The goal for all data collection is to capture quality evidence that allows analysis to lead to the formulation of convincing and credible answers to the questions that have been posed. A formal data collection process is necessary as it ensures that the data gathered are both defined and accurate. We at BtoB DataBoxx sourcing these information both manually and digitaly.

With the help of both manual and technical verification we segregate and rectify corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. After cleansing, a data set should be consistent with other similar data sets in the system. The actual process of data cleansing may involve removing typographical errors or validating and correcting values against a known list of entities. The validation may be strict (such as rejecting any address that does not have a valid postal code), or with fuzzy or approximate string matching (such as correcting records that partially match existing, known records).

In a world where data-driven companies consistently outperform their competitors, businesses who don’t make the most of their data are set to fall behind. Thus unverified data could be dangerous for any businesses looking to grow their digital assets. We at BtoB Databoxx verify the data sets witha set of process to ensure the data quality and accuracy.

With all the vefified information we profile each companies with their top level decison making contacts and other relevant departmental contacts.