Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.
More and more, we have seen the term “lakehouse” referenced in today’s data community. Beyond our own work at Databricks, companies and news organizations alike have increasingly turned to this idea of a data lakehouse as the future for unified analytics, data science, and machine learning. But what is a lakehouse? Join us for our upcoming virtual event: Delta Lake: the Foundation of Your Lakehouse.
Businesses are looking to drive strategic initiatives
As the size and complexity of data at organizations grow, businesses are looking to leverage that data to drive strategic initiatives powered by machine learning, data science, and analytics. The companies that manage to leverage this data effectively are driving innovation across industries. But doing so is challenging - the old ways of managing data can’t keep up with the massive volume. Traditional data warehouses, which were first developed in the late 1980s and were built to handle these large and growing data sets, are expensive, rigid and can’t handle the modern use cases most companies are looking to address.
As an attempted solution, companies turned to data lakes - a low-cost, flexible storage option that can handle the variety of data (structured, unstructured, semi-structured) that is required for the strategic priorities of enterprises today. Data lakes use an open format, giving businesses the flexibility to enable many applications to take advantage of the data.
While data lakes are a step in the right direction, a variety of challenges arise with data lakes that slow innovation and productivity. Data lakes lack the necessary features to ensure data quality and reliability. Seemingly simple tasks can drastically reduce a data lake’s performance and with poor security and governance features, data lakes fall short of business and regulatory needs.
The best of both worlds: lakehouse
The answer to the challenges of data warehouses and data lakes is the lakehouse, a next generation data platform that uses similar data structures and data management features to those in a data warehouse but instead runs them directly on cloud data lakes. Ultimately, a lakehouse allows traditional analytics, data science, and machine learning to coexist in the same system, all in an open format.
To build their lakehouse and solve the challenges with data lakes, customers have turned to Delta Lake, an open format storage layer that combines the best of both data lakes and data warehouses. Across industries, enterprises have enabled true collaboration among their data teams with a reliable single source of truth enabled by Delta Lake. By delivering quality, reliability, security and performance on your data lake — for both streaming and batch operations — Delta Lake eliminates data silos and makes analytics accessible across the enterprise. With Delta Lake, customers can build a cost-efficient, highly scalable lakehouse that eliminates data silos and provides self-serving analytics to end-users.
Join us for our upcoming virtual event Delta Lake: the Foundation of Your Lakehouse.
In the event, you will learn more about the importance of a lakehouse and how Delta Lake forms its foundation. Through a keynote, demo and story of a customer’s experience with Delta Lake, you will gain a better understanding of what Delta Lake can do for you and how a lakehouse architecture can create a single source of truth at your organization, and unify machine learning, data science, and analytics. We hope you’ll join us and look forward to seeing you soon!