Google Assistant vs. KNIME Analytics Platform

1. For quick timing and scheduling calls - As I can just say, ok google, I want to have a call with {teammate's name} today, can you find a. time of 30mins for me sometime this week?
2. Can you answer on the design pattern which Netflix uses for next video

Incentivized

KNIME Analytics Platform has vastly improved our effectiveness when working with large data sets. The self documenting GUI allows analysts to focus on what they are trying to accomplish, not complex code syntax. If we were to use traditional tools, like SQL, work would take much longer and it would be more difficult to collaborate both internally and with clients. Since KNIME Analytics Platform is database oriented, some spreadsheet functions are not supported, which is as it should be. For small data sets we often use Excel vlookup and pivot tables in place of KNIME Analytics Platform. If VBA code is requried, we go to KNIME Analytics Platform as we find VBA to be unstable in Excel.

• To-do lists and task boards so I can work on it better, and can ask quickly on what I need to do.
• Saves time and increases efficiency - I can ask and can answer relevant answers
• Set-up meetings - quickly scheduling and checking for time which suits all people

Incentivized

• Visual programming as oppose to scripting encourages data analysts to reap deeper insights from their data
• Large community contribution in extending the KNIME Analytics Platform into other areas of analytics, e.g. Text Analytics, Predictive Analytics, ML, etc.
• Open source with periodic updates ensures it is equipped to deal with the most sophisticated data analytics use case

• I think newer, complementary ideas are a bit sharper than Google Assistant especially in a Q&A environment or when seeking some depth to a subject. That enhancement is to be expected I feel. And Google Assistant is not so self limiting so I don't have a lot of improvement needs because I use this for what I've become accustomed to and for the ability overall.
• It is always important to do your best around hectic places, in bad tower signal areas or even if trying to do something new while using Google Assistant. Have patience in the setting. It pays off.

Incentivized

• Automation - e.g. RapidMiner Studio provides a Turbo Prep function, where one can get to working on models more quickly (RapidMiner is not open source though)
• KNIME does not replace a regular reporting tool - it is not meant to. However, if I have already spent some time developing a data acquisition and analytical model, it would be nice to be able to deploy, for example, a monitoring or reporting module that would process data autonomously and react accordingly.

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 feel this can be adjusted and after some trial and error you sort of start knowing what will work and how. And I have to say the overall impact becomes personal and we are all different. I'm small scale and as I've said, it works.

Incentivized

The training KNIME Analytics Platform provide helps you get to grips with a product that is already very intuitive. There is a KNIME Analytics Platform way of thinking about addressing problems, but once you understand a couple of patterns which you see again and again in your workflow it all makes sense.

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

This is where I would go next. And I think in functionality Google Gemini has a place. Especially so in this Newer AI driven world. I don't have any full force desire or usage on Google Gemini at the present. It is mostly what has been passed on to me in indirect ways.

Incentivized

There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business. Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.

Incentivized

• I'm about strategy and clarity in my projects and flexibility to change, enhance and correct. I get what I need in this via Google Assistant.
• When I need to get the word out or have a little extra done in real time I can easily use the feature via my voice commands while I'm doing something else simultaneously even in an environment where background noise and atmospheric clutter might be present. Clarity is pretty solid in my experience.
• I like to use as little as possible when it comes to Bluetooth, smart enhancements and such and having Google Assistant interact with my connected items is rather smooth as well.

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