![]() Legacy business intelligence platforms are designed to focus on descriptive analytics, which can take the form of reports, dashboards, and other static ways for organizations to understand how their data is changing. While Databricks and Delta Lake have been redefining how companies leverage data lakes in their data architecture, legacy business intelligence has been undergoing a similar evolution with new decision intelligence platforms like Tellius. What is AI-Powered Decision Intelligence? Taken in aggregate, Delta Lake has made the promise of the open data lakehouse into a reality for many organizations. As an open-source format storage layer, Delta Lake reduces the business risk of vendor lock-in. Delta Lake does this by leveraging Parquet files with a file-based transaction log for ACID transactions and scalable metadata handling. It essentially combines the best aspects of the data warehouse-reliability and performance-with the scale of a data lake. It includes metadata, caching, and indexing and is compatible with query engines like Apache Spark, Apache Hive, Presto, and Trino. Delta Lake is an open-storage format layer optimized for file-based storage. This has led organizations to look for new solutions to the problem of managing data and also led to the rise of the open data lakehouse paradigm.ĭelta Lake makes data on the data lake more accessible and reliable by providing data warehouse-like capabilities on top of the lake. Companies also have increasingly realized the business risk associated with vendor lock-in due to the proprietary storage formats of data warehouses. Even so, as data usage becomes more intensive at organizations, the cost and problems associated with managing a data warehouse only rise. The utilization of a data warehouse was largely seen as a result of the real or perceived lack of performance and reliability from a data lake architecture. Because data lakes were not initially thought of as a place for production analytics, they were used as a low-cost storage solution for a company’s flood of raw data. They can help organizations centralize their data architecture and eliminate silos by providing a repository for all data.Īt the same time, many organizations have struggled with the full promise of the data lake. Because data lakes have no predefined schema, they offer the flexibility to hold a wide variety of data, including images, videos, NoSQL databases, time-series data, and much more. Data lakes are highly scalable and have the ability to store many different types of data, including structured, semi-structured, and unstructured data, at a very low cost. Decision Intelligence Lakehouse Use Casesĭelta Lake + the Databricks Lakehouse Platformįor years, data lakes have been touted as the next evolution of the data storage paradigm, and many organizations today leverage data lakes in their data architecture.What is AI-Powered Decision Intelligence?.Delta Lake + the Databricks Lakehouse Platform.
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