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Star Schemas are fundamental to unleashing value from data in Microsoft Fabric

Star Schemas are fundamental to unleashing value from data in Microsoft Fabric

Barry Smart

Ralph Kimble's 1996 Star Schema principles still apply in Cloud Native Analytics.
Adopt A Product Mindset To Maximise Value From Microsoft Fabric

Adopt A Product Mindset To Maximise Value From Microsoft Fabric

Barry Smart

In this post I describe how adopting a product mindset will help you to extract maximum value from Microsoft Fabric.
Exploring Strategies Enabled By Microsoft Fabric

Exploring Strategies Enabled By Microsoft Fabric

Barry Smart

Explore building situational awareness and leveraging strategic opportunities with Microsoft Fabric in this concise overview.
Developing a Data Mesh Inspired Vision Using Microsoft Fabric

Developing a Data Mesh Inspired Vision Using Microsoft Fabric

Barry Smart

Explore Microsoft Fabric, inspired by Data Mesh, for a data-driven strategy. Learn to approach a Data Mesh vision using this powerful tool.
How Does Microsoft Fabric Measure Up To Data Mesh?

How Does Microsoft Fabric Measure Up To Data Mesh?

Barry Smart

Explore Data Mesh's influence on Microsoft Fabric, addressing gaps in data product marketplace, standards, master data management, and governance.
Microsoft Fabric Is A Socio-Technical Endeavour

Microsoft Fabric Is A Socio-Technical Endeavour

Barry Smart

Creating a successful organisation-wide data and analytics platform isn't just about architecture, schemas and semantic models. It's also about culture, organisational design and people. This blog explores the socio-technical nature of data and analytics and how this should influence your approach to adoption of Microsoft Fabric.
Azure Synapse Analytics versus Microsoft Fabric: A Side by Side Comparison

Azure Synapse Analytics versus Microsoft Fabric: A Side by Side Comparison

Barry Smart

In this Microsoft Fabric vs Synapse comparison we examine how features map from Azure Synapse to Fabric.
Data validation in Python: a look into Pandera and Great Expectations

Data validation in Python: a look into Pandera and Great Expectations

Liam Mooney

Implement Python data validation with Pandera & Great Expectations in this comparison of their features and use cases.
How to setup Python, PyEnv & Poetry on Windows

How to setup Python, PyEnv & Poetry on Windows

James Dawson

Explore using Python virtual environments & Poetry on Windows for smoother workflows, with a script & guide to enhance your dependency management experience.
How To Implement Continuous Deployment of Python Packages with GitHub Actions

How To Implement Continuous Deployment of Python Packages with GitHub Actions

Liam Mooney

Discover using GitHub Actions for auto-updates to Python packages on PyPI, assessing its role in Continuous Deployment.
Customizing Lake Databases in Azure Synapse Analytics

Customizing Lake Databases in Azure Synapse Analytics

Ed Freeman

Explore Custom Objects in Lake Databases for user-friendly column names, calculated columns, and pre-defined queries in Azure Synapse Analytics.
How to create a semantic model using Synapse Analytics Database Templates

How to create a semantic model using Synapse Analytics Database Templates

Barry Smart

Explore Azure Synapse Analytics Database Templates and learn to create semantic models in this 2nd blog of the series.
Continuous Integration with GitHub Actions

Continuous Integration with GitHub Actions

Liam Mooney

This post gives an overview of Continuous Integrations and shows how you can implement it with GitHub Actions, with an accompanying example Python project
How to apply behaviour driven development to data and analytics projects

How to apply behaviour driven development to data and analytics projects

Barry Smart

In this blog we demonstrate how the Gherkin specification can be adapted to enable BDD to be applied to data engineering use cases.
What is the Shared Metadata Model in Azure Synapse Analytics, and why should I use it?

What is the Shared Metadata Model in Azure Synapse Analytics, and why should I use it?

Ed Freeman

Explore Azure Synapse's 'Shared Metadata Model' feature. Learn how it syncs Spark tables with SQL Serverless, its benefits, and tradeoffs.
Extract insights from tag lists using Python Pandas and Power BI

Extract insights from tag lists using Python Pandas and Power BI

Barry Smart

Discover how to extract insights from spreadsheets and CSV files using Pandas and Power BI in this blog post.
Introduction to Containers and Docker

Introduction to Containers and Docker

Liam Mooney

Explore containerisation & Docker for app development & deployment. Learn to create containerised applications with examples in this intro guide.
How to test Azure Synapse notebooks

How to test Azure Synapse notebooks

James Broome

Explore data with Azure Synapse's interactive Spark notebooks, integrated with Pipelines & monitoring tools. Learn how to add tests for business rule validation.
How Azure Synapse unifies your development experience

How Azure Synapse unifies your development experience

Ian Griffiths

Modern analytics requires a multi-faceted approach, which can cause integration headaches. Azure Synapse's Swiss army knife approach can remove a lot of friction.
How to use SQL Notebooks to access Azure Synapse SQL Pools & SQL on demand

How to use SQL Notebooks to access Azure Synapse SQL Pools & SQL on demand

Howard van Rooijen

Wishing Azure Synapse Analytics had support for SQL notebooks? Fear not, it's easy to take advantage rich interactive notebooks for SQL Pools and SQL on Demand.
Azure Synapse for C# Developers: 5 things you need to know

Azure Synapse for C# Developers: 5 things you need to know

James Broome

Did you know that Azure Synapse has great support for .NET and #csharp? Learning new languages is often a barrier to digital transformation, being able to use existing people, skills, tools and engineering disciplines can be a massive advantage.
Import and export notebooks in Databricks

Import and export notebooks in Databricks

Ed Freeman

Learn to import/export notebooks in Databricks workspaces manually or programmatically, and transfer content between workspaces efficiently.
Azure Databricks CLI "Error: JSONDecodeError: Expecting property name enclosed in double quotes:..."

Azure Databricks CLI "Error: JSONDecodeError: Expecting property name enclosed in double quotes:..."

Ed Freeman

Explore solutions for JsonDecodeError in Databricks CLI & Clusters. Learn how pre-built CLIs/SDKs simplify requests & authentication in REST APIs.
Using Databricks Notebooks to run an ETL process

Using Databricks Notebooks to run an ETL process

Carmel Eve

Explore data analysis & ETL with Databricks Notebooks on Azure. Utilize Spark's unified analytics engine for big data & ML, and integrate with ADF pipelines.
Using Python inside SQL Server

Using Python inside SQL Server

Ed Freeman

Learn to use SQL Server's Python integration for efficient data handling. Eliminate clunky transfers and easily operationalize Python models/scripts.