Sap Se

Business Objects Software Limited

Fujitsu Corporation

Cisco Technology, Inc.

Min He

David Kung

Tao Zhang

Ashok Krishnaji Moghe

Aaron A Lung

Vei Ming Seah

Daniel Culp

Barbara Stortz

Ricardo Saito

Takao Naito

Paparao Palacharla

Xi Wang

Ying Liu

Qiong Zhang

Andrey Belyy

Wu Cao

Awez Syed

Nancy Yan

Puneet Jain

Claudia Lehmann

Phil Tinari

Freda Xu

Kevin Zhu

Suryanarayana Mangipudi

MonFor Yee

Chien Ming Yueh

Michael Alexander

Saranagati Chatterjee

Mengdan Ma

Srinivas Vobilisetti

Thomas Herdan

Frank Le

Hongfan Qian

Hiren Kotadia

Hemant Puranik

Khuan Tan

Abhiram Gujjewar

Jun Lu

Nikhil Patil

Systems and methods for just-in-time data quality assessment of best records created during data migration are disclosed. A data steward includes tools for creating and editing a best record creation strategy that defines how records from multiple systems will be integrated into target systems. At design time, the data steward can generate best record creation and validation rules based on the best record creation strategy. The data steward can apply the best record creation and validation rules to a sample of matched records from multiple data sources to generate a sample set of best records. The efficacy of the best record creation rules can be evaluated by assessing the number of fields in the sample set that fail the validation rules. During review, the validation rules can be applied to edits to the best records received from a human reviewer to ensure compliance with the best record creation strategy.

Just-in-time data quality assessment for best record creation

In an example, one or more processes that transform data originating in one or more of a plurality of different data sources are identified. Then, for each of the identified one or more processes, a relationship table is created, the relationship table listing objects input to the process, objects output from the process, and one or more mappings defining transformations performed on the objects input to the process to produce the objects output from the process. Dependencies are created between relationship tables by linking at least an instance of a first object input to a process in a first relationship table with at least an instance of the first object output from a process in a second relationship table. Lineage of an object in the computer system is traced by accessing one or more of the relationship tables and the dependencies.

Auto-discovery of data lineage in large computer systems

A method and system are presented of automatically suggesting rules for data stored in a table, with the table comprising a plurality of columns. The table is profiled to identify a content type for each of one or more of the plurality of columns. A rule knowledge base is accessed to locate rules specified for identified content types. Then, one or more of the located rules specified for identified content types are presented as suggestions. Acceptance of one or more of the suggested rules is received from a user, and the received validations are stored in the rule knowledge base. The accepted rules are applied to data for quality detection and monitoring. Embodiments are also described where columns are suggested based on a given rule.

System and method for automatically suggesting rules for data stored in a table

The present disclosure includes techniques pertaining to computer implemented systems and methods for data usage monitoring. In one embodiment, user manipulations of spreadsheets are translated into backend actions and executed against spreadsheet data. The actions of users on different spreadsheets automatically generate data records to track each action. The data records are stored in a data structure and portions of the records may be accessed to generate usage information.

Computer implemented systems and methods for data usage monitoring

The present disclosure includes techniques pertaining to computer implemented systems and methods for automatic generation of data transformations. In one embodiment, a user manipulates a spreadsheet of data in a user interface. On a backend, the user's manipulations trigger actions that cause the data to be modified. Actions may automatically cause data flow objects and data flow graphs to be produced. The transformations defined by the data flow graphs are automatically executed by a software engine and the results are displayed to the user. The user may access and manipulate data from a variety of data sources while the underlying complexities of the transformation process are performed in an automated manner.

Manipulating spreadsheet data using a data flow graph

Controlled startup of devices is based on dynamic statistical predictions. Timely startup of onboard associated vehicle devices is based on dynamic statistical predictions and driver proximity to the vehicle. An apparatus for timely startup includes an interface operatively coupled with a power consuming device and control logic coupled with the interface. The control logic is operable in a first mode to perform processing for determining a presence of a first condition of the vehicle, and to selectively activate the power consuming device of the vehicle, via the interface, responsive to determining the presence of the first condition. The control logic is operable in a second mode to suspend, via the interface, the processing for determining the presence of the first condition of the vehicle. The control logic selectively transitions between the first and second modes in accordance with a stochastic modeling of the presence of the first condition over time.

Startup control of devices

The present disclosure includes techniques pertaining to computer implemented systems and methods for transforming data. In one embodiment, data sources are specified by a user and copies of specified data are received in local storage. Data is presented to the user as a spreadsheet of columns and rows and the user manipulates the data in the spreadsheet. The user manipulations are automatically translated into data flow objects and a data flow graph, which is executed to transform the data. The modified data is presented to the user.

Presenting a selected table of data as a spreadsheet and transforming the data using a data flow graph

According to some embodiments, a method and an apparatus of enriching search results with metadata are provided to receive a plurality of metadata associated with an entity and storing the plurality of metadata in a repository. A search request associated with the entity is received and search results that comprise a portion of the plurality of metadata stored in the repository are determined.

Metadata search based on semantics

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.

In-memory data profiling

In an example embodiment, a method of automatically generating data validation rules from data stored in a column of a table is provided. Outliers for the data are determined by analyzing a profiling statistic for the data, the profiling statistic having a type. Then it is determined if a predefined limit is exceeded, based on a quantity of the outliers determined for the data through the analysis of the profiling statistic. A data validation rule is then automatically generated based on non-outliers detected in the data through the analysis of the profiling statistic, the generated data validation rule also being based on the type of the profiling statistic. The data validation rule can then be applied to data subsequently entered for the column, causing at least a portion of the data subsequently entered for the column to be rejected.

Automatic rule generation

According to particular embodiments, determining paths in a network with asymmetric switches includes receiving a graph representing the network. Each asymmetric switch has defined degree connectivity between one or more pairs of degrees of the asymmetric switch. The graph is transformed to yield a transformed graph that accounts for the asymmetric switches. A routing process is applied to the transformed graph to yield one or more paths through the network.

Determining paths in a network with asymmetric switches

Disclosed is a user interface on a display for editing data transformations comprising an ETL process. A first display area presents a data representation of a data transformation. A second display area presents a view of input data, and a third display are presents a view of output data. User input to modify the data transformation is received. In response to receiving the user input, the third display area is updated with output data generated by applying the modified data transformation to the input data.

Dataset previews for ETL transforms

A method, computer software program, and system provides automatic selection of time slots in time-division multiplexed connections. A network is mapped, and source and destination nodes are selected, as well as a route between them. Appropriate time slots are selected in a time-division multiplexed signal between the selected nodes, and a connection between the two nodes is automatically created, based at least in part on information related to the selected routes and time slots.

Generic SONET/SDH time slot selection algorithm

Growing community of inventors

San Jose, CA, United States of America

Min He