KNIME is an open source data analytics, reporting and integration platform. KNIME allows users to visually create data flows, selectively execute some or all analysis steps, and later inspect the results, models, and interactive views.
KNIME base version counts on more than 100 entry and exit nodes. These are preprocessing, cleansing, modeling, analysis and data mining as well as various interactive views, such as scatter plots, parallel coordinates and others. It integrates all analysis modules of the well-known WEKA data mining environment and additional plugins allow R-scripts to be run, offering access to a vast library of statistical routines..
- Scalability through sophisticated data handling
- High, simple extensibility via a well-defined API for plugin extensions
- Import/export of workflows
- Parallel execution on multi-core systems
- Command line version for “headless” batch executions
- Retrieves data from files or data bases
- Data manipulation: pre-processes your input data with filtering, group-by, pivoting, binning, normalization, aggregation, joining, sampling, partitioning…
- Views: visualize data and results through several interactive views, allowing for interactive data exploration
- Data mining: uses state-of-the-art data mining algorithms like clustering, rule induction, decision tree, association rules, naïve bayes, neural networks, support vector machines, etc. to better understand your data
KNIME Desktop is the standard interface to work with KNIME. It includes all the analysis functionalities and plugins named before.
KNIME Team Space
KNIME Server Lite provides basic workgroup functionality. Users can access a central repository to upload or download workflows.
The workflows on the server can be executed remotely so you can free up the local PC of those tasks that need more resources. You can use the resources of a server with greater capacity. Critical workflows can be blocked against any change of name, reset or implementation.
The Enterprise server has the same functionalities that the Lite server, but adding full user access control. It allows you to create different types of users and give privilege to the workflows and their implementation. You could also program workflows implementations at specific dates and times. The server can also be integrated into an existing SOA architecture by providing access to workflows via web services.
KNIME Cluster Execution provides a thin connection layer between KNIME and the cluster. This allows every node running in KNIME and every application integrated in KNIME to be executed on the cluster. Submission of data to the cluster and collection of the results is made very simple. Long-running analysis workflows can be executed on the computer cluster, freeing up resources for other productive work.
KNIME ReportDesigner is a plugin for KNIME Desktop and its goa lis to provide advanced reporting functionality for KNIME. KNIME ReportDesigner allows the usage of workflows as input for reports. The reports can be exported to commonly used reports formats such as: HTML, PDF, Word, Excel, or PowerPoint.
Annual support and maintenance service
DatKnoSys offers you a support and maintenance service for all KNIME products. This will make their usage as well as the integration of these applications easier for your company.
Our anual subscription for these services includes the following:
- Specific queries about the usage and analysis methods applied in customers’ solutions and projects.
- Unlimited quires for unlimited users about how the application works.
- Regular updates, so you can access the new features and functionalities.
- Corrections of errors and security updates between new versions.
- Support at second level, if necessary, with KNIME’s development team.
- Geographical proximity and local language.
- Attention and incident resolution.
DatKnoSys offers you an excellent training course in KNIME. It will help your understanding and usage of its applications.
- Introduction to KNIME Desktop: We will see the application set up, configuration and its plugins; the functioning, layout, categories and organization of the nodes; the basic characteristics of the application, the memory configuration and the data view.
- Ports and data bases: We will see different types of existing data in KNIME, data, data bases, PMML… We will learn how to connect to data bases, extract data with queries and refine them.
- Data manipulation: We will learn how data manipulation nodes work; row and column wise transformations; filtering; replacement of values; sampling; and data combination. We will understand the functioning of the data in the application. We will see organization and association nodes, joins, missing values…
- Scripting: We will learn how to use java-snippets and some other mathematical functions in KNIME.
- Time series: We will study nodes in order to work with time: dates and times. We will study how to get information of time-based fields, calculate mobile measurements and time differences.
- Data mining:: We will focus in the understanding of existing data mining techniques and their application. We will see how to analyze data, find patterns and relationships between them, create models and predictions including clustering, association rules, decision trees, regressions…
- Sample project: We will do a sample project using KNIME in order to create data analysis. Our client could suggest a certain analysis and give us data for the sample.
- Variables and iterative process: We will see how to use variables in KNIME process, how to use the expert mode. We will also look at the iterative process and how to create and use it.
- Integration with R and Weka: We will see R language usage, its applications for statistical analysis and its integration with KNIME. We will also see the integration of Weka data mining library and how to use it.
- Batch execution:we will see how to run KNIME workflows in batch mode and how to do it without opening KNIME Desktop.
- Introduction to KNIME Report Designer:In this chapter we will see how to install the reporting plugin in KNIME Desktop. We will also see the basic functionality of reports creation and how to alternate data viewing with report viewing.
- Reports elaboration: We will see how to elaborate a simple report with a table and a graph. We will see how to use graph wizard and how to put our logo in the report. We will also look at how to use page breaks, data mapping and data highlighting.
- Creation of advanced reports: : We will see how to create complex reports with different data and parameter sources, how to copy certain properties among reports and how to apply different styles.