A crowd of people gathered around a cornerstone of a building in Brooklyn. They could barely contain their excitement that October day in 2014.
A time capsule from 1950 was about to be opened, revealing mysterious contents. No one knew what to expect. Historical treasures? Letters from the past? Maybe even gold bars or valuable collectibles? The crowd strained to hear what officials would announce to the crowd as they opened the container. Continue reading
Data cleansing is hard to do, hard to maintain, hard to know where to start. There seem to always be errors, dupes, or format inconsistencies. One of the most challenging aspects of data cleansing has got to be maintaining a clean list of data, whether it’s sourced from multiple vendors or manually entered by your hard-working interns, or a combination of both. One mistype could create a whole myriad of problems within your database, and can lead to hours upon hours of manual cleansing that could so easily have been avoided. So what is the solution to these frustrating, time consuming problems? Continue reading
There is only one drawback to data-driven marketing: It requires conclusive, comprehensive data to be effective. While this may seem obvious, some brands continue to make important decisions about their marketing with an inaccurate or incomplete email database. Unfortunately, if they don’t do anything to verify their data (particularly user email addresses), they’ll be unaware of one of the primary reasons their marketing efforts failed. Continue reading
It is necessary for organizations to have an updated database, both for ensuring efficient contact with their customers and maintaining compliance standards. Data Cleansing or data scrubbing is the process of identifying and correcting inaccurate data from a data set. With reference to customer data, data cleansing is the process of maintaining consistent and accurate (clean) customer database through identification & removal of inaccurate (dirty) data. Here, inaccurate data stands for any data that is incorrect, incomplete, out-of-date, or wrongly formatted. Continue reading