A Field Transform tells the reporter how to process a field for output. Different data types have different transform options. To display a field exactly as it appears in the database use the Raw Data transform, available for all data types. Count and Count Distinct. These transforms apply to the id data type and are used to count database records e. Use Count to tally the total number of records. Use Count Distinct to count the number of unique records, removing duplicates.
To demonstrate the difference between Count and Count Distinct , consider an example where you want to know the number of active patrons in a given month, where active means they borrowed at least one item. Each circulation is linked to a Patron ID, a number identifying the patron who borrowed the item.
If we use the Count Distinct transform for Patron IDs we will know the number of unique patrons who circulated at least one book 2 patrons in the table below. You can do advanced searches by country, source and year. One of the recent updates December 2 was the World Development Indicators database. You can follow them in Twitter undata. These are three long words that are easy to understand Take a look at my illustration below.
They are term formation methods. The new terms that we create by means of these methods would be ideal candidates to include in our termbase. Also, being aware of this process will help us identify good candidates when we are extracting terms from a corpus.
In a previous post I talked about the importance of managing stakeholders in terminology projects. Recapping from that previous post, projects are divided in process groups , like steps you use in recipes: Who is Who in Terminology: After months and months of writing and researching on terminology and stumbling upon name after name of terminologists who have made great contributions to the field of terminology, I was curious to learn about them and thought it would be a good idea to start writing short biographies, not only to share the information with you but also to honor them and their work.
Do you know who they are and what their contribution was? And then some more like Helmut Felber and Ingrid Meyer. So, hopefully, as time permits, I will also be talking about the most contemporary ones. The information provided will depend on what is available on the Internet. If you know some important detail about them as I publish their bios, please add a comment and enlighten us. Needless to say, I will start posting about our other exciting regular topics.
Just wait and see! Compile your key terms in a TermBank or translation glossary to ensure your company-specific terminology is used accurately and correctly. Matches relate to items in your Translation Memory TM. For every new translation project we undertake your TM will offer matches: An In-Context Exact ICE match is a piece of text which has been translated in a previous project and appears again in the current project, in exactly the same context the segments before and after it are the same as in the previous project.
Reduced costs for repeated and very similar content. Increased efficiency and faster translation turnaround times. Improved consistency and accuracy of your terms. Your language assets updated and aligned with your preferences. Review language assets 2.