KNIME Software: Creating and Productionizing Data Science

KNIME Software: Creating and Productionizing Data Science


More and more businesses rely on data. And today, more than ever, business success
relies on getting fast insights out of that data. From finding new cures to diseases, to reliably
predicting energy usage in cities, or making transportation systems faster and safer, data
science teams are charged with creating and delivering reliable analytical applications
and services to enable better decision making. Wouldn’t it be great if your data science team
could focus on what they do best? From gathering and wrangling data, or making
sense of it with sophisticated modeling and visualization techniques – and with the tools
and techniques they like using? KNIME makes this possible in one uniform,
intuitive environment. KNIME Analytics Platform is the open source
software for creating data science. Intuitive, open, and continuously integrating
new developments, it makes understanding data and designing data science workflows and reusable
components accessible to everyone. As you can see, building and executing a workflow
is easy! And, no coding is needed! Although if you do want to include code, KNIME
allows that, too. Node after node, you can assemble an entire workflow, with each node performing a dedicated task. Incremental execution provides instant feedback
at each step. Not sure where to start or need some inspiration? The KNIME Hub contains hundreds of ready-to-run
workflows, plus all the available nodes and components, with information
on what they do. KNIME connects to a host of databases, file
formats, web services, cloud storage systems, and big data repositories. It offers a large number of ETL, data blending,
and data manipulation functionalities and can visualize your data with classic charts
– bar charts and scatter plots, for example, or advanced charts such as sunburst
charts, parallel coordinates, or network views. KNIME also offers a large number of machine
learning models, such as decision trees, ensemble models, logistic regression, deep learning,
and more. And, since KNIME is open, you can do all of
this using your favorite tools. KNIME integrates seamlessly with other open
source projects such as R, Python, Keras, H2O, Apache Spark, and more. But, nobody is an island. Assembling data science workflows requires
help and contributions from your data science colleagues. KNIME Analytics Platform is complemented by
KNIME Server – the enterprise software for collaboration, automation, management, and
deployment of data science workflows as analytical applications and services. Connect to KNIME Server directly from KNIME
Analytics Platform and share your workflows and components throughout the organization. When your workflow is complete, it can be
deployed. You can expose your workflow as a web service,
or even give end users access to web-based analytical applications. The KNIME WebPortal – a feature of KNIME Server
– enables you to deliver your workflows as interactive, web-based analytical applications. End users, like business leaders, can be walked
through the complex interactions via a sequence of pre-determined web pages, pulling them
into the data science process at the right places and enabling them to get the insights
they need. Scaling the execution of your workflows is
also possible with KNIME, either by using the big data and Apache Spark integrations,
by taking advantage of the distributed executors on KNIME Server, or by moving your KNIME workflows
into the cloud. From gathering and wrangling your data, to
leveraging insights from them, KNIME Software can help you with both creating and productionizing
data science. Find out how at knime.com

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