Blog Tags: Business Intelligence
What is Data Observability Used For?
Learn how Data Observability can enhance your business by detecting crucial data anomalies early. Explore its applications in improving data quality and model reliability, and discover Tiger Analytics’ solution. Understand why this technology is attracting major investments and how it can enhance your operational efficiency and reduce costs.
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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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A Comprehensive Guide to Pricing and Licensing on Microsoft Fabric
This comprehensive guide explores Microsoft Fabric’s pricing strategies, including capacity tiers, SKUs, and tenant hierarchy, helping organizations optimize their data management costs. It breaks down the differences between reserved and pay-as-you-go models, explaining Capacity Units (CUs) and providing detailed pricing information. By understanding these pricing intricacies, businesses can make informed decisions to fully leverage their data across various functions, leading to more efficient operations and better customer experiences.
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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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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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Why Self-Service BI is Important in an Agile Business Scenario
Self-service BI empowers business users to independently query, visualize, and analyze data, fostering a data-driven culture through accessible learning resources. Read how organizations can harness it towards informed decision-making and collaboration among multiple stakeholders, ultimately enhancing communication channels and data utilization.
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Achieving IPL Fantasy Glory with Data-Backed Insights and Strategies
A cricket enthusiast shares insights on building a winning IPL fantasy team. From data analysis tools such as Kaggle and Howstat to tips on player selection, venue analysis, and strategic gameplay, this guide emphasizes the role of statistics in making informed choices, ultimately highlighting the unpredictability of the sport.
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Maximizing Efficiency: Redefining Predictive Maintenance in Manufacturing with Digital Twins
Tiger Analytics leverages ML-powered digital twins for predictive maintenance in manufacturing. By integrating sensor data and other inputs, we enable anomaly detection, forecasting, and operational insights. Our modular approach ensures scalability and self-sustainability, yielding cost-effective and efficient solutions.
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