Lecture 02
Can KNIME Help in Big Data?
KNIME Large Data Extensions give graphical solutions to big data issues that are well-known and simple to use. These libraries combine the KNIME Analytics Platform's strength with Hadoop's benefits to maximise both technologies' strengths.However, if we try to explore connections across large data sets, it can wind up using all of our processing power and time. We can store, swiftly access, and operate with such massive volumes of data with the aid of big data platforms.
Though not every project requires big data! For example, the KNIME Analytics Platform can easily manage a few million rows for ETL or machine learning, provided the number of columns is constrained. With several millions of rows and a large number of input columns, performance begins to suffer. Be aware that when performance suffers, KNIME Analytics Platform execution gets slower, sometimes noticeably slower, although it does not crash.
Big data platforms undoubtedly improve the efficiency of process execution. Furthermore, integrating large data platforms into KNIME is straightforward and only requires three steps: first drag and drop the proper connector node, next set its access parameters, including credentials, and finally, finally run the node.
