Abstract: According to some embodiments, a business intelligence data store contains semantic layer information. A business intelligence language platform may receive a business intelligence language query expression from a user. The business intelligence language platform may then access the mapping information in the business intelligence model data store to compute an output type describing a result structure entity for the query expression. According to some embodiments, the output type may be used to automatically recommend at least one visualization chart to the user. Moreover, in some embodiments the output type is annotated with meta-data information about a business object.

Abstract: Techniques are described for performing a time series analysis using a clustering based symbolic representation. Implementations employ a clustering based symbolic representation applied to time series data. In some implementations, the time series data is discretized into subsequences with regular time intervals, and symbols encoding the time intervals may be derived by performing clustering algorithms on the subsequences. In the new representation, a time series is transformed into a sequence of categorical values. The symbolic representation is suitable to perform time series classification and forecast with higher accuracy and greater efficiency compared to previously used techniques. Through use of the symbolic representation, a dimension reduction is applied to transform the time sequences to a feature space with lower dimensions. As output of such transformation, a new representation is obtained based on the original time series.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improving recommendation to users in data intelligence systems. In one aspect, a method includes the actions of receiving a current observation describing an interaction of a user with a data intelligence system; identifying a current user interest based on the current observation, wherein past observations of the user with the data intelligence system are clustered to form user interests in a Markov model; using the Markov model and based on the current user interest, determining a next user interest from the user interests; extracting a one past observation from the determined next user interest based on a selection criterion and a threshold, wherein the selection criterion is based on how closely the at least one past observation matches the current observation; and sending a recommendation to the user based on the past observation.

Abstract: In some example embodiments, a graphical user interface (GUI) is caused to be displayed on a computing device of a user. The GUI can be configured to enable the user to submit an identification of a dataset and at least one configuration parameter. The identification of the data source, the at least one configuration parameter, and the at least one wrangling parameter can be received via the GUI on the computing device. A sampling algorithm can be configured based on the at least one configuration parameter. A sample of data from the dataset can be generated using the configured sampling algorithm. At least one data wrangling operation can be performed on the sample of data based on the at least one wrangling parameter.

Abstract: According to some embodiments, an abstraction engine may determine a data manipulation definition generated by a creator platform to accesses a database via a first connection protocol (e.g., ODBC). The abstraction engine may then automatically analyze the data manipulation definition to discover a connectivity parameter (e.g., a DSN, a DBMS type, a DBMS host name, a port, etc.) associated with the access to the database via the first connection protocol. The data manipulation definition may then be stored along with the connectivity parameter as a meta-connection into a metadata repository. A consuming platform may retrieve the meta-connection from the metadata repository translate the meta-connection into the database manipulation definition to accesses the database via a second connection protocol (e.g., JDBC).

Abstract: A raw dataset including measures and dimensions is processed, by a preprocessing module, using an algorithm that produces a preprocessed dataset such that at least one type of statistical analysis of the preprocessed dataset yields equal results to the same type of statistical analysis of the raw dataset. The preprocessed dataset is then analyzed by a statistical analysis module to identify subsets of the preprocessed dataset that include a non-random structure or pattern. The analysis of the preprocessed dataset includes the at least one type of statistical analysis that produces the same results for both the preprocessed and raw datasets. The identified subsets are then ranked by a statistical ranker based on the analysis of the preprocessed dataset and a subset is selected for visualization based on the rankings. A visualization module then generates a visualization of the selected identified subset that highlights a non-random structure of the selected subset.

Abstract: Techniques are described for identifying an input training dataset stored within an underlying data platform; and transmitting instructions to the data platform, the instructions being executable by the data platform to train a predictive model based on the input training dataset by delegating one or more data processing operations to a plurality of nodes across the data platform.

Abstract: A method for configuring an algorithm for processing data in a database may include generating a plurality of rules by converting a concrete syntax representation of one or more constraints associated with a parameter of the algorithm into an abstract syntax representation of the constraints. A first input value associated with the first parameter may be received from a client via a user interface at the client. The user interface may be updated based on the first input value. The user interface may be updated by applying a first rule from the plurality of rules. The update to the user interface may include a change to a visibility, a modifiability, and/or an allowed value of a second parameter of the algorithm. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A computer-implemented method for generating a plurality of data query suggestions is described. The method includes receiving a textual input in a user interface of a software application implementing a plurality of business processes and determining a query context for the textual input. The method also includes computing a plurality of ranked numerical scores based on the query context in which the ranked numerical scores are computed using information obtained from a plurality of usage metrics associated with the query context and determining, using the plurality of ranked numerical scores, a plurality of candidate data combinations. The method also includes ordering the plurality of candidate data combinations according to the plurality of ranked numerical scores and generating at least one data suggestion using the ordered plurality of candidate data combinations and providing the at least one data suggestion in the user interface.

Abstract: A state capture designation for an element of an application within an application design environment may be received, indicating that the application, once deployed, will include a state capture functionality for capturing a state of the element, and a state restoration function for restoring the state of the element. Following deployment of the application within a runtime environment, and in response to an invocation of the state capture functionality, a captured state of the element may be stored. A state restoration request for the captured state may be received by way of the state restoration functionality, and following a re-deployment of the application with an update to the element that was included as part of an update to the application within the application design environment. The captured state may then be restored to the updated element, in response to the state restoration request, and within the runtime environment.

