February 27th, 2023 | 6 min read
A Brief History of the Microsoft Intelligent Data Platform
The Microsoft Intelligent Data Platform is a suite of tools and services that enable businesses to manage and analyze large amounts of data. Although not officially launched until 2022, the origins of this powerful ecosystem can be traced back over 30 years. The platform has evolved over time to keep pace with changing technologies and business needs, and most recently was expanded to include technology, consulting and ISV partners to complement and build upon its capabilities.
Here's a brief history of the Microsoft Intelligent Data Platform:
The Origins of SQL Server (1989-1995)
The origins of the Microsoft Intelligent Data Platform can be traced back to the early days of SQL Server, which was first released in 1989 for the OS/2 operating system. SQL Server was designed to be a relational database management system (RDBMS) that could store and manage large amounts of data.
Over the years, SQL Server evolved and gained new features, such as support for stored procedures and triggers. Microsoft also released versions of SQL Server for Windows NT and Windows 2000, which helped make it a popular choice for enterprise-level applications.
The Rise of Business Intelligence (1995-2005)
In the late 1990s and early 2000s, the concept of business intelligence (BI) began to gain popularity. BI refers to the tools and processes that businesses use to analyze data and gain insights into their operations.
To meet the growing demand for BI tools, Microsoft released a suite of products under the banner of Microsoft Business Intelligence. These products included SQL Server Analysis Services, which allowed businesses to create multidimensional data models, and SQL Server Reporting Services, which enabled users to create reports and visualizations.
The Emergence of Big Data (2005-2010)
In the mid-2000s, the amount of data being generated by businesses began to grow exponentially. This trend was driven by the rise of the internet, social media, and other digital technologies.
To help businesses manage and analyze this growing amount of data, Microsoft introduced a new product called SQL Server Integration Services. This product allowed businesses to extract, transform, and load (ETL) data from a wide range of sources.
Microsoft launched its own Master Data Management offering - Master Data Services (MDS) - as part of Microsoft SQL Server 2008 R2 in 2010, and it has been included as a feature in every subsequent version of SQL Server.
The Cloud Era (2010-Present)
In 2010, Microsoft launched its cloud computing platform, Azure. Azure enables businesses to build, deploy, and manage a wide range of applications and services in the cloud. It has since grown to become one of the leading cloud computing platforms, competing with other major cloud providers such as Amazon Web Services (AWS) and Google Cloud Platform.
To support the growing demand for cloud-based data management and analysis tools, Microsoft continued to evolve its suite of data tools and services. This included the release of products such as Azure Data Factory, which allows businesses to orchestrate data workflows in the cloud, and Azure Stream Analytics, which enables real-time data analysis.
Microsoft also embraced open-source technologies, such as Apache Hadoop and Apache Spark, which allowed businesses to analyze large amounts of data using distributed computing techniques.
In October 2022 Microsoft announced the creation of the Microsoft Intelligent Data Platform Partner Ecosystem, consisting of a select number of technology companies, consulting firms, and independent software vendors (ISVs) that offer solutions and services that complement the platform. CluedIn is one such partner, forming part of the Governance pillar of the platform alongside Microsoft Purview. CluedIn is a recommended Azure-native Master Data Management provider and has also been endorsed as a modern alternative to MDS.
Today, the Microsoft Intelligent Data Platform continues to evolve to meet the needs of businesses of all sizes. With its wide range of tools and services, the platform allows businesses to manage and analyze data in the cloud, on-premises, or in hybrid environments. The ultimate goal is to allow companies to realize more value from their data by shifting the emphasis away from day-to-day data management and towards value-creation opportunities.
By Natasha Scott
Head of Demand Generation at CluedIn