Abstract: The present disclosure relates a computer-implemented method comprising obtaining, at a database application, a selection of one or more database metadata items from a user device, wherein each metadata item includes human-intelligible content and each metadata item identifying an associated database object contained in a database, identifying, based at least partially on the database objects associated with the selected one or more metadata items, one or more predefined database views of the database application, registering the identified one or more predefined database views, monitoring if the one or more predefined database views are updated after the registering operation and triggering pushing of an update notification to the user device in response to a monitored update of the one or more predefined database views.

Abstract: The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.

Abstract: A computer-implemented method for generating a contextual panel interface with a first interactive display portion for depicting a plurality of selectable datasets associated with the query context, a second interactive display portion for depicting a plurality of selectable measures associated with the query context and with at least one of the plurality of selectable datasets, a third interactive display portion for depicting a plurality of selectable dimensions associated with the query context and with at least one of the plurality of selectable datasets, and an interactive tool display portion configured to determine a query context in response to receiving a search query and to populate the first, second, and third interactive display portions.

Abstract: The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.

Abstract: Techniques of providing visualization suggestions are disclosed. In some example embodiments, a current visualization of at least a portion of data of a dataset is determined to be displayed to a user in a graphical user interface of a device, a plurality of visualization candidates is generated based on an application of transition rules to the current visualization, a corresponding score for each one of the plurality of visualization candidates is generated based on a corresponding level of data variance for the data of the corresponding visualization candidate, a ranking of the plurality of visualization candidates is generated based on the scores, at least one of the plurality of visualization candidates is selected based on the ranking, and a plurality of selectable visualization suggestions corresponding to the selected visualization candidates is caused to be displayed to the user in the graphical user interface of the device.

Abstract: The disclosure generally describes computer-implemented methods, software, and systems, including a method for presenting information. A first graph is presented that represents plural groups, each representing an aggregated set of data points grouped based on a first set of common attributes. User input selecting a particular group is received. The aggregated set of data points is analyzed to determine whether the number of aggregated set of data points exceeds a threshold. In response to determining that the number exceeds the threshold, the aggregated set of data points is re-grouped. A second set of common attributes associated with the re-grouped set of data points is identified. The data points are aggregated based on the second set of common attributes. A second graph is provided for presentation, the updated graph representing plural groups, each group representing an aggregated subset of data points from the aggregated set of data points.

Abstract: A system and method for simplifying data access between tiers in a multi-tier system is disclosed. In an embodiment, a method is provided for receiving a request for service from a browser at a generic data access object (GDAO) layer; generating, by use of a data processor, a single, shared, generic data transfer object (GDTO) at the GDAO layer; calling through to a database tier, the database tier providing database metadata; and using the database metadata to include result data in the GDTO and return the GDTO in response to the request.

Abstract: The current subject matter describes displaying historical data associated with one or more data values within a business intelligence report. A graphical user interface executed by a computing device can receive, from a user, a request for display of historical data associated with a specified/selected data value in a business intelligence report. Subsequently, a representational state transfer engine (RESTful engine), which can be connected to a server system connected to the computing device, can execute a representational state transfer service (RESTful service) to fetch historical data from current and past instances associated with the data value. Then, the RESTful engine can write the fetched historical data to a file. The RESTful engine can generate or determine a uniform resource locator (URL) to the file, and can send the URL to the computing device. When the URL is selected by the user, the computing device can display the file.

Abstract: A mobile device user may quickly and naturally explore data received in a data grid from a remote database. A mobile device engine receives the database data including dimensions and measures, in a grid format comprising rows and columns of numerals. In response to a recognized suite of user gestures (e.g., horizontal swipe, vertical swipe, drag and drop), the engine may modify the data grid to provide a changed visualization, without the user device having to re-access a remote database server. In one example, a touch swipe down a column of the data grid may result in display of column data in vertical bar chart form, rather than exclusively as numerical values. Other user recognized gestures can include a user dragging and dropping one column into another, with horizontal bar visualizations combined into stacked bar charts that serve to rapidly apprise the user of a relative magnitude of column information.

Abstract: Methods, systems, and computer-readable storage media for exposing relationships between universe objects. In some implementations, actions include identifying a universe, the universe including objects at an abstracted layer, automatically processing the objects of the abstracted layer to provide one or more link groups, each link group including a plurality of objects that have some relation to one another, and outputting the one or more link groups.

