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Accelerate your Data Analytics and AI Initiatives
Unleash Data Synergy by partnering with Tiger Analytics and Databricks
Unleash Data Synergy by partnering with Tiger Analytics and Databricks
Across all industries, organizations utilize data science and machine learning (DS/ML) to expedite expansion, enhance predictive capabilities, and elevate customer interactions, leading to overall advancements and Data Excellence.
Tiger Analytics partnership with Databricks is a collaboration that brings together cutting-edge capabilities to empower enterprises in solving complex problems and accelerating solutions for today’s dynamic world and future challenges.
Harness the power of Databricks Lakehouse Platform harmoniously fused with Tiger Analytics’ expertise in advanced analytics and AI/ML. Enable real-time processing and analysis of immense datasets with centralized governance, simplify data streaming, supercharge your analytical and operational workloads, automate infra scaling, and seamlessly integrate data engineering, data science, and business analytics by eradicating data silos to maximize performance gains and reduce costs & complexity.
Across all industries, organizations utilize data science and machine learning (DS/ML) to expedite expansion, enhance predictive capabilities, and elevate customer interactions, leading to overall advancements and Data Excellence.
Tiger Analytics partnership with Databricks is a collaboration that brings together cutting-edge capabilities to empower enterprises in solving complex problems and accelerating solutions for today’s dynamic world and future challenges. Read More
Harness the power of Databricks Lakehouse Platform harmoniously fused with Tiger Analytics’ expertise in advanced analytics and AI/ML. Enable real-time processing and analysis of immense datasets with centralized governance, simplify data streaming, supercharge your analytical and operational workloads, automate infra scaling, and seamlessly integrate data engineering, data science, and business analytics by eradicating data silos to maximize performance gains and reduce costs & complexity.
Implement a modern data platform with Tiger’s expertise in data ingestion from disparate sources, data processing and building Raw, Processed & Prepared layer for faster consumption leveraging Delta Lake, Unity Catalog as part of Tiger Data Fabric Accelerator
Embark on a successful data modernization journey with Tiger’s Migration competency with dedicated in-house accelerators that enhances data accessibility, improve data quality, and enable data-driven decision-making. Utilize Databricks Autoloader to seamlessly migrate data from disparate legacy subsystems into unified Databricks Lakehouse platform.
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 solutions and accelerators like TigerML enable you to enhance agility, reliability, and cost- effectiveness in delivering business value.
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.
Accelerator for Implementing Modern Lakehouse leveraging Databricks and the underlying cloud in a highly scalable manner with powerful Governance & Automation Capabilities at its core
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.
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 0 reporting for
optimization.
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.
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