Automated analysis of current legacy EDW, MPP, and Hadoop objects with complexity analysis.
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Overview
Data explosion is a significant phenomenon that poses a grave challenge to traditional on-premises data warehouse platforms today. Even continuous scaling of the platform does not match the data velocity, resulting in high procurement and operational costs. Modern-day organizations are, therefore, moving towards cloud-based data platforms that provide greater flexibility and cost-effectiveness. A traditional analytics platform comprises different tools, involves integration costs, and presents challenges. Databricks Lakehouse is a unified platform that stores, processes, and reports data and executes advanced use cases based on AI/ML.
However, modernizing on-premises data platforms demands a high degree of planning, reverse engineering, and technical competencies, leading to higher costs, effort, and significant time. LTM’s Alcazar is an intelligent modernization accelerator for Databricks migration that addresses these challenges. It provides automated solutions for Data/Schema and ETL migration and a suite of MLOps accelerators for simplifying AI/ML implementation with Databricks. Testing and developing Advanced Data Science use cases in real time becomes quick and easy.
Key Features
Our offerings
Strategize end-to-end migration scope and design with a design framework based on technology consulting, which encompasses
- Vision and Roadmap
- Solution Selection
- TCO Calculation
- Business Case
Migrate an on-premises database to the Databricks platform with a complete migration framework comprising of
- Source Inspect
- DatabricksConvert
- DatabricksMigrate
- Data Match
Optimize the Databricks platform and enable AI/ML use cases with our accelerators
- FinOps: Monitor and optimize
- KenAI: Operationalize AI/ML models
- Data Science: Leverage proven Data Science solutions
Solutions and Accelerators
Migrate/ transform the source database objects from source syntax into equivalent Databricks objects.
Automated migration of data from Source tables to Databricks Catalog in an optimized manner using Databricks features.
Row and Column level validations of migrated data between source and Databricks with detailed reports.
Provides insights into Databricks usages and provides recommendations for better cost and performance optimization.
Accelerators to help implement Data Mesh in Databricks, thereby enabling an organization to be a data-driven organization by using data as a product.
Deploy, Test, Package, and Monitor model drift, data drift, and service health of your ML models.
Resources
Data Intelligence Platform-The New Databricks Avatar is Set to Revolutionize Data Platforms
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The Fast-Track is Getting Faster: Why the Data Intelligence Platform is the Best Place for Your Gen AI Projects
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