Data Drudgery

A common type of mechanism used to solve problems in the software industry is the workflow mechanism. at least in a very broad manner of description. A service has to do a particular job, but to do that particular job it has to query a couple of other services, and then process all the information, persist it and then update a downstream service with the processed information. I'll give an example from the advertising domain. Any advertising platform must find out a way to filter out bad ads, could be because of vulgar test, photo not following resolution guidelines etc. The seller interface registers the new ads in the main database. The ad quality service periodically gets the new ads from the registration service which are marked as under processing. The ad quality service has to make the ad go through multiple local checks with local persistence, and then finally it has to update the ad server with the final verdict on whether the ad follows all guidelines and is good to

A very common question among people new or about to enter the software industry is where and how are algorithms and data structures used. Software development is mostly about applying known algorithms to a particular problem domain and tweaking it with some data structure either to fit the input space or to make some particular performance improvement due to some specificity of the problem domain. Below is one such example from the domain of workplace analytics. Let’s take the example of workplace analytics, a new domain where organizations are using data to find out what perks work, what attributes contribute more to employee satisfaction and performance. One example is Google finding out, based on data, that new mothers had a very high attrition rate, and Google increased the maternity leave by two months and it reduced the attrition in new mothers by 50%. Similarly, some sales focused organizations have found using workplace analytics tools, that employees not the ones wor