Abstract: The disclosure generally describes computer-implemented methods, software, and systems for presenting error information. An indication is received of a selected error for a product installation. Installations are identified having a matching stream, build number and error. Other builds in a same stream having the same error are identified. Information is provided for displaying a graph having a horizontal line graph including first nodes representing builds in the same stream having the same error. Other occurrences of the error in builds of other streams are identified. Information for updating the graph is provided with parallel lines for each of the other streams, each parallel line including second nodes representing builds. An oldest one of the first nodes and second nodes is identified. Information is provided for presenting a list of potential changes occurring before the date associated with the oldest node and that are candidates for causing the error.

Abstract: Various embodiments of systems and methods for visual tracking of report changes are described herein. The used technique adds transitions between all steps of modification to a report document instead of static new pages. A classification module classifies the modifications and an identification module selects a visual effect to be used as transition state according to the classified modification.

Abstract: Various embodiments may operate to access individual lines of information included in a file stored in an electronic storage medium, to detect the existence of data clusters in the file based on neighboring cell content in a horizontal direction (corresponding to the individual lines), and in a vertical direction (orthogonal to the horizontal direction), to identify at least some of the data clusters as being associated with predefined table types (comprising vertical tables, horizontal tables, or cross tables), to merge some of the data clusters into section tables having common properties, and to transform the tables resulting from the merging activity, as well as remaining un-merged data clusters, into a single flat table. The stored file may comprise a spreadsheet file.

Abstract: Techniques for obtaining data from unstructured data for a structured data collection include receiving unstructured data that includes text; identifying an attribute associated with a structured data collection; obtaining at least one of historical data associated with the attribute or additional data associated with a user of the computing system; identifying one or more terms from the unstructured data as being associated with the attribute based on at least one of the historical data or the additional data; and storing the identified one or more terms in a data record of the unstructured data collection.

Abstract: Described herein is a technology for a dashboard used for visualizing data. In some implementations, a dashboard with one or more dashboard item is provided. Performance of the dashboard is evaluated to determine a load time of the dashboard. Possible suggestions for improving performance of the dashboard are provided if performance issues are determined from evaluating performance of the dashboard.

Abstract: Methods, systems, and computer-readable storage media for determining data structure and field types of a data source that is to be processed by an application. Actions include receiving the data source, providing base data associated with the data source, determining a number of fields of the data source and, for each field, a field type based on the data source and the base data, generating data structure data, the data structure data comprising the number of fields and field types, and providing the data structure data to the application.

Abstract: Described herein is a descriptive framework to facilitate data visualization. In accordance with one aspect of the framework, one or more module manifests are provided, wherein a module manifest describes a module that represents a particular component of a visualization. A chart manifest may be used to coordinate the one or more module manifests. A visualization may be rendered based on the chart manifest.

Abstract: Techniques for processing semi-structured data include receiving semi-structured data, a value of the semi-structured data being associated with a key; identifying a structured data collection, the structured data collection being associated with a category and having a plurality of attributes; obtaining at least one of historical data associated with the plurality of attributes or additional data associated with a user of the computing system; mapping the key to an attribute of the plurality of attributes based on at least one of the historical data or the additional data; and storing the value in a cell of a data record of the structured data collection, the cell being associated with the attribute that was mapped to the key.

Abstract: Systems and methods for resuming data transformations, such as broken or otherwise unsuccessful data transformations, are described. In some example embodiments, the systems and methods receive a message that indicates a broken data transformation of a data table between a source database and a destination database, identify a maximum and/or largest and greatest value for a date attribute contained within an index column for all rows of the data table that were successfully loaded to the destination database during the data transformation, and select a group of rows of data of the data table stored in the source database by querying the source database to identify rows that include a value for the date attribute that is greater than the identified value.

Abstract: A computer-implemented method of profiling a data set in a parallel processing environment includes vertically partitioning an initial data set. One or more attribute subsets are then profiled. A list of subjects is generated each corresponding to a specific attribute value identified in the profiling. Values of multiple attributes are extracted for each identified subject, and the sample results are assembled and merged.

