Blog Tags: Business Intelligence
How to Simplify Data Profiling and Management with Snowpark and Streamlit
Learn why data quality is one of the most overlooked aspects of data management. While all models need good quality data to generate useful insights and patterns, data quality is especially important. In this blog, we explore how data profiling can help you understand your data quality. Discover how Tiger Analytics leverages Snowpark and Streamlit to simplify data profiling and management.
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Implementing Context Graphs: A 5-Point Framework for Transformative Business Insights
This comprehensive guide outlines three phases: establishing a Knowledge Graph, developing a Connected Context Graph, and integrating AI for auto-answers. Learn how this framework enables businesses to connect data points, discover patterns, and optimize processes. The article also presents a detailed roadmap for graph implementation and discusses the integration of Large Language Models with Knowledge Graphs.
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Connected Context: Introducing Product Knowledge Graphs for Smarter Business Decisions
Explore how Product Knowledge Graphs, powered by Neo4j, are reshaping data analytics and decision-making in complex business environments. This article introduces the concept of Connected Context and illustrates how businesses can harness graph technology to gain deeper insights, improve predictive analytics, and drive smarter strategies across various functions.
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Solving Merchant Identity Extraction in Finance: Snowpark’s Data Engineering Solution
Learn how a fintech leader solved merchant identification challenges using Snowpark and local testing. This case study showcases Tiger Analytics’ approach to complex data transformations, automated testing, and efficient development in financial data processing. Discover how these solutions enhanced fraud detection and revenue potential.
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Advanced Data Strategies in Power BI: A Guide to Integrating Custom Partitions with Incremental Refresh
Explore advanced data management strategies in Power BI through a detailed examination of integrating Custom Partitions with Incremental Refresh to efficiently handle large datasets. Key benefits such as improved query performance, more efficient data refresh, and better data organization are outlined, along with a practical guide on implementing these strategies in Power BI environments.
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Power to the People: How GenAI Empowered Employees are Redefining Workplace Productivity
As GenAI becomes increasingly accessible, employees are transforming into AI-empowered superheroes. Organizations must focus on individualized rollouts, research tools, expert assistance, and readiness assessment frameworks to harness the full potential of GenAI and redefine workplace productivity.
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Tiger’s Snowpark-Based Framework for Snowflake: Illuminating the Path to Efficient Data Ingestion
In the era of AI and machine learning, efficient data ingestion is crucial for organizations to harness the full potential of their data assets. Tiger’s Snowpark-based framework addresses the limitations of Snowflake’s native data ingestion methods, offering a highly customizable and metadata-driven approach that ensures data quality, observability, and seamless transformation.
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Migrating from Legacy Systems to Snowflake: Simplifying Excel Data Migration with Snowpark Python
Discover how Snowpark Python streamlines the process of migrating complex Excel data to Snowflake, eliminating the need for external ETL tools and ensuring data accuracy.
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Empowering BI through GenAI: How to address data-to-insights’ biggest bottlenecks
Explore how integrating generative AI (GenAI) and natural language processing (NLP) into business intelligence empowers organizations to unlock insights from data. GenAI addresses key bottlenecks: enabling personalized insights tailored to user roles, streamlining dashboard development, and facilitating seamless data updates. Solutions like Tiger Analytics’ Insights Pro leverage AI to democratize data accessibility, automate pattern discovery, and drive data-driven decision-making across industries.
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A Complete Guide to Enabling SAP Data Analytics on Azure Databricks
Uncover how SAP data analytics on Azure Databricks empowers organizations by optimizing data processing and analysis and offering a scalable solution for efficient decision-making.
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Patient Services: Pharma’s Answer to Supporting Patients with Rare Diseases
From ‘drug providers’ to becoming a ‘care partner’ and creating a powerful support system. Read how some Pharma companies are utilizing AI and ML to offer patients of rare diseases and their caregivers much-needed support during their very difficult patient journey
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Building Data Engineering Solutions: A Step-by-Step Guide with AWS
In this article, delve into the intricacies of an AWS-based Analytics pipeline. Learn to apply this design thinking to tackle similar challenges you might encounter and in order to streamline data workflows.
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