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Azure Synapse

Whether you're running Azure Synapse or planning your migration to Microsoft Fabric, our free call allows you to ask our experts as many questions as you like in 60 mins.

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Azure Synapse Analytics is Microsoft's mature PaaS and Serverless Data Lake Platform. It's a Swiss Army Knife for data teams - with all the tools you need run a modern data platform.

Discovery

Discovery

Jumpstart your Synapse adoption with our battle tested process
Proof of Concept

Proof of Concept

Build the business case by implementing a scenario
Blueprints

Blueprints

De-risk your project and accelerate time to value
Delivery Squads

Delivery Squads

Team-per-week working to a deadline or budget
DataOps

DataOps

Improve the quality, speed, and security of data delivery
Data Science

Data Science

Iteration based innovation where new knowledge is always gained
Training

Training

Upskill your team with bespoke training tailored to your needs
Mentoring

Mentoring

Weekly "office hours" to help solve problems & make decisions
Skills Assessment

Skills Assessment

Understand your capabilities to plan for modernisation success

A new data platform for Ascot Lloyd

From strategy to support, delivering a modern data platform to enable growth.

Read the case study

We created talks covering every aspect of building Azure Synapse solutions.

We were featured on the Microsoft Mechanics show to demo how we use SQL On Demand, and have recorded many talks we've given at conferences and user groups.

Watch on YouTube

Azure Synapse Learning Paths

With 30+ in-depth blog posts, our team covers every aspect of Azure Synapse Analytics — from architecture and SQL Serverless to notebooks and pipeline automation.

All Synapse posts

Latest Synapse blogs

Scaling API Ingestion with the Queue-of-Work Pattern

Scaling API Ingestion with the Queue-of-Work Pattern

Jonathan George

The queue-of-work pattern enables massive parallelism for API ingestion by breaking large jobs into thousands of independent work items processed by concurrent workers. This approach reduced data ingestion time for our use case from 15 hours to under 2 hours while providing automatic retry handling and fault tolerance at a fraction of the cost of traditional orchestration tools.
How to access multi-select choice column choice labels from Azure Synapse Link for Dataverse with PySpark or SQL

How to access multi-select choice column choice labels from Azure Synapse Link for Dataverse with PySpark or SQL

Jessica Hill

Learn how to access multi-select choice column choice labels from Azure Synapse Link for Dataverse using PySpark or SQL.
Introduction to Python Logging in Synapse Notebooks

Introduction to Python Logging in Synapse Notebooks

Jonathan George

The first step on the road to implementing observability in your Python notebooks is basic logging. In this post, we look at how you can use Python's built in logging inside a Synapse notebook.
How to access choice labels from Azure Synapse Link for Dataverse with SQL

How to access choice labels from Azure Synapse Link for Dataverse with SQL

Jessica Hill

Learn how to access the choice labels from Azure Synapse Link for Dataverse using T-SQL through SQL Serverless and by using Spark SQL in a Synapse Notebook.
How to access choice labels from Azure Synapse Link for Dataverse with PySpark

How to access choice labels from Azure Synapse Link for Dataverse with PySpark

Jessica Hill

Learn how to access the choice labels from Azure Synapse Link for Dataverse using PySpark.
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 Kimball's 1996 Star Schema principles still underpin modern cloud-native analytics — why dimensional modelling unlocks value from data in Microsoft Fabric.

From SMEs to global enterprises, we help organisations harness the full potential of their data.

We pride ourselves on our customer relationships. Here's what they had to say about us.

Often website quotes are full of token platitudes, however, hand on heart, endjin have been the most consistent, high quality partners I have ever used. One of the key highlights was help in designing an Azure solution to help process over 1.5B rows of data to display to the user in less then 3 seconds, with the help of endjin we had a solution in under 12 weeks.

It's the unique blend of commercial acumen, strategy awareness, deep technical ability and the willingness to call bullshit/not tolerate it, that makes endjin so special.

Endjin's experience & processes enabled us to move on from simply collecting data, to asking business questions, and gaining valuable insights, which allowed us to focus on the right business decisions.

We worked with Endjin as part of an ambitious project around consolidating and migrating data to a new stack and new processes. Their Microsoft Azure platform expertise, deep understanding of data strategy and management best practice and exemplary approach to insights completely changed how we thought about data. Our team is capable of things we would not have been able to do without their support.

At Juniper we had the opportunity to take a fresh look at our data strategy, and how we could help our customers get better value from the data they entrust us with. Endjin helped us shift how we thought about data, introduced us to end to end processes for establishing and delivering requirements, and helped us put the baseline technology platform in place along with some exemplar implementations. Endjin upskilled our team so we could stand alone on completion of the engagement.

We needed a quick answer about whether something was even possible with the data available. Endjin helped us to focus our hypothesis, then used Machine Learning experiments to cut the discovery down from months to weeks.

Bang for buck, endjin are the best value for money you can spend.

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Chat

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Call

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Email

Email

Or you can use good old fashioned email to drop us a line, hello@endjin.com