5 Steps to Data Cleansing of Customer Data 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. Read More:goo.gl/Kn2nKf #Dataprocessing #Dataanalyst #Datacleaning #Dataentry
Why Is Data Cleansing Essential For Successful Master Data Management? Technology has enabled businesses to expand their base and go global. This has led to many alliances and associations being formed, as every organization aspires to grow larger and achieve success. Though many entrepreneurs consider forming associations as a strategy to move up the ladder, they fail to realize that with growth, there would be an additional dose of responsibility that they must undertake. Read More...
It looks for corrupted data records and hunts them down. This whole data cleansing process can be applied on a set of data records, data tables or on an entire database. At times, after a full process of web scraping or data harnessing, you can end up with a lump of dirty data sets as the sole output of the entire hard earned day. What happens next? It affects your decision making quality as the analysis of dirty data veers you off from the true information.
B2B Data Cleansing Services: Marketing Big Data: Why Continuous Data Cleansing ...
"Many of the sophisticated statistical techniques out there are created to sort out data quality problems. Scientists are always skeptical about data quality and are used to dealing with questionable data. So for them the lake is important because they get to work with raw data and can be deliberate about applying techniques to make sense of it, rather than some opaque data cleansing mechanism that probably does more harm that good."
5 Types of Unclean Data and How to Clean Them: Data quality is no longer something that any organization can avoid or put on the back burner. With all data being considered as assets, it is critical to ensure data credibility at every stage of processing. Today we tell you about the errors that can creep in your data and how you can ensure that it does not affect your business. More #VerdantisBlog http://blogs.verdantis.com/5-types-unclean-data-clean/