Databricks | Partnerships | Tiger Analytics

Our Capabilities

Data Foundation

Implement a modern data platform with Tiger’s expertise in data ingestion from disparate sources, data processing and building Raw, Processes & Prepared layer for faster consumption leveraging Delta Lake, and Unity Catalog as part of Tiger Data Fabric Accelerator.

Data Modernization

Embark on a successful data modernization journey with Tiger’s migration competency and dedicated in-house accelerators that enhance data accessibility, improve data quality, and enable data-driven decision making. Utilize Databricks Autoloader to seamlessly migrate data from disparate legacy subsystems into a unified Databricks Lakehouse platform.

Data Governance and DataOps

Safeguard your data assets and ensure compliance with industry regulations with Tiger’s expertise in Unity Catalog implementation leveraging Delta Sharing. Tiger’s advanced DataOps solution and accelerators like TigerML enable you to enhance agility, reliability, and cost-effectiveness in delivering business value at scale.

Model and Serve

Efficiently optimize the complete data science/ML lifecycles spanning data preparation, modeling, and insights sharing via your SQL and BI applications with the help of Tiger’s in-house accelerator – Tiger MLCore with tools such as MLflow, Databricks Notebooks and Databricks Workflows powered by Unity Catalog.

Our Accelerators

Tiger Data Fabric

Tiger MLCore

Data Quality & Profiling Framework

Databricks Operations Monitoring

DataOps Observability

Intelligent Data Express (IDX)

Model Risk and AI Governance

Always ON Brand Equity

Next Best Action

Tiger Forge

Contact Center Copilot

Intelligent Data Engineering Agent (iDEA)

Augmented Data Quality (ADQ)

Financial Advisor Assistant

Tiger Data Fabric

Accelerator for Implementing Modern Lakehouse leveraging Databricks and the underlying cloud in a highly scalable manner with powerful Governance & Automation Capabilities at its core.

Tiger MLCore

This accelerator built on top of Databricks Delta Lake, MLFlow, and Unity Catalog brings a collection of end-to end MLOps workflow modules to accelerate the development of MLOps platforms and model management.

Data Quality & Profiling Framework

End-to-end solution for implementing configuration driven data testing with a library of more than 50 testing rules and the ability to add many more custom rules. This accelerator also has dashboarding capability for analyzing test and data profiling results.

Databricks Operations Monitoring

This accelerator built on top of Databricks Overwatch feature helps in implementing Governance best practices at the workspace level with a consolidated view of cost and infrastructure utilization patterns enabling 360° reporting for optimization.

DataOps Observability

The Observability accelerator captures vital operational and runtime metadata, encompassing pipeline jobs, runs, and datasets, including data quality (DQ) assertions. It offers comprehensive end-to-end data lineage across diverse cloud services, delivering insights into the versions of pipelines, datasets, and more.

Intelligent Data Express (IDX)

Intelligent Data Express (IDX) is an AI-powered Data Modernization accelerator designed to streamline Data Lakehouse management on Databricks.

Model Risk and AI Governance

Explore Tiger x Databricks’ Model Risk Management solution that integrates MRM’s best practices, AI governance controls, and Databricks-native observability to support regulatory compliance, transparency, and operational efficiency across the full model lifecycle.

Always ON Brand Equity

Explore Always ON Brand Equity to protect and grow brand value 24/7 with real-time intelligence that tracks sentiment, perception, and equity drivers across every digital touchpoint.

Next Best Action

Unlock AI-powered Next Best Action strategies to deliver personalized HCP engagement, boost brand performance, and maximize every commercial interaction.

Tiger Forge

AI Agent Development and Management Platform designed to redefine how enterprises build, deploy, and scale GenAI-powered agents. In today’s fast-evolving AI landscape, organizations face high build costs, fragmented development workflows, and the lack of unified, scalable platforms. These challenges make it difficult to iterate quickly, manage multiple models, and maintain governance across increasingly complex AI ecosystems. Tiger Forge addresses these gaps by providing a comprehensive, enterprise-ready solution that simplifies agent creation and oversight through an intuitive, no/low-code environment.

Contact Center Copilot

Tiger Analytics' Contact Center Copilot is a GenAI-powered assistant designed to boost agent efficiency and elevate service quality in today’s high-pressure contact center environment. It addresses the growing challenges faced by agents, including fragmented systems, repetitive manual searches, and increasing customer expectations that often lead to slower resolutions and burnout. The Copilot empowers agents with real-time insights, intelligent guidance, and faster access to accurate information—helping them deliver consistent, empathetic, and high-quality support.

Intelligent Data Engineering Agent (iDEA)

An AI-powered accelerator that transforms how enterprises engineer, manage, and consume data on the Databricks Lakehouse. Built for both Data Engineers and Business Users, iDEA provides a unified conversational interface that bridges technical precision with business agility. iDEA automates every stage of the data product journey from ingestion, transformation, quality validation, and governance to discovery, analytics, and visualization. By understanding natural language intent, iDEA intelligently orchestrates workflows, enforces compliance, and delivers actionable insights instantly, empowering organizations to automate the complete Data Product Lifecycle end-to-end.

Augmented Data Quality (ADQ)

Powered by Generative AI, ADQ transforms manual, reactive data quality processes into proactive trust. Its advanced "Agentic Architecture" automatically profiles data, enriches metadata, and recommends complex DQ rules in minutes. ADQ moves beyond simple checks to perform advanced anomaly detection, identifying business-centric microsegments and flagging outliers with natural language explanations. This framework saves > ~60% in manual effort, building a new foundation of data trust and reimagining data governance.

Financial Advisor Assistant

The Financial Advisor Assistant is a GenAI-powered solution designed to address manual, time-consuming investment research. Trained on financials, market signals, and sentiment data, it empowers investors to make faster, data-backed decisions across sectors and portfolios. The platform delivers Comprehensive Market Intelligence with real-time updates on indices like NASDAQ and NIFTY50. Its GenAI-driven insights uniquely merge sentiment analysis with forecast modeling to assess market impact. Additionally, the assistant features customer research tools for generating detailed company reports and a News & Insights Feed equipped with sentiment indicators to visualize potential portfolio impacts across varying market conditions.

Customer Stories

Delivering on Mead Johnson’s Promise of Science-based Pediatric Nutrition Through SAP Data Modernization & AI

Mead Johnson Nutrition (MJN) is a leading global provider of pediatric nutrition products, with a legacy of over a century in developing science-based formulas for infants and children.

Enabling Easier Data Consumption and Improving Data Lake Adoption for a Fortune 500 Logistics Service Provider

The client had multiple data sources feeding into their data lake but the data dictionary and understanding of data lineage was missing. They didn’t have a silver layer having clean and standardized data before moving into the data lake. Besides, the performance of Databricks and Power BI was not good. All of these led to an incomplete road map for data lake adoption. The client wanted our help in cleaning the data from the raw/bronze layer and move it to the silver layer from where the data can be pulled by the data science and analytics team.

Delivering Real-Time Operational Insights for PTP with Databricks Lakehouse

Pelabuhan Tanjung Pelepas (PTP) reached out to Tiger Analytics to modernize their data ecosystem using a Databricks-powered data lakehouse, creating a single source of truth across logistics operations. The solution unified data from over 10 sources, enabled real-time analytics, and enhanced decision-making in key areas like operations and finance. With improved data governance and scalable processing, PTP reduced report generation time from hours to minutes and laid the foundation for advanced ML use cases, driving greater efficiency and strategic growth.