Lighting Data Suite

Lightning Data Suite (LDS) is an AI-powered data modernization solution designed to help enterprises migrate, modernize, and govern data platforms faster with lower risk. Built on leading cloud data platforms like Microsoft Fabric, LDS combines AI, automation, and intelligent accelerators to reduce manual effort across discovery, migration, engineering, quality, and validation. LDS enables organizations to move from legacy and fragmented data landscapes to modern, analytics-ready platforms with confidence, speed, and measurable outcomes.

Challenges:

Enterprise data modernization initiatives often struggle with slow discovery, poor data quality visibility, manual schema mapping, high engineering effort, and delayed validation. These challenges increase cost, extend timelines, and introduce migration risk. Lightning Data Suite addresses these challenges by embedding AI across the modernization lifecycle, enabling:

1. Faster understanding of complex legacy data environments
2. Early detection of data quality issues and migration risks
3. Automated pipeline creation and schema mapping
4. Intelligent cataloging and governance of modernized data assets
5. Accelerated testing and validation to ensure business trust

Key capabilities:

Lightning Data Suite applies AI across data management, engineering, and BI to continuously learn from metadata, schemas, and usage patterns.

1. Autonomous data discovery and cataloging: AI-driven discovery automatically scans source and target systems to identify data assets, relationships, and metadata. This enables faster onboarding, improved governance, and easier compliance.

2. Intelligent data quality management: Built-in AI profiling assesses completeness, accuracy, consistency, and anomalies early in the migration lifecycle, reducing downstream failures.

3. AI-powered data engineering: Automated pipeline generation and transformation logic significantly reduce manual engineering effort and accelerate time-to-value.

4. Proactive insight delivery and recommendations: LDS surfaces insights, risks, and recommendations throughout the modernization journey, helping teams make informed decisions earlier.

5. Dynamic and adaptive dashboards: Real-time dashboards provide visibility into data quality, migration progress, and operational health, adapting as the platform evolves.

How it works:

Lightning Data Suite includes a modular set of AI-powered accelerators that can be deployed together or independently based on customer needs:

1. IntelliDQ: AI-driven data profiling and quality assessment to identify issues early and mitigate migration risk.
2. IntelliPipe: Automated data pipeline generation to reduce engineering effort and accelerate delivery.
3. IntelliMapper: Intelligent schema and data mapping to improve accuracy and reduce manual rework during migration.
4. IntelliCatalog: AI-powered data catalog for automated discovery, governance, and compliance.
5. IntelliC360: Intelligent Customer 360 enablement to unify data across domains for analytics and insights.
6. IntelliConvert: AI-assisted conversion of legacy logic, schemas, and transformations to modern cloud platforms.
7. IntelliQA: AI-driven test case generation, test data creation, and validation scripts to improve productivity and confidence. All components operate within Harmoni.AI, Sonata’s responsible AI framework, ensuring governance, transparency, and ethical AI usage.

Supported platforms: Lightning Data Suite is designed to work seamlessly across modern data platforms, including:

• Microsoft Azure/Fabric: This flexibility allows customers to modernize on their preferred platform without vendor lock-in.

Use cases:

1.Enterprise data warehouse modernization 2. Legacy system migrations to cloud data platforms 3. Data quality improvement and governance initiatives 4. Customer 360 and analytics modernization 5. Large-scale data transformation and validation programs

Business impact:

Organizations using Lightning Data Suite can expect:

1. 30–40% faster data modernization timelines
2. 35–50% Reduced engineering and migration effort through automation
3. 25–60% Improved data quality and trust from day one
4. 20–35% Lower migration risk through early validation and AI-driven insights
5. 2x Faster realization of analytics and business value

Who benefits:

• Data Architects • Cloud Architects (Azure, Fabric) • Enterprise Architects • Data Engineering Lead • Head of Engineering • Migration Architect