LTIMindtree Scintilla
LTIMindtree’s Scintilla framework helps fasten the complex journey of moving SAS workloads to PySpark. Scintilla addresses the core challenges of designing, accelerating, and governing your data transformation journey. The tool enables automated conversion of SAS programs to PySpark, along with a smart analyzer, which summarizes SAS coding standards and complexity.
Key Benefits
Automation:
Accelerate your modernization journey to PySpark Data Cloud, which is predictable, cost-effective, and agile, without any impact on business continuity.
Cost Optimization:
Scintilla ensures comprehensive governance for costs, ensuring value delivery. In essence, monitor, optimize, and predict the cost across the PySpark Data Cloud.
Modernize & Monetize:
Improve business agility and scalability by adapting to a modern data stack. In a nutshell, build, maintain, and monetize your data products.
Our Framework
Scintilla provides a complete playbook, encompassing comprehensive automated migration strategies, to enable PySpark’s cloud data platform adoption.
Strategize
Ensure automated analysis of the existing data landscape during the initial assessment phase.
- Smart Analyzer: Performs landscape analysis, and provides complexity, and technical debt. It analyzes SAS codes, producing concise summaries within its intuitive reporting interface.
- Dependency Analyzer: Provides in-database object dependencies and lineage
- Domain Analyzer: Groups all the database objects into domains to identify nondependent clusters for deployments
- Change Monitor: The built-in intelligent conversion engine translates SAS codes into an executable PySpark code, with a transparent intermediate process
- Risk Factor Analyzer: Provides risk factor identification and an analysis mechanism to mitigate risks during automated conversion.
Convert
Automated code conversion and validation reduce manual efforts and improve efficiency.
- Object Convert: Converts the source-compatible objects into equivalent PySpark codes
- Odd Exclusion: Ensures the exclusion of elements like automatically-generated SAS macros and variables utilized by SAS DI jobs and transformations irrelevant to business logic.
- Code Segmentation: Segmenting parses SAS codes into distinct units based on their purpose, such as data blocks, procedure blocks (PROCs), macroblocks, and other sections.
- Lineage Summary: Provides details of input and output data sources and references (files, tables, etc.) referred to in the SAS code.
Business Benefits
- Scintilla brings downs the total execution cycle from 60 hours to ~15 hours every month, which gives enough time for businesses to validate and proceed with the next steps on time.
- Reduction in TCO – around USD 1.5 million annually
