The marketing term “lakehouse,” a combination of the terms “data warehouse” and “data lake,” is used by Databricks to develop a cloud data platform. Based on the open source Apache Spark technology, Databricks’ lakehouse enables analytical queries against semi-structured data without the need for a conventional database schema.
Dependance, robust governance, top notch performance of data warehouses in an amicable & flexible manner and the machine learning support of data lakes are some of the premium features provided on the Databricks Lakehouse Platform which integrates the finest components of data lakes and data warehouses.
Lagozon Technologies support customers in implementing and scaling the Databricks platform by combining the best of data warehouses and data lakes and creating an open and unified platform for all data, analytics, and AI workloads. By removing the data silos that normally segregate and entangle data engineering, data science, and BI, analytics, and machine learning, this comprehensive solution Databricks streamlines modern data stack. Additionally, its standardized approach to data management, security, and governance enables to work more productively and develop more quickly.
Perks of Using Databricks Platform:
Data Integration from Multiple Sources
Importing huge volumes of transactional data into the Databricks Unified Analytics Platform has become quite easier using BI tools market-leading CDC capabilities.
Automating Data Pipelines
Boost organizational agility with fully automated data pipelines that handle everything from real-time data ingestion to data transformation and creation for analytics.
It synchronizes with the cloud providers on security, computation, analytics as well as AI services, allowing us to consolidate all of our data and AI workloads.