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Ni componentworks datagraph
Ni componentworks datagraph












  • The technical support offered by NI was invaluable when we ran into problems or had questions.
  • We could use DataFinder to perform a query to narrow down the data we wanted to analyze and then selectively load what data we wanted from one or more files for analysis in the DIAdem client. Sometimes our files contained over 200 channels, but we only wanted to analyze five of the channels.
  • Using DIAdem, we can interactively create analytics dashboards without programming.
  • DIAdem can read in and load over 1,000 file formats, which meant none of our current data acquisition processes had to change and should they change in the future, we do not have to worry about compatibility with our data analysis program.
  • DataFinder Server Edition is an off-the-shelf database solution to index metadata to which we can send queries to find specific test results.
  • In addition to meeting the criteria listed above, we chose the NI Technical Data Management Platform for the following reasons: Why We Chose a Solution Based on DIAdem and DataFinder Server EditionĪfter reviewing the results from the nine tools we benchmarked, we chose to build our solution off DIAdem software and now called SystemLink TDM DataFinder Module.

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  • Flexible platform-We wanted to integrate into existing data acquisition processes and potentially expand to other departments in the future.
  • Reporting templates-We wanted to produce consistent, reliable reports to aid decision making.
  • Parallel analysis run as a batch process-This would help us execute simultaneous processes on potentially thousands of files.
  • ni componentworks datagraph

    This also empowered the engineers to perform their own analysis instead of relying on a handful of analysis experts. Interactive tool to perform analysis-Our engineers did not want to learn another programming language, so our solution needed to feature interactive analysis.Manage metadata-This included combining metadata from multiple sources, adding metadata that was not originally saved to file, and being able to search files from their metadata.Ability to automate data uploads-To make it as easy as possible for the 400+ users of this solution, we needed to be able to upload any new data sets automatically whenever a computer was connected to a network and move those files to a centralized server.Some of the criteria used to evaluate these tools include: To address this Big Analog Data challenge, we created a dedicated team to benchmark nine tools to determine which platform would be the best for our application. This process led to us analyzing only 10 percent of the data we were collecting.īenchmarking Criteria to Find the Best Solution for Our Application Nothing was standardized, not even our metadata or channel names. We had multiple analysis tools, all of which required special scripting to implement algorithms.

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    We based our analysis routine off a manual process and by our estimate, took 20 times longer than with the automated process that we have since developed. We found that we often repeated tests because we could not find specific test results. With our investment in R&D, over 400 engineers in our powertrain calibration and controls department collect up to 500 GB of time-series data daily.Īs a department, we had difficulty managing the amount of data we collected. We invest more in research and development than any other manufacturing company in the UK, which has empowered our thousands of engineers to develop world-class innovations.

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    The Big Analog Data Problem at Jaguar Land RoverĪdvanced design, engineering, and technology have all played a part in the success of Jaguar Land Rover (JLR) over the years.












    Ni componentworks datagraph