Data Quality dimensions are useful concepts for improving the quality of data assets. Although Data Quality dimensions have been promoted for many years, descriptions of how to actually use them have often been somewhat vague. Data that is considered to be of high quality is consistent and unambiguous. Poor Data Quality results in inconsistent and […]
Data Cleansing: Why It’s Important
Click to learn more about author Avee Mittal. Data cleansing is an important step to prepare data for analysis. It is a process of preparing data to meet the quality criteria such as validity, uniformity, accuracy, consistency, and completeness. Data cleansing removes unwanted, duplicate, and incorrect data from datasets, thus helping the analyst to develop […]
A Brief History of Non-Relational Databases
First came relational databases, which provide a useful comparison for understanding non-relational databases. Invented by Edgar F. Codd in 1970, the relational database arranges data into different rows and columns by associating a specific key for each row. Almost all relational database systems use Structured Query Language (SQL) and are remarkably complex. They are traditionally […]