How to shape business metrics and stories into Dashboards

Are business Dashboards easy to design? You tell me: you’ll need to draw a clear picture of the most valuable information about a business subject, in less than a minute. Of course, it should also be visually appealing, interactive, quick, and self-explanatory, what else?!

Introduction

Although for many designers the Dashboards conception and development are intuitive activities, especially since the explosion of friendly tools and self-service BI, I believe that some guidelines and a methodology are necessary. To make a difference in the field we need to define our own style, our signature.

I have constantly been trying to “discipline” myself…


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In this series we look at all sorts of SQL features, by doing examples from real world scenarios.

Content:

· Intro
·
Source data & DIY setup
·
Quiz
·
Concepts explained
1. Exponential Row Generator : Cross Join
2. Unique data value generation
·
Solution

Intro

Sometimes we need to generate big amounts of data with different data types, to help us with the development, to test, debug, tune the performance of our queries, data processes, algorithm.

In this post I want to share a simple way to do it, starting from a simple and little data set.

Source data & DIY setup

If you want to try it yourself, here is the script to build from scratch the table, and…


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In this post I want to share with you a way to get started with Tableau, by showing the 3 mains steps necessary for any data visualization.

I recommend getting and installing the free version of Tableau (we’ll this as well), to practice the 3 steps yourself.

Content:

· Getting Tableau Public and a data set
Getting Tableau Public
Getting the source data set
·
Getting the source data set
·
Step 1 — Connecting the data
·
Step 2 — Editing the data
·
Step 3 — Visualizing the data
·
In a nutshell..

Getting Tableau Public and a data set

If you want…


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In this series we look at all sorts of SQL features, by doing examples from real world scenarios.

Content:

· Intro
·
Data
·
Quiz
·
Concepts explained
·
Solution

1. Intro

Dealing with dates is not always immediate. There are cases, for instance when we prepare our data for a time series visualization in a dashboard, in which we need to adapt our dates so that overlapping time periods are merged.

In this post we use the concepts of CTEs and subqueries to deal with date merging.

2. Data

We consider the following table “TimePeriods”, in which each row has two dates, representing the start and end of periods.

Notice that some periods are overlapping:


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In this series we look at all sorts of SQL features, by doing examples from real world scenarios.

Content:

· Intro..
·
Source data & DIY setup..
·
Quiz..
·
Concepts explained..
·
Solution..

Intro..

Ranking values is a very common task. By ranking we make our SQL query doing useful things

  • finding the Top N, or Bottom N values
  • handling duplicate rows, or values
  • assigning unique rows identifiers
  • calculating more advanced derived values
  • .. so much more

In this post we will look at some different ways to define a rank in SQL., …


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How human perception drives Dashboard designers

Design is one of the essential factors of a successful dashboard. At least as much as its content and the quality of the underlying data. Whereas the dashboard’s content and data quality are clearly measurable, design is more difficult to evaluate objectively, but fortunately we have some guidelines.

Design can cause weakness

Why boring dashboard are boring? Why engaging dashboards are engaging? Dashboard designers need to know what can push a data visualization to rank low or high in the user’s appreciation range.

Some empiric but effective ideas that can give Dashboard design hints are the “Conventional” and “Gestalt” principles.

In this story I…


Image from Patrick Tomasso edited by Author

Tableau recently released a new feature “Quick LOD” that should make it easier to build LOD calculations. As an intensive LOD user, I want to try this feature out and share my thoughts with you.

Content:

· Quick reminder about LOD expressions
·
Testing "Quick LOD"
·
Testing Outcomes
·
In a nutshell…

Quick reminder about LOD expressions

When we build a data visualization we often need to dispose of multiple aggregation levels of the same measure at the same time, by using LOD calculations.

If we make a conceptual parallel with SQL, LOD expressions allow defining more than one different GROUP BY clauses in…


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Tips and Tricks

An effective approach to analyse and understand complex SQL

In this story I want to share a possible way to tackle the tricky understanding of complex (or complicated) SQL queries. When we need to handle some existing SQL code, maybe non-documented, poorly written, or uses SQL versions that we don’t master just yet, it can be frustrating to deal with it.

Whatever thing we need to do with it, just running it as it is, using it in a Data Science or Analytics process, modifying it, etc., in any case we need to understand it.

Content:

· What can make SQL tricky
· Breaking SQL complexity
1. Improve…


New data specializations always offer opportunities to the ones who can see them coming.

In this 2-parts story, I want to share some ideas about Self-Service Analytics.

In Part-1 I give an overview of what SSA is, explain the opportunities it offers to Data passionates, and walk through the subjects one needs to learn or improve to work in Self-Service Analytics.

In Part-2 I look in more detail at the needed skill sets, toolkits, and possible entry points to plan the SSA learning.

Revolutionary SSA

I call “Self-Service Analytics” the stack techniques and skills that allow anyone (not only technical users) in…


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This divulgation series aims to explain different topics about Data subjects, in a simple but effective way.

Introduction

In general, a data model is a representation of how data is organized into database tables. I know, that’s not a rigorous/academic definition, but my only goal here is to be clear. For a given collection of data, representing a Business Process, there is a number of possibles ways to organize store them: do we store all data in 1 big table? Or in 2, in 100,.. ? It depends. For any Data Analytics- driven subject, ranging from classic Business Intelligence to the wildest Data Science applications, a very comfortable and efficient way is using Dimensional Modeling.

The topics will…

Maw Ferrari

Data freelance. Data literacy evangelist. Math & music hobbyist.

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