Altair Monarch (formerly Datawatch Monarch, acquired by Altair in December, 2018) works with both relational and multi-structured data including support for a wide range of formats including PDF, XML, HTML, text, spool and ASCII files. The product can access data from invoices, sales reports, balance sheets, customer lists, inventory, logs and more. According to the vendor, the system is easy to use, allowing users to quickly select any data source and automatically convert it into…
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RapidMiner
Score 8.9 out of 10
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RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
Datawatch is very good value of money compared to QlikView; QlikView is really more of a BI tool and has a lot of functions that I didn't need. Datawatch is very strong in the real-time area where Tableau, Panorama, and Qlik don't do very well. If you need to set up a visual …
Datawatch Monarch has been the standard text editing solution for Supervalu for over 10 years. Because it works so well and was already a well-known fixture in our organization, the benefits of Data Pump were immediately recognized. We did not look for other software solutions, …
We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and …
For me, the best advantage to use RapidMiner is the ease of use to learn and deploy new processes. Yo don't need to code, you learn fast and it's really flexible when it comes to transforming data. Knime is also good, but not so flexible, and visually less attractive. Pentaho …
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual …
Used R and RapidMiner Studio. The main advantage for RapidMiner Studio is the reduced need to program. It has a much smaller learning curve, and it is easy to start using the tool and analyzing from day one.
We selected RapidMiner due to ease of use and a comfortable user interface. It stacks up very well against these tools in the predictive analytics space. For basic analytics and data reporting, we chose QlikView and Qlik Sense as a more robust reporting platform.
SPSS and SAS are too expensive. Their interfaces are excellent, but the price point is quite high making them inappropriate for higher education. KNIME is my second choice tool in this space, but it doesn't have the same long established english-speaking user community as …
The best part about RapidMiner is it mainly focus on machine learning algorithms whereas other tools focus on mainly the extract transform load (ETL) process. It can serve for all the KDD (Knowledge data discovery) process stages e.g. data cleaning, transformation, modeling and …
RapidMIner Studio is freely available and requires no programming skills. When compared with other free analytics tools, its graphical and analytical capabilities are far superior.
You simply cannot do everything with RapidMiner, it is just one tool in your arsenal. I like using Python directly much better with tools such as Jupyter Notebook in conjunction with JupyterHub.
The problem with R was that you had to code everything yourself and it doesn't do that well with large amounts of data. At the same time the advantage it provided was it has a large user base which means that you could get help easily.
* Individual seat licenses are very expensive, which is one reason we are moving to CMOD/RMS. But RMS has less functionality than standalone Monarch (now known as "Modeler"). I would like to know what improvements we can expect in RMS, I would also ask, what is the future of the standalone version? * In the past there has been a dearth of user discussion and support in the online community, although this seems to be improving with the new "Datawatch Commmunity" (http://community.datawatch.com).
RapidMiner is the best tool to build models on textual data. It is rich in ML algorithms and reduces the need to manually tune the parameters. It automatically optimizes them, thus providing a better solution. RapidMiner again extends great capability for data preparation, its insane connections to almost every data source pulls in the data easily into one environment. And it can comfortably perform data cleaning and process tasks over that. RapidMiner is not so good with image, audio or video data. These data points cannot be used directly in their raw form. They must be transformed into some intermediate form for performing analytics over it. Moreover, there are no connectors to directly pull data from their varied sources. For example, we don't have a connector to read audio data directly from a switch and then convert it to text (although Google speech API is available for audio to text conversion.)
Setting up visualizations with time series data requires a good understanding of how the software works. I would like it to be more intuitive. Having said that, time series data is inherently complicated and I don't see any obvious ways to make it simpler. But I'm not a software designer myself; they could put more resources into the user experience.
Their video training is really helpful and they have a big library of videos, but the videos get out of date as they come out with new versions. I can imagine that it's difficult to keep all the videos updated, but it would be great if the videos were always using the latest major version of the product.
They need more visualizations. They have a pretty big collection now but it seems like there is often some other way to present and visually analyze data that would be a better/tighter fit with requirements than the visualizations available in the standard product. I understand it is possible to add more visualizations - custom visualizations - but that's beyond my expertise.
Wish the tool was more efficient in terms of processing power. The tool takes a lot of CPU processing power, even for a small process on a small data set
Wish there were more options on charts and graphs to visualize the data
Datawatch recently repositioned Data Pump and essentially priced us out of the market. The initial investment was very inexpensive, but the yearly maintenance contract was viewed as being a little pricey. The only value of the contract was that it included software upgrades. The Professional Services portion of the contract that was meant to provide support was not viewed as being very effective or beneficial.
Datawatch is very good value of money compared to QlikView; QlikView is really more of a BI tool and has a lot of functions that I didn't need. Datawatch is very strong in the real-time area where Tableau, Panorama, and Qlik don't do very well. If you need to set up a visual monitoring dashboard, Datawatch is the best product I've seen for that. if you want to do a lot of in depth statistical analysis of large databases, Tableau is probably a good option.
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual workflow and therefore it is easier to demonstrate and visualise the processes involves in getting the desired results. Visualization of workflow enhances teaching and learning. RapidMiner is rich with algorithms and online learning materials that can assist students in their self-directed learning on data preparation, machine learning, deep learning, text mining, and predictive analytics. Moreover, RapidMiner repository has more than 1500 machine learning algorithms and functions that students can explore for any case study and assignments. The RapidMIner is also an open platform that can seamlessly integrates with other applications programmed with other programming languages like R and Python.