Sap Se

Business Objects Software Limited

Alexander Ocher

Viktor Lapitski

Andrey Belyy

Sreenivasulu Gelle

Reinhard Sudmeier

Anil Samudrala

Richard Joe

Yanlun Ma

Maicon Trasel Loebens

Zoltan Hajnal

Manali Pise

Karoly Daxkobler

Wu Cao

Frank Buchholz

Werner Daehn

Ben Hofmans

A computer implemented method can obtain, in a data transfer system, a plurality of data records from data sources and monitor operating status of a target application running on a target machine. Responsive to finding that the target application stops operating, the method can send one or more first data records from the data transfer system to the target machine and store the first data records in a target buffer on the target machine. Responsive to finding that the target application resumes operating, the method can send one or more second data records from the data transfer system to the target machine and directly store the second data records in a data repository. While sending the one or more second data records, the method can transfer the one or more first data records from the target buffer to the one or more target databases.

Robust data transfer to cloud and on-premise storage systems

A database includes a blockchain infrastructure that allows data tables comprising the database to be associated with respective blockchains. Data inserted into a data table is replicated in its associated blockchain. Certain operations on a data table are disabled when it is associated with a blockchain.

Dual-stack architecture that integrates relational database with blockchain

Disclosed herein are system, method, and computer program product embodiments for managing data storage devices. In some embodiments, a server receives a request to store data in a first storage device. The server determines the storage space remaining in the first data storage device based on historical data associated with the first data storage device. The server further determines that the first data storage device will exceed its storage capacity based on a size of the data and the storage space remaining in the first data storage device. The server transfers a set of data stored in the first data storage device to a second storage device. Transferring the set of data causes the storage space remaining in the first storage device to be greater than or equal to the size of the data. The server stores the data in the first data storage device.

Transferring data to backup data repositories

Embodiments are described for a data processing tool configured to cease operations of a plurality of database readers when detecting a congestion condition in the data processing tool. In some embodiments, the data processing tool comprises a memory, one or more processors, and a plurality of database readers. The one or more processors, coupled to the memory and the plurality of database readers are configured to determine a congestion condition in at least one data pipeline of a plurality of data pipelines of the data processing tool. Each data pipeline of the plurality of data pipelines connects a database reader and a transformer of the data processing tool, a transformer and a database writer of the data processing tool, or two transformers of the data processing tool. The one or more processors are further configured to refrain from reading data from one or more databases responsive to the congestion condition.

Control mechanism of extract transfer and load (ETL) processes to improve memory usage

A computer implemented system and method of performing parallel load operations during an extract, transform, load (ETL) operation. The system generates a single transaction having multiple processes, where each process loads into one target table. The processes are executed in parallel, and the system performs verification on the single transaction.

Parallel load operations for ETL with unified post-processing

Technologies described herein can be used to generate and distribute neural network models and executable code using feedback data received from one or more client computing devices. A neural network model can be generated by a server computer. Executable code can also be generated by the server that, when executed by a client computing device, causes the client device to generate a prediction using the neural network model. The server can transmit the model and code to one or more client computing devices. The server can receive feedback data from the client device(s) based on predictions generated by the client device(s) using the neural network model and the executable code. The server can generate an updated version of the neural network model and/or an updated version of the executable code base on the feedback data, and can transmit the updated model and/or the updated code to the client device(s).

Neural network model generation and distribution with client feedback

Embodiments of the present disclosure pertain to accessing computing resources. In one embodiment, the present disclosure includes a computer implemented method comprising storing at least one credential for accessing a first system, storing a plurality of user credentials for a plurality of users having access to a second system, linking the plurality of user credentials for the plurality of users having access to the second system to the at least one credential for accessing the first system, receiving a first user credential for a first user from the second system over a first connection, authenticating the first user credential, wherein the first user credential is authenticated when the first user credential matches one of the stored plurality of user credentials, and establishing a second connection between the first system and the second system using the at least one credential when the first user credential is authenticated.

Systems and methods for authorizing access to computing resources

Embodiments of the present disclosure pertain to a personal assistant controller. In one embodiment, the present disclosure includes a computer implemented method comprising receiving a voice audio signal in the personal assistant controller, converting the voice audio signal into a target command corresponding to one of a plurality of personal assistants, wherein different personal assistants comprise different target command protocols for executing different operations on different network enabled appliances, and sending the target command for execution by a backend system corresponding to the one of the plurality of personal assistants, and in accordance therewith, performing an operation on the backend system.

Intelligent personal assistant controller where a voice command specifies a target appliance based on a confidence score without requiring uttering of a wake-word

Disclosed herein are system, method, and computer program product embodiments for a an ETL (extract-transform-load) system. An embodiment operates by receiving, at a processor, a message including a request to move data from a source database to a target database. The data is retrieved from the source database. One or more operations to perform on the data that convert the data from a source format associated with the source database to a target format associated with the target database are determined from the message. The one or more operations are executed on the data. The data is stored on the target database in the target format.

Dynamic execution of ETL jobs without metadata repository

Disclosed herein are system, method, and computer program product embodiments for a secured cloud storage system. An embodiment operates by receiving a compressed file comprising data that has been compressed using a compression algorithm. The compressed data is divided into a plurality of separate files. A password for each of the separate files is determined. Each of the separate files is encrypted with its corresponding password. The encrypted files are stored across a plurality of servers.

Secure cloud storage system

Disclosed herein are system, method, and computer program product embodiments for interfacing with and managing IoT devices. An embodiment operates by requesting a list of device-specific capabilities from one or more IoT devices, providing a user interface by which users can view all available capabilities across the one or more IoT devices, and receiving a selected capability which subsequently executes on the appropriate IoT device.

Internet of things device interface

According to some embodiments, a method and an apparatus of importing data using a database management system ('DBMS') with integrated Extract, Transform and Load ('ETL') functionality. The method comprises receiving a command to access data. The command is associated with an ETL function. An executable file associated with the ETL function is called and the data associated with the command is received.

Next generation architecture for database connectivity

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&#x2122;, UNIX) and support multiple computer languages (e.g. C++, Java&#xae;, Python&#xae;, .NET, etc.).

Growing community of inventors

San Jose, CA, United States of America

Alexander Ocher