Variable data creator6/30/2023 ![]() ![]() If the press has to wait for the data to be prepared, the job will naturally take longer. Since the PDF is not created by the print service provider itself, it has no control over the quality of the PDF file and, above all, whether it allows fast processing. There are certain requirements for such PDF files in order to enable their high-performance processing in the DFE. In this case, the print service provider receives a PDF file containing many thousands of pages. In today's increasingly short-term pure service relationships, however, the customer must create the individualized PDF pages himself. In this case, there must be a close relationship between the customer and the print service provider to ensure that the data can be processed by the latter. The merging of the individual data with the template can take place directly in front of the press in its Raster Image Processor (RIP) or the Digital Front End (DFE) of the print service provider. Other applications include individualized labels or packaging, direct mailings and tickets, where the combination of variable data and designed templates almost always adds up to several thousand pages.Īs a rule, such print products are created on powerful machines that are now very fast. To persuade the customer or potential customer to buy the selected products, retailers can send them a postcard, for example, which should of course be addressed to them personally and perhaps include a discount code. These are the people who add products to their shopping cart in an online store but do not complete the order. One example is the so-called shopping cart droppers. In principle, individualized print communication is achieved by combining individual data - associated with the addressee of the communication - and designed templates. However, these products must then also be able to be output on high-speed presses in an acceptable time, which is not always unproblematic. Powerful applications and integrated marketing tools that enable the integration of variable or individual data are already available, and the result is usually PDF files. Among other things, this approach has implications for PDF creation and PDF workflows in prepress. This requires defined digital processes that combine information to produce individual print results. In commercial printing, too, ‘ Giesskannenprinzip’ or the ‘watering-can principle’ with standardized advertising campaigns has therefore had its day and is often replaced by individualized communication via variable data printing (VDP). ![]() This you can easily do in Table Creator node but as your list probably doesn’t come from it see here how to easily add new column with missing values to your data table (missing values in KNIME are denoted as red question marks).Due to the continuously increasing competitive pressure, companies are looking for ways and means to address their customers and prospects in a more targeted manner. Missing functionality in it is that you are unable to create new columns (and rows as well I think) with it so you should create it before and it’s best to be empty. Then you need to present users with option to input correct mapping for season column. Also after it you won’t need Column Filter node probably. So if I got your process right you should first get unique values and for it you can use GroupBy node as you did but also Duplicate Row Filter node (which is more intuitive and has a bit more options if you’ll need it in future). Especially when there are other (better) options for your use case. Controlling Table Creator node with flow variables is a bit cumbersome and I would suggest to stay away from it. ![]()
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