Microsoft Enhancing Azure Data Lake Capabilities with ADRM Acquisition
Microsoft announced on Thursday that it bought ADRM Software Inc., a maker of data models for various industries.
The terms of the deal weren't described in the announcement, but the entire ADRM team is joining the Microsoft Azure global engineering team, according to a Thursday announcement by Kevin Schofield, ADRM's president and CEO. He described the combination of Azure storage and compute capabilities with ADRM's data models as empowering "the next generation of intelligent data lakes."
These data lakes provide "metadata-rich foundations which can supercharge modern data warehouses, next-level analytics, and AI [artificial intelligence] and ML [machine learning]," Schofield added.
The intelligent data lakes concept was echoed in Microsoft's announcement by Ravi Krishnaswamy, Microsoft's corporate vice president for Azure Global Industry, who indicated that intelligent data lakes can harmonize data from "multiple lines of business," which can then scale via Azure infrastructure.
ADRM describes itself as a 30-year-old company with customers in 18 countries worldwide. Its data models are used "across 65 different lines of business in 10 industry groups." The models are used for things like enterprise data governance, data warehouse, data lakes, business intelligence and master data management, among other functions. ADRM's models are used in communications and media, financial services, government, manufacturing, insurance and health care, among other industries.
ADRM defines a data model as "a graphic representation of the data within a specific area of interest" per its FAQ. The idea behind the models is to convey the relationships among data. The company has three data model types: an Enterprise Data Model, a Data Warehouse Model and Business Area Models.
Industries tend to follow similar structures, which makes the data models fairly stable, according to the FAQ:
The data required by organizations within the same industry tend to be very similar. This is why we can assume that data models have basic stability within the organization while process models are relatively unstable.
Data models don't really change too much for organizations, "unless the business changes the fundamental way that it does business or enters into a new line of business," the FAQ explained.
Kurt Mackie is senior news producer for 1105 Media's Converge360 group.