Billing systems create invoices from data and ideally send them right away. Microsoft’s Word, Excel and Access are common tools to do the job. Sometimes, parts of the invoice creation process are already automated. Mostly, however, the majority of the work is still done manually because of the need for
Occasionally, aggregating data into information is a labour intensive, tedious job which takes lots of comparisons, consistency checks, summations etc.. Even the creation of the initial data can be complicated. The good news is, however, that practically all of these process steps can be completely automated: Starting with the extraction
There is usually more information in a given dataset than one would expect. The Austrian Post scandal has demonstrated this impressively and gives a faint idea of what Google is capable of doing, especially given the information grows faster than linear with the amount of data. So having more data
Classic data warehouses are relational databases whose structure is optimised for fast querying of the contained data. The power of data warehousing lies in the effective linking of data. This creates new insights into the underlying business. Typical applications are the combination of financial data with that of production by,
“Agile” is one of the most important innovations in the software development field. Properly applied, Agility helps to keep track, learn, housekeep and adhere to deadlines – as well as countless other petty things in everyday development. Scrum and SAFe in particular help to structure the development process and teams.