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Texera is a system to support collaborative data analytics as a cloud-based service using GUI-based workflows. It supports scalable computation with a parallel backend engine, and enables advanced AI/ML techniques. "Collaboration" a key focus, and we want to enable an experience similar to existing services such as Google Docs, but for data analytics.
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Many data analysts need to spend a significant amount of effort on low-level computation to do data manipulation and preparation, and want to use latest AI/ML techniques. These tasks are especially tough for non-IT community due to their lack of IT background.
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Many workflow-based analysis systems are not scalable. They are mostly software systems that run on a single machine and their architecture doesn't support huge amounts of data. Also, the existing systems support little or no interaction during the execution of the workflow. They face the long running time and lack of debugging tools, and need to re-run the program after making just some minor changes.
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Cloud-based services and technologies have emerged and advanced significantly in the past decade. Emerging browser-based techniques make it possible to develop powerful browser-based interfaces, which also benefit from high-speed networks.
- Provide data analytics as cloud services;
- Provide a browser-based GUI to form a workflow without writing code;
- Allow non-IT people to do data analytics;
- Support sharing for productive collaboration;
- Allow users to interact with the execution of a workflow by debugging;
- Support huge volumes of data efficiently.
The following is a workflow formulated using the Texera GUI in a Web browser. It consists of a workflow of basic operators, such as keyword search, sentiment analysis, and NLP.
Check this video to see Texera in action! (Texera was formally known as "TextDB" before August 28, 2017.)
- For users, visit Guide to Use Texera.
- For developers, visit Guide to Develop Texera.
- Eclipse:
- Lucene:
- Maven:
- Yourkit:
This project is supported by the National Science Foundation under the awards III 1745673, III 2107150, AWS Research Credits, and Google Cloud Platform Education Programs.