This blog will take you through all of the information, updates and study tips you’ll need to pass the Databricks Certified Data Analyst Associate exam.
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In the realm of data visualisation and analytics, Tableau and Power BI have emerged as two dominant players. These powerful business intelligence tools offer us plenty of features to transform raw data into actionable insights - but which should you choose?
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This blog will walk you through the entire data lifecycle of ingesting data from SharePoint and Azure Blob Storage, through the lakehouse pattern, and finally to the reporting stage - all using Microsoft Fabric.
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A common challenge faced by our clients is that knowing the well-architected framework is not the same as being able to deliver products to this standard. The step-up in technical maturity can be daunting for businesses to achieve, which is why we developed Hydr8.
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It’s really easy to get started with Microsoft Fabric. We can ingest data, transform it, and have it surfaced in Power BI in no time without creating a single Azure resource. That’s the easy part but how do we turn that into a robust, logical architecture that will give us a successful Analytics Platform?
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The blog post explores the potential of large language models (LLMs), like OpenAI's GPT-4, in enhancing Business Event Analysis & Modeling (BEAM) sessions. The fusion of BEAM and LLMs can revolutionize the design of data warehousing and business intelligence by providing scalability, accessibility, consistency, automatic documentation, and rapid prototyping.
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With the advent of Fabric, many organisations with existing lakehouse implementations in Azure are wondering what changes Fabric will herald for them. Do they continue with their existing lakehouse implementation and design, or do they migrate entirely to Fabric?
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Every year on June 20th, the world comes together to recognise World Refugee Day. This day is dedicated to raising awareness about the plight of refugees worldwide and honouring their strength and resilience in the face of adversity. Being within data it is important for us to understand the global refugee crisis and use our skills to help improve the lives of those affected.
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In the data engineering field, we must ensure that large datasets are compressed efficiently to save storage space and reduce costs, but we also need to maintain strong query performance. This can be balanced by utilising the VertiParq engine and Delta in Microsoft Fabric.
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If you have had a play around with Microsoft Fabric you will have seen that there are lots of different ways to get to your end goal. One of the most important decisions to make is whether to use a Lakehouse or Warehouse?
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As data engineers, we face many challenges daily. Data is often distributed across many different sources, and frequently in a wide range of file types with varying levels of data quality. This is where OneLake comes in, described as the OneDrive for data.
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Fabric is Microsoft’s brand-new SaaS analytics platform just announced at their Build conference. We think there are some great features in Fabric so in this blog post we want to highlight our top 10.
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Fabric is Microsoft’s shiny new all-encompassing Software-as-a-Service (SaaS) analytics platform. That means Fabric is your one-stop-shop for your full data platform, from ingesting source data through to data visualisation across each persona, from Data Engineer to Power BI user and everyone in between.
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Recently, I had the opportunity to explore the Databricks SQL extension for VSCode, and I was thoroughly impressed. With its user-friendly interface, robust features, and seamless integration with Databricks, this extension is the ideal solution for querying your Databricks Lakehouse outside of the Databricks ecosystem.
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Databricks SQL is a powerful tool for querying and analysing data in Databricks Lakehouse. It empowers data analysts and engineers that are familiar with SQL, to extract insights without the need for complex code, thereby streamlining and speeding up the data analysis process.
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Medallion Architecture is a system for logically organising data within a Data Lakehouse. A standard medallion architecture consists of 3 main layers, in order: Bronze, Silver and Gold. The increasing quality of precious metal in the names is no accident and represents an increasing level of structure and validation when moving through the layers.
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