“Data is a precious thing and will last longer than the systems themselves.” – Tim Berners-Lee Data today powers business decisions,…
The latest in
Data and AI
We are specialist Microsoft partners, building the critical data platforms on Fabric and Azure AI that power business intelligence and drive the next generation of Agentic AI.
Mastering Your Data Management Strategy
“More than 70% of employees have access to data they shouldn’t, and 80% of analysts’ time is wasted just preparing…
Real-Time Data Ingestion 101: A Comprehensive Guide
Whether it’s fraud detection in banking, predictive maintenance in manufacturing, or personalized recommendations in e-commerce, real-time data ingestion plays a…
How to Build an AI-Ready Data Foundation
The rise of large language models (LLMs) has given some businesses the impression that training data is no longer a…
The Data Value Gap: Why Only 32% of Companies Realise
Data is often hailed as the new oil, the lifeblood of modern enterprises, and the key to unlocking competitive advantage….
Automatically Migrating Power BI Premium Capacities to Microsoft Fabric
In early 2024, Microsoft announced the consolidation of purchase options and the retirement of Power BI Premium per capacity SKUs…
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Why AI/ML Projects Fail: A Practical Guide for High-Level Executives
Artificial Intelligence (AI) and Machine Learning (ML) have been hailed as transformative technologies that can unlock new business opportunities, drive operational efficiencies, and generate significant ROI. Despite the hype, a substantial number of AI/ML initiatives fail to see completion or fail to deliver the expected value. For decision-makers, CXOs, and VPs, understanding why these projects…
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Where is Your Organization in the Data Science Hierarchy of Needs?
Introduction In today’s data-driven world, businesses are increasingly relying on data science to gain insights and make informed decisions. However, the application of data science within an organization is not a one-size-fits-all approach. Understanding where your organization stands in the Data Science Hierarchy of Needs is crucial for optimizing processes and making strategic advancements. This…
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Unlocking ROI: How Quality Data Drives AI Success
Investing in artificial intelligence (AI) has become a strategic imperative for many leading organizations. With the promise of transforming industries and delivering unprecedented efficiencies, AI initiatives are attracting significant financial and intellectual capital. However, while the potential of AI is nearly limitless, its success hinges on one critical factor: the quality of the data that…
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Integrating Azure AI Search with Your Azure MySQL Database
Integrating Azure AI Search (formerly known as Cognitive Search) with your Azure MySQL Database can significantly enhance the search capabilities of your applications, making them more efficient and user-friendly. Given that this feature is currently in public preview and can only be accessed through APIs, this guide aims to provide you with a comprehensive, step-by-step…
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GraphRAG 101: A New Dawn in Retrieval Augmented Generation
The field of artificial intelligence is continually evolving, and one of the latest advancements driving innovation is Retrieval Augmented Generation (RAG). By augmenting retrieval processes with the generative power of language models, RAG has promised to revolutionize how we manage, extract, and utilize information. Now, Microsoft has introduced a groundbreaking tool known as GraphRAG—a new…
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Copilot Studio: What is it and How you can use it?
Build powerful chatbots with the security of Microsoft 365 Introduction If you have been keeping up the Generative AI developments, I am sure you have heard of Microsoft Copilot especially if you use Microsoft Products in any part of your workflow (PC or Cloud). Pitched as an LLM-powered assistant that integrates with all your documents…
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Data Mesh – Is it for your organisation?
Progressively maintain extensive infomediaries via extensible niches. Dramatically disseminate standardized metrics after resource-leveling processes. Objectively pursue diverse catalysts for change for interoperable meta-services.
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Developing Technology Strategy and Architecture for Healthcare Providers
Dynamically reinvent market-driven opportunities and ubiquitous interfaces. Energistically fabricate an expanded array of niche markets through robust products. Appropriately implement visionary e-services vis-a-vis strategic web-readiness.
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Accelerating cloud adoption for data analytics in public sector
Progressively maintain extensive infomediaries via extensible niches. Dramatically disseminate standardized metrics after resource-leveling processes. Objectively pursue diverse catalysts for change for interoperable meta-services.
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