KNIME Analytics Platform

KNIME Analytics Platform

von KNIME.COM

Was ist KNIME Analytics Platform?

Mathematische und statistische Funktionen, Workflow-Steuerung, erweiterte Prognose, maschinelle Lernalgorithmen und weitere Funktionen für Datenwissenschaftler.

KNIME Analytics Platform – Details

KNIME.COM

http://www.knime.org

KNIME Analytics Platform – Kostenübersicht

KNIME Analytics Platform bietet keine Gratisversion und keine kostenlose Testversion.

52642

Kostenlose Version

Nein

Gratis Testen

Nein

Einsatz

Cloud, SaaS, Web

Training

Persönlich

Kundenbetreuung

Support während der Geschäftszeiten

KNIME Analytics Platform Funktionen

Predictive Analytics Software
AI / Maschinelles Lernen
Benchmarking
Data Mining
Daten-Vermischung
Empfindungsanalyse
Für die Bildung
Modellierung & Simulation
Nachfragevorhersage
für das Gesundheitswesen

KNIME Analytics Platform – Nutzerbewertungen

Zeigt 5 von 11 Nutzerbewertungen

Gesamt
4,5/5
Benutzerfreundlichkeit
4,4/5
Kundenservice
4/5
Funktionen
4,5/5
Preis-Leistungs-Verhältnis
4,6/5
Yashoda W.
Bsc. Engineering Undergraduate
Programmentwicklung, Selbstständig
Verwendete die Software für: 6-12 Monate
  • Gesamtbewertung
    5/5
  • Benutzerfreundlichkeit
    5/5
  • Eigenschaften & Funktionalitäten
    5/5
  • Kundenbetreuung
    5/5
  • Preis-Leistungs-Verhältnis
    5/5
  • Wahrscheinlichkeit der Weiterempfehlung
    10/10
  • Quelle des Nutzers 
  • Bewertet am 4.8.2019

"A Suitable software for Engineering Undergraduates "

Kommentare: This is a good software which helps to solve statistical ptoblems,mathematical problems and also algorithm problems.so in Engineering there have lots of problems belongs to aforesaid kind of problems.so this can be useful for pre- Engineers.

Vorteile: This software gives most accurate answers and it has more sensitivity & most of values have precision.

Nachteile: sometimes error messages displaying while works are in progress

  • Quelle des Nutzers 
  • Bewertet am 4.8.2019
Meliksah T.
Data Scientist
Unterhaltungselektronik, 5.001-10.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    5/5
  • Eigenschaften & Funktionalitäten
    4/5
  • Kundenbetreuung
    4/5
  • Preis-Leistungs-Verhältnis
    4/5
  • Wahrscheinlichkeit der Weiterempfehlung
    8/10
  • Quelle des Nutzers 
  • Bewertet am 1.7.2019

"KNIME is very easy to learn and use for anybody"

Kommentare: KNIME is a very good Data Analytics software overall. If the team can handle the slowness issue, it's great for both computer science associates and other employees.

Vorteile: There are multiple features that is great about KNIME.
- It has a visual UI that does not require programming knowledge, where you connect nodes by drag and dropping but still do not lose the flexibility of programming languages because it has Python, R and JavaScript nodes too where you can write your own code.
- Since it's a visual UI that you work on, it's possible to track down what's going on, similar to an ETL tool. That's something that does not exist on programming.
- Community continuously develops Nodes so its like an organism that grows.

Nachteile: Its upsides come with downsides:
- Since it's high level (so to speak in CS manner) software. It is far from computer language, and that makes it very slow. It gets even slower more nodes and extensions are installed which was again, an upside.
- Nodes have customization and parameter management but they are not as customizable as Python/R libraries, though for that Python/R node can be used.

  • Quelle des Nutzers 
  • Bewertet am 1.7.2019
Verifizierter Rezensent
Chief Information Officer
Gesundheit, Wellness & Fitness, 5.001-10.000 Mitarbeiter
Verwendete die Software für: 6-12 Monate
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    3/5
  • Eigenschaften & Funktionalitäten
    4/5
  • Kundenbetreuung
    2/5
  • Preis-Leistungs-Verhältnis
    5/5
  • Wahrscheinlichkeit der Weiterempfehlung
    6/10
  • Quelle des Nutzers 
  • Bewertet am 1.5.2020

"Solid Platform for Small Datasets and Broad Data Connectivity"

Kommentare: The two main reasons we used KNIME were to process and prep data, then to conduct machine learning by training models and processing predictions. KNIME is great with data prep and blend as long as the data set is small to medium in size (< 4GB). There were areas where we struggled and that was when models were more complex (> 50 variables) and being able to deploy and schedule jobs. We had to download JDBC drivers for our database connections, which was not something we had to do with other platforms.

