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Alcazar


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. LTIMindtree’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.

Our Services


LTI Canvas Alcaza

Key Features

Cost Saving

Cost Saving


An automation-led approach for massive cost savings, up to 50%.

Reduced Efforts

Reduced Efforts


Automated and simplified data migration activities reduce efforts.

De-risked Migration

De-risked Migration


Accelerators based on key principles, best practices, and industry guidelines minimize risks.

Optimized Platform

Optimized Platform


Constant platform monitoring furnishes insightful recommendations for optimization.

Our Offerings

Plan


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

Plan

Migrate

Migrate


Migrate an on-premises database to the Databricks platform with a complete migration framework comprising of

  • Source Inspect
  • DatabricksConvert
  • DatabricksMigrate
  • Data Match

Optimize


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

Optimize

Solutions and Accelerators

 
Source Inspect:

Source Inspect:

Automated analysis of current legacy EDW, MPP, and Hadoop objects with complexity analysis.

DatabricksConvert:

DatabricksConvert:

Migrate/ transform the source database objects from source syntax into equivalent Databricks objects.

DatabricksMigrate:

DatabricksMigrate:

Automated migration of data from Source tables to Databricks Catalog in an optimized manner using Databricks features.

Data Match:

Data Match:

Row and Column level validations of migrated data between source and Databricks with detailed reports.

FinOps:

FinOps:

Provides insights into Databricks usages and provides recommendations for better cost and performance optimization.

Databricks Mesh:

Databricks Mesh:

Accelerators to help implement Data Mesh in Databricks, thereby enabling an organization to be a data-driven organization by using data as a product.

KenAI:

KenAI:

Deploy, Test, Package, and Monitor model drift, data drift, and service health of your ML models.

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