Snowflake | Partnerships | Tiger Analytics

Our Capabilities

Cloud Adoption Blueprinting & Advisory

Define business cases, build data strategies, and design scalable Snowflake architectures aligned to enterprise goals and future growth.

Cloud Data Warehouse (DWH) CoE Setup & Extension

Establish best practices, reusable frameworks, and governance models while enabling teams with training and standardized operating models.

Infrastructure Planning & Optimization

Perform workload sizing, cost optimization, and performance tuning with robust monitoring to ensure efficient Snowflake utilization.

Cloud DWH Implementation & Migration

Deliver end-to-end data engineering, seamless migration from legacy systems, and implementation of DataOps/MLOps for automated, scalable pipelines.

AI & Advanced Analytics Enablement

Leverage Snowflake Cortex AI and Tiger’s ML capabilities to build predictive models, enable real-time insights, and drive intelligent decision-making.

Unified Data Platform Development

Break down data silos by integrating structured and unstructured data into a governed, scalable Snowflake ecosystem for enterprise-wide analytics.

Our Accelerators

Source-to-Target Mapping (STTM) Code Generator

Data Migration & Validation Toolset

Data Quality Rule Framework

dbt Excellence & Snowflake Review Framework

Snowflake Cost Monitoring Framework

Snowflake Query Optimizer

ETL-to-Snowflake Migration Accelerator

DBT Observability

Snowflake Data Intelligence

Data Modelling

Accelerating Data Harmonization

Data Catalog

Automated Metadata Ingestor (Tech & Biz. Metadata)

Source-to-Target Mapping (STTM) Code Generator

Cortex AI-powered accelerator that transforms business rules and STTM documents into production-ready Snowflake code. It automatically interprets source-to-target mappings, applies Snowflake-optimized data type conversions, and generates standardized DDL, DML, and stored procedures for landing, staging, and curation layers. Generated code will comply with the coding standards and be performance-optimized.

Data Migration & Validation Toolset

A configurable, metadata-driven Python framework for automated data ingestion, historical data migration, and end-to-end validation across enterprise data platforms. Supports relational databases, files, APIs, and semi-structured data with scalable, reusable pipelines designed for high-volume and reliable data movement.

Data Quality Rule Framework

Snowflake-native solution that combines automation and AI to proactively improve data trust and governance. It profiles data, discovers quality rules using Cortex AI, and automatically generates deployable Great Expectations validation suites. The framework continuously monitors data quality, detects anomalies, and triggers alerts through Email or Slack when thresholds are breached. By reducing manual profiling and rule creation efforts by up to 90%, it delivers a self-evolving, centralized data quality ecosystem with minimal operational overhead.

dbt Excellence & Snowflake Review Framework

Deep-dive review of project modularity, macro usage, and materialization strategies, Automated linting and SQL pattern analysis, dbt test coverage and documentation completeness and inefficient join patterns or "expensive" models.

Snowflake Cost Monitoring Framework

A centralized framework to monitor, analyze, and optimize Snowflake consumption across warehouses, users, workloads, and business units with near real-time visibility into compute and storage costs.Enables proactive cost governance through usage trends, anomaly detection, chargeback/showback reporting, budget tracking, and optimization recommendations.

Snowflake Query Optimizer

A Cortex-powered Snowflake Query Optimizer that intelligently analyzes query performance bottlenecks and automates optimization recommendations to improve execution efficiency and reduce compute costs.The solution consists of three integrated modules: a Root Cause Analyzer to identify performance issues, a Recommender Engine to suggest tuning strategies, and a Query Rewriter to automatically generate optimized SQL patterns and best-practice transformations.

ETL-to-Snowflake Migration Accelerator

AI-powered modernization framework that analyzes legacy ETL implementations at the object, feature, and configuration levels to assess migration complexity and identify optimization opportunities. It automatically converts ETL workflows and transformation logic into Snowflake-native SQL or DBT models, while applying performance optimization and code standardization best practices. Built-in validation and regression testing ensure business logic consistency and data accuracy throughout the migration process. The accelerator reduces migration effort by up to 70%, accelerates cloud adoption, and minimizes risk while preserving critical enterprise data processing logic.

