It's December 6 and KNIME Analytics Platform is curving into Christmas with its latest 3.3 release.
The things most likely to immediately catch your eye are the new curved connections; we like to think they get the data sliding even faster through workflows ;-) There are some other nice noteworthy additions:
The Excel integration has been reworked both in terms of speed and support for really large excel files. There are a couple of new convenience nodes for dealing with variables such as the String Manipulation (Variable) while the Text Processing extension comes with a bunch of new integrations, including Apache Tika to read major document formats such as PDF, EMail, or Microsoft Office documents.
Are you storing your data in the cloud? With this new release you can seamlessly read and write your data to systems such as Amazon S3 or Microsoft Azure Blob storage.
Big Data analysts will be interested to try out the new file connectors to read and write standard Hadoop file formats (Avro, Parquet, etc.) and they will appreciate an improved integration of databases into their Apache Spark workflows, including nodes to embed database systems transparently and to query Spark tables by means of simple SQL as part of the KNIME Big Data Extensions.
These are just some of the improvements in this Christmas Release. You can find more detailed information on our What's New page and on the ChangeLog page. And note that upgrading from a previous KNIME Analytics Platform 3.x version is as easy as choosing the update link in KNIME Analytics Platform’s Welcome Page or by choosing File -> Update KNIME.
A new O’Reilly Media course is now available to learn the basics of Data Analytics and KNIME Analytics Platform. This is the course to recommend to beginners taking their first steps with KNIME Analytics Platform.
Introduction to Data Analytics with KNIME
A Data Science Approach to Analytics
About the course
This O’Reilly Media course will guide you step by step with hands-on exercises through the application of data analytics techniques using the KNIME Analytics Platform. It’s designed for learners with very little experience in data analytics or in programming. It is taught by our Principal Data Scientist, Dr. Rosaria Silipo here at KNIME and it covers everything a beginning data analyst needs to know.
About the tutor
Dr. Rosaria Silipo is not only an expert in data mining, machine learning, reporting, and data warehousing, she has become a recognized expert on the KNIME data mining engine, about which she has published three books: KNIME Beginner’s Luck, The KNIME Cookbook, and The KNIME Booklet for SAS Users.
SAN FRANCISCO (Aug. 8, 2016) — The creators of KNIME Analytics Platform, a popular open source data analytics, reporting and integration tool, will host their 2016 Fall Summit on Thursday and Friday, Sept. 15-16 in San Francisco. Making KNIME’s North American summit debut, the packed schedule of sessions will take place close to downtown at the Mission Bay Conference Center. Featuring more than 15 speakers from an array of industries and backgrounds, the summit promises to offer a fresh look at what is happening in the data science community.
The conference’s goal is to get the larger KNIME community to talk about the variety of applications and opportunities, as well as provide sneak peeks of new and upcoming features of the platform. This opportunity will bring users together and spur discussion on and around modern data analytics.
KNIME Analytics Platform 3.2.1 has just been released, providing some minor bug-fixes. Check out the changelog. You can try it out for yourself by updating your existing KNIME installation using the "Update KNIME..." action in the "File" menu or downloading it from here.
The new Workflow Coach is our brand new recommendation engine that suggests which node would best follow the last one, based on community usage statistics. Missing Node Installation means that you no longer have to look for the missing plugin or extension yourself. Now, when you open a workflow that contains nodes not in your workbench, the missing items can be selected and are then automatically installed.
We’ve also added new functionality to further advance our analytics capabilities. Here are just a few examples. Gradient Boosted Trees and Deep Learning are a new set of nodes for learning and scoring both classification and regression models. The PMML Transformation Applier is a new node that applies all of the preprocessing operations described in a PMML document to a data stream.
Have you been needing to analyze linked data? Well, now you can with new functionality enabling access to the Semantic Web and resources such as DBpedia and CHEMBL from within KNIME Analytics Platform.
Enjoy KNIME Cloud Analytics Platform on Microsoft Azure – find KNIME Analytics Platform on the Azure marketplace and launch a new machine in a matter of minutes. You can now also scale your analytics – launch the Azure machine most suitable for your workload and simply shut it down when you’re done.
KNIME Server can now be configured to manage license files for enhanced KNIME Analytics Platform functionality – such as the KNIME Personal Productivity package or the KNIME Big Data Extensions – getting new users started quickly and easily. The KNIME Server Rest API has also been further extended to allow upload and download of files and workflows.
Interested in big data analytics within KNIME? The KNIME Spark Executor 1.6 now allows you to run workflows with Spark nodes on clusters with Spark 1.5 and 1.6 – including support for Hortonworks and Cloudera distributions.