Abstract: A system for a rapid deployment of software system includes a rapid deployment preparation module and a rapid deployment module. The rapid deployment preparation module archives a machine-independent portion of a software system preinstalled and preconfigured on a source machine. The rapid deployment module unpacks and installs the machine-independent portion of the software system on a target machine. The rapid deployment module then reconstructs a machine-dependent portion of the software system on the target machine using the target machine specific data.

Abstract: Systems and methods for matching data based on numeric difference are described herein. Input data elements are parsed to identify a first number and a second number. A difference between the first number and the second number is calculated based on a predefined formula. Based on the difference, a matching score between the input data elements is evaluated. The matching score is proportional to a base matching score corresponding to a threshold difference, and a maximum score corresponding to a match between the first number and the second number. A similarity between the input data elements is reported based on the evaluated matching score.

Abstract: Systems and methods are disclosed for analyzing application code changes. The method may include adding instrumentation code to a selected one or more of a plurality of software objects associated with an application, when a corresponding object class for the selected software objects matches at least one preferred object class. In response to at least one application-related event, detecting using the instrumentation code, one or more state changes of the selected software objects or one or more communications between at least two of the selected software objects. At least one baseline assertion may be generated using the instrumentation code based on the one or more state changes or communications. A notification may be generated upon detecting at least one subsequent assertion that does not match the at least one baseline assertion. A list with the at least one preferred object class may be accessed in a configuration file.

Abstract: A system and method for managing business intelligence data is described. In some example embodiments, the system extracts data and metadata from a business intelligence file, generates a data bundle of the data and metadata, generates an application bundle based on the data bundle, and generates an interactive document using the data bundle and application bundle.

Abstract: In an example embodiment, a method of performing data profiling in an in-memory database is provided. A command requesting a data attribute calculation on data in the in-memory database may be received. A precreated procedure stored in the in-memory database may then be used to perform the data attribute calculation on the data in the in-memory database The precreated procedure may be described in a computer language utilized by the in-memory database. Finally, a result of the performing of the data attribute calculation may be returned to the client computer.

Abstract: Techniques for disambiguating data using contextual and historical information include determining that data is potentially associated with two or more classifications of a plurality of classifications; obtaining contextual information associated with the data; obtaining historical information associated with a user of the computing system; and determining that the data is more likely associated with one classification of the two or more classifications than other classifications of the two or more classifications based on the contextual information and the historical information.

Abstract: In one embodiment, data records associated with attributes are received. A check is made to determine whether the data records are greater than a maximum data record limit of a graph. Further, when the maximum number of data records in the bin is less than or equal to the maximum data record limit of the graph, the data records are retrieved and presented in the graph. When the data records are greater than the maximum data record limit of the graph, the data records are grouped into bins based on initial bin sizes corresponding to the plurality of attributes. Furthermore, weighted densities of the bins are determined using a maximum number of data records associated with a bin and a maximum data record limit of the bin. Further, the graph is rendered to present the weighted densities of the bins using a randomization technique to analyze the data records.

Abstract: Embodiments include systems and methods for automated versioning of software on a client machine, allowing installation and updates over multiple platforms with modules written in different computer languages. In an embodiment, the client sends a list of installed modules to the server. This may be done by causing a client processor to perform method calls determining version information of the installed product. The server then checks the list and sends updates (if any) that are then automatically installed on the client. Some embodiments can perform software installation over-the-network, and prerequisite software may also be automatically installed on the client machine. The system may work on multiple platforms (e.g. Windows™, UNIX) and support multiple computer languages (e.g. C++, Java®, Python®, .NET, etc.).

Abstract: A method and system for visualization interaction design for cross-platform utilization is described. The system includes a unified user interface interaction module and a visualization module. The visualization module generates an interactive graph for data visualization. The unified user interface interaction module includes a unified user interface module configured to receive an operation on the interactive graph. The unified user interface module includes a pointer user interface module and a touchscreen user interlace module. The visualization module updates the interactive chart from the operation on the interactive graph with the corresponding user interlace module.

Abstract: A certificate of a user is presented by a client to a server. The certificate is used to authenticate communications between the client and the server. Thereafter, data from the certificate is cached at the server. The server then initiates one or more business intelligence processes of a business intelligence application at the client using the cached data to provide context to the one or more business intelligence processes. Related apparatus, systems, techniques and articles are also described.