a result of the previously generated resolved-request as a data-source for the resolved-request.

6. The method of claim 5 , wherein generating the resolved-request comprising:

obtaining results data responsive to a previously generated resolved-request from a distributed in-memory database.

7. The method of claim 6 , wherein generating the resolved-request comprising:

locally storing, with respect to a relational search unit, the results data.

8. The method of claim 1 , wherein generating the resolved-request comprising:

in response to a determination that the conversational phrase is an autonomous-analysis phrase, generating the resolved-request such that the resolved-request indicates a request for autonomous-analysis based on the previously generated resolved-request.

9. The method of claim 8 , wherein the request for autonomous-analysis identifies one or more insights based on the previously generated resolved-request, where the one or more insights are data other than data expressly requested by a user.

10. The method of claim 1 , wherein generating the resolved-request comprising:

in response to a determination that the conversational phrase is an action phrase, generating the resolved-request includes identifying the previously generated resolved-request as the resolved request and generating an action-request corresponding to the action phrase, the action-request referring to the previously generated resolved-request.

11. The method of claim 10 , wherein the action phrase includes one or more of pinning the previously generated context, sharing the previously generated context, or changing a chart type of the previously generated context.

12. A system comprising:

a low-latency database; and

a processor, the processor configured to:

obtain data expressing a usage intent with respect to the low-latency database analysis system, wherein the data expressing the usage intent includes a current request string expressed in a natural language, a current context associated with the current request string, and a previously generated context associated with a previously generated resolved-request;

identify, from the current request string, a conversational phrase corresponding to a conversational phrase pattern from a defined set of conversational phrase patterns;

generate a resolved-request based on the identified conversational phrase;

include the resolved-request in the current context;

obtain results data responsive to the resolved-request from a distributed in-memory database;

generate a response including the results data and the current context; and

output the response.

13. The system of claim 12 , wherein the processor further configured to:

in response to a determination that the conversational phrase is a data-request phrase, generate the resolved-request based on the data-request phrase, wherein generating the resolved-request omits using the previously generated context.

14. The system of claim 12 , wherein the processor further configured to:

in response to a determination that the conversational phrase is a request-transformation phrase, generate the resolved-request by modifying the previously generated resolved-request based on the request-transformation phrase.

15. The system of claim 12 , wherein the processor further configured to:

in response to a determination that the conversational phrase is a serial-request phrase, generate the resolved-request based on the serial-request phrase such that the resolved-request identifies a result of the previously generated resolved-request as a data-source for the resolved-request.

16. The system of claim 12 , wherein the processor further configured to:

in response to a determination that the conversational phrase is an autonomous-analysis phrase, generate the resolved-request such that the resolved-request indicates a request for autonomous-analysis based on the previously generated resolved-request.

17. The system of claim 12 , wherein the processor further configured to:

in response to a determination that the conversational phrase is an action phrase, generate the resolved-request includes identifying the previously generated resolved-request as the resolved request and generating an action-request corresponding to the action phrase, the action-request referring to the previously generated resolved-request.

18. A non-transitory computer-readable storage medium, comprising processor-executable instructions for performing operations in a low-latency database analysis system, the operations performed in response to the instructions comprising:

obtaining data expressing a usage intent with respect to the low-latency database analysis system, wherein the data expressing the usage intent includes a current request string expressed in a natural language, a current context associated with the current request string, and a previously generated context associated with a previously generated resolved-request;

identifying, from the current request string, a conversational phrase corresponding to a conversational phrase pattern from a defined set of conversational phrase patterns;

generating a resolved-request based on the identified conversational phrase, wherein the generating a resolved-request based on the identified conversational phrase further comprising:

in response to a determination that the conversational phrase is a data-request phrase, generating the resolved-request based on the data-request phrase by omitting the previously generated context;

in response to a determination that the conversational phrase is a request-transformation phrase, generating the resolved-request by modifying the previously generated resolved-request based on the request-transformation phrase;

in response to a determination that the conversational phrase is a serial-request phrase, generating the resolved-request based on the serial-request phrase such that the resolved-request identifies a result of the previously generated resolved-request as a data-source for the resolved-request;

in response to a determination that the conversational phrase is an autonomous-analysis phrase, generating the resolved-request such that the resolved-request indicates a request for autonomous-analysis based on the previously generated resolved-request; and

in response to a determination that the conversational phrase is an action phrase, generating the resolved-request includes identifying the previously generated resolved-request as the resolved request and generating an action-request corresponding to the action phrase, the action-request referring to the previously generated resolved-request;

including the resolved-request in the current context;

obtaining results data responsive to the resolved-request from a distributed in-memory database;

generating a response including the results data and the current context; and

outputting the response.

19. The non-transitory computer-readable storage medium of claim 18 , wherein the request-transformation phrase includes one or more of remove a column from the previously generated context, add a filter, remove a filter on a column, remove all filters, change a filter value, sort on a set of columns, sort columns in an ascending order, sort columns in a descending order, change date bucketing, limit to top N, exclude one or more value, drill down by an attribute, and drill down on a particular filter value by an attribute.

20. The non-transitory computer-readable storage medium of claim 18 , wherein the action phrase includes one or more of pinning the previously generated context, sharing the previously generated context, or changing the chart types of the previously generated context.