Abstract: A computer-implemented method for disaggregating data in a spreadsheet or other data structure hosted on a client computing device includes providing an analyzer module as a plug-in or add-in to a spreadsheet application on a client computing device. The analyzer module locally performs disaggregation and aggregation processes on data in the spreadsheet on the client computing device. The method includes parsing, by the analyzer module, content entered in a subject cell of the spreadsheet to determine if sets of special syntax characters corresponding to a disaggregation instruction or command precede an amount in the entered content, and accordingly disaggregating or aggregating data in the spreadsheet.

Abstract: Software program “help” functionality includes features enhancing its relevance to users. An engine may receive/record context data arising from interactions between a user and the software program. The engine may process that context data to reference a plurality of sources (e.g., official help documentation, user blogs, partner web sites, etc.) and harvest relevant help information. Based upon stored context data and help information available from the plurality of sources, certain embodiments may generate suggested questions allowing further exploration of help issues. Some embodiments may offer help information in the form of an interactive “hotspot” focusing upon a specific UI element (e.g., icon). Processing the context data may allow the engine to assign a particular skill level (e.g., novice/intermediate/expert) to individual users, tailoring the help information to that skill level.

Abstract: Software program “help” functionality includes features enhancing its relevance to users. An engine may receive/record context data arising from interactions between a user and the software program. The engine may process that context data to reference a plurality of sources (e.g., official help documentation, user blogs, partner web sites, etc.) and harvest relevant help information. Based upon stored context data and help information available from the plurality of sources, certain embodiments may generate suggested questions allowing further exploration of help issues. Some embodiments may offer help information in the form of an interactive “hotspot” focusing upon a specific UI element (e.g., icon). Processing the context data may allow the engine to assign a particular skill level (e.g., novice/intermediate/expert) to individual users, tailoring the help information to that skill level.

Abstract: Embodiments visualize large data volumes utilizing initial sampling to reduce size of a dataset. This sampling may be random in nature. The sampled dataset may be refined (wrangled) by binning, grouping, cleansing, and/or other techniques to produce a wrangled sample dataset. A user defines useful end visualization(s) by inputting expected dimension/measures. From these visualizations of sampled data, minimal grouping sets are deduced for application to the full dataset. The user publishes/schedules the wrangled operation and grouping sets definition. Based on this, a wrangled dataset and grouping sets are produced in the big data layer. When the user accesses the visualization(s), minimal grouping sets are retrieved in the in-memory engine of the client and processed by an in-memory database engine according to the common processing plan. This produces result sets and a final set of visualizations of the full dataset, in which the user can recognize valuable data trends and/or relationships.

Abstract: Methods, systems, and computer program products for visually representing and displaying data are described. The visual representation may be a data animation. A data query may be submitted, a time measurement for processing the query may be obtained, and a sample size of the query may be adjusted based on the time measurement and a frame refresh rate of a data animation. A data animation may be generated based on one or more results of the query.

Abstract: A plurality of graphical elements may be represented as a document object model (DOM) having a plurality of nodes, each node representing a different graphical element, the DOM having an ordering of the nodes, each node having a z-value of front or back, indicating that the corresponding graphical element is to be displayed in a front layer for a z-value of front or a back layer for a z-value of back. The z-value of one or more of the plurality of nodes corresponding to one or more graphical elements to be moved to the front layer or back layer may be altered. The DOM can then be reordered so that the one or more graphical elements to be moved to the front layer or back layer are at the front or back of the DOM, while maintaining the ordering between nodes having z-values of front and the ordering between nodes having z-values of back.

Abstract: Provided are a system and method for semantic generation and enrichment. In one example, the method includes displaying a plurality of tiles on a user interface, each displayed tile visually representing a data entity obtained from a data file, detecting, via the user interface, a selection of a first displayed tile visually representing a first data entity and a second displayed tile visually representing a second data entity, and in response to detecting the selection via the user interface, generating a new data entity based on the first data entity visually represented by the first displayed tile and the second data entity visually represented by the second tile, and displaying a new tile visually representing the newly generated data entity. Accordingly, an end user can provide semantic creation and enrichment to visually displayed data without the need for an administrator.

Abstract: In some example embodiments, a graphical user interface (GUI) is caused to be displayed on a computing device of a user. The GUI can be configured to enable the user to submit an identification of a dataset and at least one configuration parameter. The identification of the data source and the at least one configuration parameter can be received via the GUI on the computing device. A sampling algorithm can be configured based on the at least one configuration parameter. A sample of data from the dataset can be generated using the configured sampling algorithm. The time parameter can limit an execution time of the generating of the sample of data to within a maximum amount of time indicated by the user.

Abstract: A computer-implemented method for initiating, at a user interface, execution of a software application implementing a plurality of business processes associated with a plurality of business objects, and displaying, in the user interface, a query box and a plurality of visualizations depicting data corresponding to at least a portion of the plurality of business objects. The method includes receiving and parsing a free text input, generating and executing a search using a plurality of keyword search queries based on one or more keyword tokens. The method also includes applying grammar rules, generating query trees, and generating a number of search suggestions using the query trees.

Abstract: The disclosure generally describes methods, software, and systems, including a method for using and managing ephemeral tables. User inputs associated with a database management system are received from an application. The user inputs are associated with a particular user and a particular application. From an auto-save cache index, one or more ephemeral tables are identified that are associated with the user inputs. The ephemeral tables are mapped to one or more tables in the database management system. Using the user inputs and the auto-save cache index, the one or more ephemeral tables are updated. Information associated with the user inputs is automatically stored on a temporal basis. The information survives database sessions, transaction boundaries, and database management system restarts.