Business Analysis

A management book for product development leaders tired of "on track" reports that turn out to mean nothing. It shows how to make "better" explicit enough to design against, spend against, and be proven wrong by.

Eighteen practitioner-oriented technical notes covering the full arc of early-stage company finance, from the financing gap through to exit planning.

You want to analyse, understand and capture the subject matter of a domain, typically because you want to build a software system in that domain? You're looking for abstractions to describe and ultimately execute said subject matter? Then this book is for you: it's chock-full of experience and practices for tackling this challenge.

Hands-on and written in jupyter notebook....feel the heat!

Most data modelling books teach you the craft. This one teaches you the reality. Seven chapters of honest, practical guidance from real project experience — covering conceptual modelling, governance, enterprise challenges, and the human side of data work that nobody else writes about.

In Multivariate Analysis – The Simplest Guide in the Universe, guides you through the building blocks of multivariate analysis towards discovering the relationships within your data.Here, you’ll discover the most used multivariate analysis tests – and learn how to choose them correctly.

STOP REACTING TO NOISE. START RESPONDING TO SIGNALS.  Measures of Success shows business leaders how. Buy the eBook here and receive exclusive digital extras

I numeri ti dicono cosa succede. Non ti dicono perché. La tua organizzazione misura attività — conferenze fatte, partecipanti registrati, borse erogate — ma non ha mai definito quale cambiamento vuole generare nel mondo. "Theory of Change, the Right Way" è il metodo pratico per partire dal futuro che vuoi creare e lavorare a ritroso fino alle azioni di oggi. Con il backwards mapping, le assumption nascoste e le sentinel metrics, imparerai a progettare impatto misurabile invece di sperare che le cose migliorino. Training from the Back of the Room: impari facendo, non ascoltando.

Your manager calls you into a meeting. Everyone is cheerful. The Head of Sales is there. “We heard AI is really useful for boosting productivity. We’d love to explore how it can help us in Sales.” Your manager agrees. “This is the perfect pilot. Please give us a concept until next week so we can see what we can do.”The follow-up arrives quickly. Sales is overloaded. Everyone is busy serving customers. Nobody has time for a workshop, but they do have Sales.xlsx. That is what you get. The clock is ticking.And then you open Sales.xlsx.You have nothing. No requirements, no workflows, not even a proper data model. What you have is a snapshot of the messy reality Sales is dealing with every day. Customer names, contacts, opportunity values, dates, products, notes, colors that apparently mean something, and a field called Status_Final_2, which tells you enough about its history that asking about Status_Final_1 would probably ruin the afternoon.And then it strikes you: they are not even using the CRM. You do not know why. Nothing you know from IT seems to apply in Sales, and they do not particularly care. They have customers to serve. Whatever happened between the shiny CRM rollout and this spreadsheet happened years ago. Today, Sales.xlsx is the truth.And now, just because AI promises productivity, they are asking for the benefits.How is that even supposed to work?

Hoshin Kanri wird seit Jahrzehnten erfolgreich von Toyota sowie zahlreichen führenden Unternehmen in Japan und den Vereinigten Staaten eingesetzt, um strategische Ziele und Lean-Initiativen nachhaltig umzusetzen.

One issue. One source. One proof question. A cleaner way to move from claim to evidence.

Evaluating a novel and original approach to a problem involves many types or organizational structures, forecasting and communication styles.

Quality Statistics Made Simple! Brainstorming is a conceptualizing process that is well-known for producing a large number of ideas in a short period of time. It serves as a tool for identifying difficulties and causes. This book offers an in-depth guide to the tool.

Move beyond prompt experimentation. Build governed Claude AI workflows for FP&A, forecasting, close, reporting, document review, reconciliation, and finance controls—then practise with 20 hands-on exercises and worked solutions in the included GitHub Companion Pack.

Markets are not static rows. This book shows how to turn fragmented public and private evidence into an answerable, versioned map of who exists, who fits, why now, and who to contact—without hiding uncertainty, provenance, or change.