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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

Why traditional bottom-up data warehouse projects so often deliver compromised platforms — and how a top-down, action-oriented approach changes the outcome.
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

Successful data projects start by forgetting about the data. Begin with business goals and the decisions that drive them, and let data follow the insight.
Insight Discovery (part 3) – Defining Actionable Insights

Insight Discovery (part 3) – Defining Actionable Insights

James Broome

Define actionable insights by starting with a specific action, then identifying the questions, evidence and feedback loops that turn data into business value.
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

Capture actionable insights through workshops, build a delivery backlog, and learn why cloud analytics success ultimately comes down to people, not technology.