The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…
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Enovia
Score 7.0 out of 10
N/A
Dassault Systèmes S.A. is a French company and a world leader in the production of 3D design software, 3D digital mock-up and product lifecycle management (PLM) solutions.
DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.
Very well suited for direct integration with CAD packages (Solidworks/ Auto desk Inventor or AutoCAD) and version control of CAD Model/Assemblies and Drawing files) and creating parts and document objects directly into Enovia and controlling their lifecycle from CAD Interface. Similarly, Enovia's Engineering central is already equipped with Industry standard ECR/ECO process which needs little customization for implementing Engineering Change management process. The hardest part in Enovia is controlling the disposition of released material for the downstream process in other ERP systems. For example, if a released material has gone for production or purchasing in ERP system/MRP system then dispositioning that material with Major revision (which may need manufacturing to stop the production due to faulty design) have no direct control to stop the downstream activities. Most cases its manual process to communicate with ERP team to for taking action. Similarly, revision of Documents (material Spec for example) linked to thousands of parts required special process (some time needs to schedule in the weekend).
DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making.
Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives.
It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience.
The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now.
The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model.
The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice.
When a part/assembly has been released in Enovia and gone for production or downstream processing, Enovia doesn't have much control, hence, Enovia should come up with an easy controlling mechanism for various disposition of parts and seamless communication with an ERP or downstream process.
If a document is linked to thousands of materials then revising this document takes long time gets floated to the BOMs where the previous document versions are used. So, Enovia should have an efficient way to replace the floating process or another efficient mechanism for document revision processing.
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.
Easy learning curve for the users- Very user-friendly Interface for Engineering central make the users happy and easy to learn the BOM creation and Engineering change management process.
Time-saving - Seamless Creation and revision process of objects saves a huge amount of time compared to other systems.
Easy to copy existing business data and modify them as required.
