12 September 2018


10 reasons why you need to upgrade to RapidMiner 9 today!

There have been some major advancements to the RapidMiner platform since this article was originally published. We’re on a mission to make machine learning more accessible to anyone. For more details, check out our latest release.

RapidMiner regularly releases new versions of RapidMiner Studio and RapidMiner Server (now RapidMiner AI Hub). Here are my top 10 reasons why you should upgrade to RapidMiner 9, the latest version, and take advantage of new features as well as other improvements and enhancements.

1. Turbo Prep

Turbo Prep is an incredibly exciting and useful new capability, radically simplifying and accelerating the time-consuming data preparation task. Easily blend and join data from a variety of sources like relational databases, NoSQL, APIs, spreadsheets, applications, social media, and more.

Once you have the relevant data, use Turbo Prep to quickly extract, join, filter, group, pivot, transform and cleanse your data. The creation of repeatable data prep steps means less time spent on repeating processes. You can also save your data as Excel or CSV or send it to data visualization products like Qlik.

 2. Auto Model

RapidMiner Auto Model accelerates the entire data science lifecycle using automated machine learning. It speeds feature selection by analyzing data to identify common quality problems. It automates predictive modeling by suggesting the best machine learning techniques and then generating optimized, cross-validated predictive models.

Auto Model highlights which features have the greatest impact on the desired business objective, highlighting the most important influence factors and correlations. Built in visualizations and an interactive model simulator let data scientists quickly explore the model to see how it performs under a variety of conditions.

3. Real-time scoring

Predict at scale, with very low latency, and deliver actionable intelligence in real-time to the decision maker or machine. This back-end capability is designed for demanding use cases requiring very fast scoring, like predicting how your customers behave, when your industrial parts will break, or calculating the risks associated with an action or a client. Enable real-time online scoring from web portals, phone apps, or desktop applications.

4. Faster

Parallelization of operators with Loop and Optimize Parameters, FP Growth, Join and other built-in operators makes it lightning fast to work with complex data imports and perform feature engineering steps with a few clicks. These operators were the first one to migrate to Studio’s new data core. Overall, the results are remarkable, depending on your data, FP-Growth improved by a factor of 5.

5. Highly scalable, distributed architecture for RapidMiner AI Hub

The new architecture (introduced in v8.0) provides a way scale indefinitely and let the RapidMiner environment grow with your needs, as well as structure jobs and executions with queues that can adapt to your organization. Know that you’re doing everything to be in control, reduce risk, and grow, as your business needs evolve.

6. Many more advanced ML capabilities and algorithms

We have added numerous extensions to our extensions library and expanded out data science capabilities to cover more use cases than ever. Learn more about our extensive and ever-expanding extensions library, adding new functionality to RapidMiner products, like text mining, Deep Learning, or integration with R, Python, Weka and more.

7. Global Search

Finding exactly what you need inside RapidMiner Studio can be difficult sometimes, especially when using a lot of extensions or functions that require more than one click. Searching for a specific process in your repositories or that specific panel you once saw might also take some time.

The Global Search in RapidMiner Studio will help you with all that- you can now search in your repositories, marketplace and all available operators in one place.

8. More data connectors and integrations

MapR, Informatica, Microsoft HDInsight, AWS, Google cloud connector (Splunk, Hive connectors as extensions). Easily connect to your data, no matter where it lives, with out-of-the box connectors to many 3rd party applications, social media sources, data bases and more.

9. More stable

We are always pushing to improving the overall stability of the platform by constantly fixing bugs and adding speed and power to our operator toolbox. During the past releases, we focused heavily on reducing unhandled exceptions and improving error messaging (easier to solve errors). Moreover, we have expanded the coverage and visibility of Studio’s powerful ‘Quick fix’ feature, which provides you a solution for the most common errors.

10. RapidMiner Radoop expands on big data use cases

New operators for Anomaly detection, Windowing, Discretization. These operators enable you to identify fraud, detect abnormal consumer or machine behavior in your data on Hadoop, reduce overfitting of machine learning models and improve their predictive performance, time series forecasting and more.

Also, the new intuitive UI for configuring the settings and variables of your Hadoop cluster makes it easier to change or tweak anything, helping users and administrators to refine the connections and test each section independently.

As we mentioned above, there have been several major advancements to the RapidMiner platform since this post was originally published. Be sure to check out our latest release.

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