This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.

For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.

Current data architecture is going through a revolution. Enterprises are starting to shift away from the monolithic data lake towards something less centralized: data mesh. It’s a relatively new concept, first coined in 2019, that addresses potential issues with data warehouses and data lakes that can cause businesses to be slow, unresponsive, or even suffer from data silos. What is a data mesh, and how could it benefit your business?

From databases to data warehouses and, finally, to data lakes, the data landscape is changing rapidly as volumes and sources of data increase. With a growth projection of almost 30%, the data lake market will grow from USD 3.74 billion in 2020 to USD 17.6 billion by 2026. Also, from the 2022 Data and AI Summit, it is clear that data lake architecture is the future of data management and governance.

The data lakehouse is a promising new technology that combines aspects of data warehouses and data lakes.

Gaps in patient healthcare, ranging from access and affordability, to those specific to race, gender, age and beyond, are widening across the US and leading to a variety of detrimental results for people, the healthcare system, and the economy itself. Such ongoing disparities are slowing the country’s ability to achieve population health and accounting for billions of dollars in unnecessary health care spending annually.

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. The data lakehouse is gaining in popularity because it enables a single platform for all your enterprise data with the flexibility to run any analytic and machine learning (ML) use case. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Current data architecture is going through a revolution. Enterprises are starting to shift away from the monolithic data lake towards something less centralized: data mesh. Data mesh is a relatively new concept, first coined in 2019, that addresses potential issues with data warehouses and data lakes that can cause businesses to be slow, unresponsive, or even suffer from data silos. Data mesh benefits are able to provide a wealth of advantages to your business.

What pray tell is a tautology? A tautology is something that, under all conditions, is true. It is kind of like gravity. You can throw a ball in the air and, for a few seconds, it seems to be suspended. But soon gravity takes hold, and the ball falls back to earth.