Abstract: In an example embodiment, a bundle loader is run in response to a communication from an application. The communication may indicate that the plurality of bundles of components in the application is to be executed. The plurality of bundles may include at least one bundle having a component that depends on a dependency component in another of the plurality of bundles. A configuration file indicating a set of the plurality of bundles to load in the bundle loader is received. The bundle loader is operated to load a bundle manifest for each bundle in the set of the plurality of bundles to load. Then, for each of the bundles in the set of plurality of bundles to load, the bundle is activated if no unactivated dependency component exists for any component in the bundle.

Abstract: The present disclosure involves systems, software, and computer-implemented methods for merging object hierarchies. An example method includes identifying a first object hierarchy including one or more objects, each of the one or more objects representing a query associated with a data set; identifying a second object hierarchy including one or more objects; and generating a merged object hierarchy including the one or more objects from the first object hierarchy and the one or more objects from second object hierarchy, the merged hierarchy combining objects from the first and second object hierarchies that match and share a common parent object, and separately maintaining objects from the first and second object hierarchies that match and do not share a common parent object.

Abstract: A dataset and some user selected columns of the dataset are received by a statistical analysis module for analysis. The statistical analysis module generates a score for each unselected column of the dataset based on statistical analysis of the unselected columns and all or a subset of the selected columns. A ranking of the unselected columns is presented to the user for selection of one additional column of the dataset, after which the remaining unselected columns are re-ranked according to their associated scores and once again displayed to the user. The user may continue selecting from among the ranked columns until a threshold number of columns has been selected, at which point the user may deselect a selected column in order to continue selecting additional columns. A visualization suggestion application program interface then matches the selected columns with compatible visualization configurations and presents some of these visualizations to the user.

Abstract: A method and system for highlighting portions of a graph based on exception highlight rules is described. Highlight rules for a graph are received from a selection of a portion of an axis of the graph. Portions of the graph satisfying the highlight rules are identified. Visualization on the graph is generated to highlight the identified portions of the graph satisfying the highlight rules.

Abstract: The present disclosure describes methods, systems, and computer program products for dynamic generation and modification of input schemas. One computer-implemented method includes receiving event data from a data source with an event collector, the data source registered with the event collector to transmit event data to the event collector, transmitting the received event data for analysis, saving the transmitted event data, determining whether to create or update a business intelligence view, determining whether to create or update an input schema based on the saved event data, and providing, by a computer, an input schema describing how data is represented in the database to a query generation engine.

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 user may provide input to search an existing visualization (e.g., bar chart, graph) of a dataset returned in response to database querying. A highlighted visualization may then provide additional insight into relationships within the dataset. The highlighting may comprise changes to the appearance (e.g., size, color, background) of visualization elements. The search and highlighting may be executed by a functional module in an application layer of a local client in communication with database on a remote server. A search engine of the functional module may perform searching of dimension names, dimension values, and measure names within the dataset, identifying particular elements of the data set that are relevant to a search term (e.g., “q1”). Based upon recognition of relevant dataset data, a visualization engine may highlight particular elements of the visualization (e.g., changing an appearance of vertical bars showing first quarter revenue relative to vertical bars for other quarters).

Abstract: Example embodiments involve a system, computer-readable storage medium storing at least one program, and computer-implemented method for behaviorally consistent data wrangling. A local client device selects a set of raw sample data from a remote datastore. A local execution engine then applies one or more local data wrangling operations to the raw sample data. If the results of the local data wrangling operations are satisfactory, the local data wrangling operations may then be transferred to a remote data wrangling cluster. A remote execution engine being executed by the remote data wrangling cluster then applies the data wrangling operations to the larger set of raw data from which the sample raw data was obtained. As the remote execution engine and the local execution engine are of the same type, the data wrangling behavior exhibited by the local execution engine is reflected in the data wrangling behavior of the remote execution engine.

Abstract: Some examples of visualizing relationships in data sets can be implemented as a method by one or more computer systems. Dimension objects and multiple measure objects are displayed adjacent to a cause region and an effect region in a user interface. Each dimension object represents an input category associated with an input quantity that contributes to a total quantity in a data set. Each measure object represents an output category associated with an output quantity based on an input category. A dimension object and a measure object can be moved into the cause region and the effect region, respectively, in response to input. From the data set, an output quantity associated with the measure object is determined based on an input quantity associated with the dimension object from the total quantity in the data set. A result representing the output quantity is displayed in the measure object.

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.