6 results about "Extract, transform, load" patented technology

The invention discloses a scientific research project management system based on big data processing, and relates to the technical field of project management. The data acquisition module comprises a plurality of key modules, the data acquisition module is connected with multiple sources, acquires project data greater than or equal to 10Hz, cleans the project data, transmits the cleaned project data to a storage center adopting a Hadoop distributed architecture through ETL (Extract Transform Load), and establishes an index and compresses and backs up Snappy according to multiple dimensions; the data analysis module performs clustering and mining association based on a Spark framework; the project progress monitoring module is used for capturing key nodes, displaying the key nodes by using a Gantt chart, and lagging 20% early warning pushing; the personnel management module records personnel information, intelligently recommends and evaluates performance; the fund management module tracks the fund and gives out a report early warning when the fund deviates from the budget by 15%; and the achievement management module collects and arranges achievements, mines and compares to promote transformation. According to the system, scientific research projects are comprehensively and intelligently managed, data are accurately collected and efficiently analyzed, the progress is monitored in real time, personnel funds are reasonably managed and controlled, achievement transformation is assisted, and scientific research benefits are improved.

Provided are systems, methods, and apparatuses for data analytics based on zero extract transform load (ETL). In one or more examples, the systems, devices, and methods include generating a data request for at least a subset of data stored in a database; converting the data request to an object storage request; determining, based on parsing the object storage request, that the object storage request includes an extract transform load (ETL) request; creating an ETL command based on the object storage request; routing the ETL command to a storage device based on the storage device comprising at least one ETL function requested in the data request; and determining information from result data that is received from the storage device in response to routing the ETL command to the storage device.

Provided are systems, methods, and apparatuses for data analytics based on zero extract transform load (ETL). In one or more examples, the systems, devices, and methods include generating a data request for at least a subset of data stored in a database; converting the data request to an object storage request; determining, based on parsing the object storage request, that the object storage request includes an extract transform load (ETL) request; creating an ETL command based on the object storage request; routing the ETL command to a storage device based on the storage device comprising at least one ETL function requested in the data request; and determining information from result data that is received from the storage device in response to routing the ETL command to the storage device.

Various embodiments described herein relate to systems and methods for processing data received from various data sources in a facility. In this regard, an input is received corresponding to at least one change in one or more assets. Configuration data associated with the one or more assets is updated based on the at least one change. Further, the updated configuration data is persisted at one or more data loaders. At least one Extract Transform Load (ETL) process is triggered corresponding to the updated configuration data to generate one or more aggregates associated with the one or more assets. As a result, Key Performance Indicator (KPI) metrics associated with the one or more assets is calculated.

Provided are systems, methods, and apparatuses for data analytics based on zero extract transform load (ETL). In one or more examples, the systems, devices, and methods include generating a data request for at least a subset of data stored in a database; converting the data request to an object storage request; determining, based on parsing the object storage request, that the object storage request includes an extract transform load (ETL) request; creating an ETL command based on the object storage request; routing the ETL command to a storage device based on the storage device comprising at least one ETL function requested in the data request; and determining information from result data that is received from the storage device in response to routing the ETL command to the storage device.

Provided are systems, methods, and apparatuses for data analytics based on zero extract transform load (ETL). In one or more examples, the systems, devices, and methods include generating a data request for at least a subset of data stored in a database; converting the data request to an object storage request; determining, based on parsing the object storage request, that the object storage request includes an extract transform load (ETL) request; creating an ETL command based on the object storage request; routing the ETL command to a storage device based on the storage device comprising at least one ETL function requested in the data request; and determining information from result data that is received from the storage device in response to routing the ETL command to the storage device.