As data is frequently updated within an organization, achieving quality data requires constant monitoring and measurement as well as improvement actions. In addition to defect correction for quality data, it…
When we design tables in a relational database, different tables can hold different information. This information is held in the form of an entity. So an entity can be defined…
Database Constraints are rules/restrictions that are applied to the database table columns to limit the type of data that can be persisted in a table. It provides a way to…
There are many layers in Enterprise Data warehouse(EDW) such as Integration/Semantic/Performance which serve their own purpose. In this blog post, we would go into detail about each of these layers.…
Metadata is the information that describes other data or, simply, it is data about the data. It is the descriptive, administrative, and structural data that defines a firm’s data assets. It…
While working as a developer, one needs to automate some of the existing SQL Queries using bash script without accessing the interactive MySQL prompt. In this blog post i will show the different ways to run sql queries using Bash Script.I will be using MySQL database in this Blog.
In this blog post we will load the retail data into MySQL instance and analyze it using Structured Query Language.SQL is one of the most popular languages among developers,data engineers,data scientists and DBAs.
Managing Data quality is one of the important aspect in a IT company.Accurate,consistent and timely available quality data in the relational database that organization use are essential to the management of organization today.
Normalization is the process of successively reducing relations with anomalies to produce smaller, well-structured relations.This blog post contains tutorials for database normalizations and First Normal Form, Second Normal Form, Third Normal Form, BCNF and Fourth Normal Form
A Slowly Changing Dimension is a dimension that stores and manages both current and historical data over time in a data warehouse.