DBT Observability

A comprehensive DBT Observability framework that provides real-time monitoring of pipeline executions, lineage, freshness SLAs, and resource utilization to ensure reliable and transparent data operations.Enables proactive issue detection and faster recovery through automated alerts, operational dashboards, and end-to-end lineage visibility for impact analysis and governance.

Snowflake Data Intelligence

Tiger Snowflake Data Intelligence is a one-stop solution for Data Integration and Data Management needs on Snowflake. It provides a configurable and scalable design, enabling you to adapt and expand effortlessly as your data landscape evolves.

Data Modelling

Empower your data strategy with our Snowflake Data Modeling Accelerator, delivering optimized schemas and structures for faster insights and scalable analytics. Includes data insights, data model generation tool, and data dictionary & governance tool.

Accelerating Data Harmonization

Data Build Tool (DBT) – Tiger Libraries – drive seamless data harmonization with Tiger Analytics' dbt-powered libraries, accelerating transformations and ensuring unified, reliable data pipelines.

Data Catalog

Consolidates diverse metadata types, facilitating comprehensive data exploration with advanced search, lineage tracing, impact analysis, and real-time governance, ensuring holistic management and understanding of data ecosystems.

Automated Metadata Ingestor (Tech & Biz. Metadata)

Validates, enriches, and transforms metadata from diverse sources, supporting custom validations, intelligent enrichment through ML, and creation of tailored properties, empowering seamless management and enhancement of metadata.

Snowflake Marketplace: Native Apps

Ready-to-deploy, AI-driven solutions available directly in your Snowflake account.

Tiger Analytics

STTM CodeGen

The Tech: Powered by Snowflake Cortex AI.
The Value: Automatically converts plain-English business rules (Source-to-Target Mappings) into optimized Snowflake SQL.
Impact: Eliminates manual coding errors and accelerates pipeline development by 3x.

View Listing on Snowflake Marketplace

Tiger Analytics

Data Quality Management (DQM)

The Tech: A Snowflake Native App built with Snowpark and Streamlit.
The Value: Leverages Cortex LLMs to automatically profile schemas and recommend Data Quality (DQ) rules. It generates Great Expectations (GX) validation suites tailored to your business logic.
Impact: Ensures 100% data trust with NLP-based insights and automated anomaly detection.

View Listing on Snowflake Marketplace

Tiger Analytics

Cortex Powered Snowflake Query optimization

The Tech: Cortex AI-driven SQL optimization engine.
The Value: Uses Cortex AI to analyze complex query execution patterns and automatically generate actionable optimization recommendations for engineering teams. It reduces manual trial-and-error tuning, improves query performance and warehouse efficiency, and keeps all processing securely within the Snowflake environment without moving data outside the platform.
Impact: Delivers a 20% to 40% reduction in Snowflake compute costs by identifying and optimizing inefficient query patterns. Accelerates critical dashboard and report performance by up to 5x, while significantly reducing engineering effort spent on manual query troubleshooting and performance tuning.

View Listing on Snowflake Marketplace

Summary of Value (The “Tiger Effect”)

Tiger Analytics brings a differentiated approach to Snowflake adoption by combining deep domain expertise, scalable engineering, and AI-driven innovation—delivering measurable business outcomes at speed.

01

Faster Time-to-Value

Pre-built accelerators, reusable frameworks, and proven delivery models significantly reduce implementation timelines and enable rapid insights.

02

Cost Efficiency at Scale

Optimized Snowflake architectures, workload management, and governance frameworks help control costs while maximizing performance.
03

Business-Ready Data Ecosystem

Build a unified, governed, and high-quality data foundation that empowers business users with trusted, actionable insights.

04

AI-Driven Decision Intelligence

Integrate advanced analytics and AI capabilities directly within Snowflake to move from descriptive reporting to predictive and prescriptive decision-making.
05

Reduced Risk & Improved Governance

Standardized processes, automated quality checks, and robust metadata management ensure compliance, reliability, and transparency.
06

Sustainable & Scalable Growth

Future-ready architecture and operating models that evolve with business needs, supporting continuous innovation and expansion.