Abstract: A device configured to perform data analytics comprising a memory and a processor may be configured to perform the techniques described in this disclosure. The memory may store multi-dimensional data. The processor may receive a sequence of inputs defining a recipe for analyzing the multi-dimensional data according to a language sub-surface specifying a natural language containment hierarchy defining a grammar for a natural language as a hierarchical arrangement of a plurality of language sub-surfaces. The processor may also receive data indicative of a summarized narration of the recipe and parameterize a field of the summarized narration to insert a user adjustable parameter that enables manipulation of the underlying recipe and obtain a parameterized summary that includes the user adjustable parameter. The processor may next present, via a first user interface, the parameterized summary.

Abstract: A device configured to perform data analytics comprising a memory and a processor may be configured to perform the techniques described in this disclosure. The memory may store multi-dimensional data. The processor may present, via a user interface, a graphical representation of a format for visually representing the multi-dimensional data. The processor may also receive, via the user interface, a selection of an aspect of one or more aspects of the graphical representation of the format. The processor may further receive, via the user interface and for the aspect of the one or more aspects of the graphical representation of the format for visually representing the multi-dimensional data, an indication of a dimension of the multi-dimensional data, and associate the dimension to the aspect to generate a visual representation of the multi-dimensional data. The processor may then present, via the user interface, the visual representation of the multi-dimensional data.

Abstract: A device comprising a processor and a memory may be configured to perform various aspects of the techniques described in this disclosure. The processor may present, via a first portion of a user interface, an interactive text box in which a user may enter the data indicative of the current input, present, via a second portion of the user interface, an interactive log of previous inputs entered prior the current input, and present, via a third portion of the user interface, a graphical representation of result data obtained responsive to the data indicative of the current input. The second portion of the user interface and the third portion of the user interface may be separately scrollable but coupled such that interactions in either the second portion of the user interface or the third portion of the user interface synchronize the second portion of the user interface and the third portion of the user interface. The memory may store the data indicative of the current input.

Abstract: In general, techniques are described for various aspects of accessing datasets. A device comprising a memory configured to store the multi-dimensional dataset; a processor may perform the techniques. The processor may apply a plurality of machine learning models to the multi-dimensional dataset to obtain a result output by each of the plurality of machine learning models. The processor may next determine a correlation of one or more dimensions of the multi-dimensional dataset to the results output by each of the machine learning models, and select, based on the correlation determined between the dimensions and the result output by each of the machine learning models, a subset of the plurality of machine learning models to obtain the result for each of the subset of the machine learning models. The processor may then output the result for each of the subset of the plurality of machine learning models.

Abstract: In general, techniques are described for various aspects of accessing datasets. A device comprising a memory configured to store the dataset, and a processor may be configured to perform the techniques. The processor may expose a language sub-surface specifying a natural language containment hierarchy defining a grammar for a natural language as a hierarchical arrangement of a plurality of language sub-surfaces. The processor may receive a query to access the dataset, the query conforming to a portion of the natural language provided by the exposed language sub-surface. The processor may transform the query into one or more statements that conform to a formal syntax associated with the dataset, access, based on the one or more statements, the dataset to obtain a query result, and output the query result.

Abstract: Domain specific programming is facilitated through the use of a conversational interface using natural language commands from the user and natural language cues to the user. The natural language conversation provides the actual program and thus can be saved and edited for future use.