| Author | Message | ||
     Gandhiguevara Legend Username: Gandhiguevara Post Number: 44387 Registered: 10-2009 Posted From: 142.136.143.47 Rating: N/A |
DBA la gurinchi kaadhu yee bukku | ||
| Rudraksha Side Hero Username: Rudraksha Post Number: 2919 Registered: 07-2012 Posted From: 70.181.57.58 Rating: N/A |
dba's ki manchi billing untadi, so this book might help  | ||
| Gandhiguevara Legend Username: Gandhiguevara Post Number: 44371 Registered: 10-2009 Posted From: 142.136.143.47 Rating: N/A |
Why have powerful tools if you aren't asking the right questions? Good questions trump shiny tools, but our community has done little to improve how we train people in the "soft side" of data science. We will show how to borrow ideas from design, the humanities, consulting practices to structure problems and improve the questions we ask of our data. | ||
| Gandhiguevara Legend Username: Gandhiguevara Post Number: 44370 Registered: 10-2009 Posted From: 142.136.143.47 Rating: N/A |
Bullets: Lot to learn from other disciplines Mental models make our lives easier and our work better.We should invest time in learning them From Data to insights through 'Arguments'...Arguments are a deep part of working with data Short read....94 pages | ||
| Gandhiguevara Legend Username: Gandhiguevara Post Number: 44369 Registered: 10-2009 Posted From: 142.136.143.47 Rating: N/A |
By Max Shron Many analysts are too concerned with tools and techniques for cleansing, modeling, and visualizing datasets and not concerned enough with asking the right questions. In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how, through an often-overlooked set of analytical skills. Thinking with Data helps you learn techniques for turning data into knowledge you can use. You’ll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You’ll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved. Learn a framework for scoping data projects Understand how to pin down the details of an idea, receive feedback, and begin prototyping Use the tools of arguments to ask good questions, build projects in stages, and communicate results Explore data-specific patterns of reasoning and learn how to build more useful arguments Delve into causal reasoning and learn how it permeates data work Put everything together, using extended examples to see the method of full problem thinking in action |
