In the world of data management, the evolution of SQL Server has been a fascinating journey. From the early days of storing data in flat files to the current era of Big Data, SQL Server has undergone significant transformations to meet the growing demands of data-driven applications.

Data in Flat Files

In the early days, data was stored in flat files without any structure. Retrieving data from these flat files was a cumbersome process, lacking efficiency and data integrity. The database residing in flat files posed numerous challenges for data processing in applications. However, the need for proper data management was always present.

Edgar F Codd and 12 Rules

Edgar Frank Codd, a British computer scientist working for IBM, revolutionized the database world by inventing the relational model for database management. He presented 12 rules for the Relational Database, bringing discipline and structure to the chaotic world of databases. Relational databases improved data retrieval performance and introduced the concept of relationships between data.

Relational Database Management Systems

Following Edgar F Codd’s proposal of the 12 rules for Relational Database Management Systems (RDBMS), various vendors started building applications and tools to support the relationship between databases. This era marked a learning curve for developers who had never worked with database modeling before. Eventually, the concept of the relational database became widely accepted, leading to the development of expert professionals and high-quality products. The Entity-Relationship model also evolved during this time, providing an abstract way to describe databases.

Enormous Data Growth

As the popularity of RDBMS grew, organizations faced the challenge of managing the enormous amount of data generated by new age applications and social media. The race to provide developers with user-friendly RDBMS management tools intensified. However, the traditional relational database model had limitations when dealing with unstructured data. Data warehousing solutions emerged as a way to store and process large volumes of data, enabling organizations to build intelligent systems and provide real-time user experiences.

Interesting Challenge

While organizations had expertise in managing structured data, the world had already shifted to unstructured data. Videos, photos, SMS, social media messages, and other data sources contained valuable intelligence that needed to be brought together in a unified system. The way businesses operate has also changed, with technology being built to support user-demanded features. Real-time intelligence from fast-paced data flow has become a necessity, presenting challenges that traditional database systems cannot resolve.

Big Data is Reality!

The need for innovation in data handling and management led to the emergence of Big Data Science. Creative ways to capture and present data became essential to meet the demands of large volumes, variety, and velocity of data. Big Data has become a reality, shaping the future of data management.

Stay tuned for tomorrow’s blog post where we will discuss the basics of Big Data Architecture.