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A six-part framework for successful data projects — from defining actionable insights to delivering them incrementally with data pipelines.

Insight Discovery (part 1) – why do data projects often fail?

Insight Discovery (part 1) – why do data projects often fail?

James Broome

Discover a unique, action-oriented approach to data projects for maximum impact. Learn how to synergize with platforms like Azure Synapse for fast delivery.
Insight Discovery (part 2) – successful data projects start by forgetting about the data

Insight Discovery (part 2) – successful data projects start by forgetting about the data

James Broome

Many data projects fail to deliver the impact they should for a simple reason – they focus on the data. This series of posts explains a different way of thinking that will set up your data & analytics projects for success. Using an iterative, action-oriented, insight discovery process, it demonstrates tools and techniques that will help you to identify, define and prioritize requirements in your own projects so that they deliver maximum value. It also explores the synergy with modern cloud analytics platforms like Azure Synapse, explaining how the process and the architecture actively support each other for fast, impactful delivery.
Insight Discovery (part 3) – Defining Actionable Insights

Insight Discovery (part 3) – Defining Actionable Insights

James Broome

Discover a unique, action-oriented approach to data projects for maximum impact. Learn how to synergize with platforms like Azure Synapse for fast delivery.
Insight Discovery (part 4) – Data projects should have a backlog

Insight Discovery (part 4) – Data projects should have a backlog

James Broome

This series focuses on maximizing data projects' impact via an iterative, insight discovery process, and synergy with cloud platforms like Azure Synapse.
Insight Discovery (part 5) – Deliver insights incrementally with data pipelines

Insight Discovery (part 5) – Deliver insights incrementally with data pipelines

James Broome

Traditional bottom-up data modelling leads to platforms that are hard to evolve and don't meet business needs. Data pipelines let you deliver thin, focused slices of value from source to insight.
Insight Discovery (part 6) – How to define business requirements for a successful cloud data & analytics project

Insight Discovery (part 6) – How to define business requirements for a successful cloud data & analytics project

James Broome

Many data projects fail to deliver the impact they should for a simple reason – they focus on the data. This series of posts explains a different way of thinking that will set up your data & analytics projects for success. Using an iterative, action-oriented, insight discovery process, it demonstrates tools and techniques that will help you to identify, define and prioritize requirements in your own projects so that they deliver maximum value. It also explores the synergy with modern cloud analytics platforms like Azure Synapse, explaining how the process and the architecture actively support each other for fast, impactful delivery.