Vorteile: There is a wide range of tools to process and prep data in the platform natively and additional tools that can be download within the platform. The ability to customize the settings for most of the tools allows the user to adjust the output. Even more technical settings, like hyperparameter tuning, can be done in the tool UI. There are numerous input and output options and types.

Nachteile: Pulling in very basic files, like Excel spreadsheets can be a bit challenging where other platforms handle files with ease. Also, database connections are not seamless. The Java memory errors also limit the size of data that can be processed without making manual adjustments to settings. Lastly, not being a cloud-based platform, processing big data is very time-consuming.

  • Quelle des Nutzers 
  • Bewertet am 1.5.2020
Ferhat D.
Data Warehouse Developer
Informationstechnologie & -dienste, 5.001-10.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    5/5
  • Eigenschaften & Funktionalitäten
    3/5
  • Kundenbetreuung
    3/5
  • Preis-Leistungs-Verhältnis
    3/5
  • Wahrscheinlichkeit der Weiterempfehlung
    7/10
  • Quelle des Nutzers 
  • Bewertet am 25.1.2020

"Data Science 101 Platform for non-IT people"

Kommentare: It was the tool I learned the Data Science in the first place. So it is really good and intuitive with its graphical interface. For example you understand train-test split very well because you literally see the split as you work on it. As I progressed and needed more functions and more custom solutions, I started using Python scripts and solved it like that. So it gave me all these abilities.

Vorteile: - Its ease of use makes it possible for non-IT, non-developer, non-CS background people to make data manipulation, preprocessing, mining, visualization and modelling.
- It has a graphical interface with nodes and connections so that you don't need to know Python/R to make predictive models or association rules/recommendation systems.
- There's a vast library of functions
- Even more functions are created by the community so non-existing customized functions are created by the community, via existing functions.
- The visual flow of data makes it easy to understand and interpret it.
- It teaches the CRISP-DM methodology in an intuitive way thanks to its graphical user interface
- It can connect to SQL and similar servers so that the data can be read directly.
- It is possible to write own Python/R script for custom needs.

Nachteile: - Custom needs are hard to carry out.
- Functions have limited abilities and parameters
- Data visualization is weak and relatively primitive
- Model development is easy but deployment is hard
- It is very slow unfortunately and I think this is KNIME's most important drawback

  • Quelle des Nutzers 
  • Bewertet am 25.1.2020
Stephen S.
Director
Non-Profit-Organisation Management, 201-500 Mitarbeiter
Verwendete die Software für: 6-12 Monate
  • Gesamtbewertung
    5/5
  • Benutzerfreundlichkeit
    4/5
  • Eigenschaften & Funktionalitäten
    4/5
  • Kundenbetreuung
    5/5
  • Preis-Leistungs-Verhältnis
    5/5
  • Wahrscheinlichkeit der Weiterempfehlung
    10/10
  • Quelle des Nutzers 
  • Bewertet am 2.3.2018

"KNIME is a powerhouse for all types of analysis, including machine learning. "

Kommentare: We were able to build a reproducible workflow for analyzing our data and creating actionable insights.

Vorteile: KNIME desktop is a powerful tool for building analytical workflows. The visual interface is extremely helpful. They also have extensions to integrate other tools like R and Python into the workflows. Best of all you can share your workflows with others - great for reproducible research. There are built in tools for many types of supervised and unsupervised machine learning. The desktop application is free and open source. The support community on the KNIME website is very active and responsive. To extend the features you can purchase KNIME server.

Nachteile: Like any new tool there is a learning curve. However, they have lots of videos, examples and an active support community. There are some features that are not intuitive, such as how to use flow variables. In general I have found that I use R much less now and do most of my analysis in KNIME. KNIME is primary drag and drop and requires little to no coding.

  • Quelle des Nutzers 
  • Bewertet am 2.3.2018