ARIS vs. KNIME Analytics Platform

Well suited for enterprise architecture modeling where the intent to document elements beyond processes as well, such as risks and controls, KPIs, systems, org charts, etc. It also has the excellent capability of creating custom reports, hence if looking for various views right from summary to detailed, this is a great tool. It is less appropriate for implementing the processes as it is not very strong in BPMN.

KNIME Analytics Platform is excellent for people who are finding Excel frustrating, this can be due to errors creeping in due to manual changes or simply that there are too many calculations which causes the system to slow down and crash. This is especially true for regular reporting where a KNIME Analytics Platform workflow can pull in the most recent data, process it and provide the necessary output in one click. I find KNIME Analytics Platform especially useful when talking with audiences who are intimidated by code. KNIME Analytics Platform allows us to discuss exactly how data is processed and an analysis takes place at an abstracted level where non-technical users are happy to think and communicate which is often essential when they are subject matter experts whom you need for guidance. For experienced programmers KNIME Analytics Platform is a double-edged sword. Often programmers wish to write their own code because they are more efficient working that way and are constrained by having to think and implement work in nodes. However, those constraints forcing development in a "KNIME way" are useful when working in teams and for maintenance compared to some programmers' idiosyncratic styles.

Incentivized

• Query feature is excellent to extract information in a specific manner.
• Ability to create custom reports.
• Collaboration feature is very good.
• Semantic checks to check validation errors.
• cloud based central repository.

Incentivized

• Summarize instrument level financial data with relevant statistics
• Map transactions from core extracts to groups of like transactions using rule engines
• Machine learning using random forests and other techniques to analyze data and identify correlations for use in predictive models
• Fill out sampling data from averages.

• Defining databases, use of entities and relationship diagrams, define data, like data models, there is still a part they could improve.
• Providing more standard reports and improving on access rights and privileges functionality

Incentivized

• It does not have proper visualization.
• Some other BI tools (QlikView) have much easier functions for data interaction.
• Some other BI tools (Tableau) can be set up much faster.
• It is not an easy tool to use for non-tech savvy staff.

Incentivized

We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end

I am a BPM and Enterprise Architect Consultant and hence have been using different BPM and EA tools for consulting practice. Until now I have used Opentext Provision EA,Sparx EA, MS Visio and IBM Blueworks. All of the tools used are good and have their own unique features and capabilities. ARIS BPA is widely used by my current organization for different projects.

Incentivized

KNIME Analytics Platform offers a great tradeoff between intuitiveness and simplicity of the user interface and almost limitless flexibility. There are tools that are even easier to adopt by someone new to analytics, but none that would provide the scalability of KNIME when the user skills and application complexity grows

Incentivized

It has good, even complex functionality that is provided by its library and ability to create relations between items, yet it is not hard to use. Anyone can use it in a short time. It provides reporting abilities and good documentation with the availability of exporting options. The only drawback I have seen was user management/login issues.

Incentivized

KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.

Incentivized

KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.

Incentivized

The Service area, they have been very useful. ARIS suite is covering number of applications. ARIS engine is very powerful and robust. The tool can be configured in many ways which can be beneficial but can be a curse at the same time. As a user, you need to apply this flexibility with care.

Incentivized

Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of Alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what Alteryx can do along with how much ease it can do. Having said that, the 90% functionality and UI at no cost would be enough for me to quit using Alteryx and move towards [KNIME Analytics].

Incentivized

• Documentation of processes made it possible for anyone to see who does what, how and using what systems.
• Dependency on specific people is eliminated.

Incentivized

• It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
• Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.

Incentivized