9 Key Elements of a Successful Data Strategy for Business Growth

Get the Competitive Edge with Decisively Digital - The Ultimate Guide to Data Strategy
Get the Competitive Edge with Decisively Digital – The Ultimate Guide to Data Strategy

Data is a valuable asset that can give businesses a competitive edge and drive growth in today’s digital age. But without a clear and well-defined data strategy, companies risk missing out on the benefits that data provides. To help your business succeed in the digital world, here’s an overview of nine essential elements of a comprehensive data strategy.

    1. Goals and Objectives: Define specific goals and objectives that the company wants to achieve through its data efforts, such as improving customer experiences or optimizing business processes.
    2. Data Sources: Identify the most valuable data types and determine where they will come from, such as internal transaction or customer data and external market research.
    3. Data Management and Storage: Outline how data will be collected, organized, and stored consistently, accurately, and compliantly, with data management tools and technologies.
    4. Data Analysis and Reporting: Define how data will be analyzed and used to inform business decisions, with data visualization tools, dashboards, and reporting systems.
    5. Data Governance: Establish clear roles and responsibilities for data management, guidelines for data use and access, and ensure ethical and regulatory compliance.
    6. Data-driven Culture: Foster a data-driven culture by providing training and resources for data-driven decision making.
    7. Data Security and Privacy: Ensure data is collected, stored, and used securely and in compliance with privacy regulations.
    8. Data Integration and Interoperability: Define how data will be integrated and shared across systems and platforms.
    9. Data Quality and Accuracy: Ensure data is accurate and up-to-date, with processes for data cleansing and enrichment.

A data strategy is a must-have tool for any company that wants to fully realize the benefits of its data. It provides a clear roadmap for data collection, management, and analysis and helps organizations make better use of their data, drive growth, and succeed in today’s digital world. Get more insights and in-depth information by reading the book Decisively Digital (on Amazon).

Tableau Calculated Field: 20 Essential Tricks for Your Tableau Dashboards – A Comprehensive Guide

Tableau Calculated Field tips: Even more Tableau tricks in these books: “Datenvisualisierung mit Tableau” and “Visual Analytics with Tableau”
Tableau Calculated Field tips: Even more Tableau tricks in these books: “Datenvisualisierung mit Tableau” and “Visual Analytics with Tableau”

Tableau’s Calculated Field feature is at the core of its capabilities, offering powerful data manipulation and insights. In this post, we’ll explore 20 ultimate tricks to elevate your Tableau dashboards with calculated fields. Whether you’re a beginner or an expert, these Tableau Calculated Field tips will unlock the full potential of Tableau.

20 Ultimate Tableau Calculated Field Tricks – Simply Explained

  1. 📊 Summing Based on Conditions
    Calculate the sum of sales for a specific region:
    IF [Region] = "West" THEN SUM([Sales Amount]) END
    Great for targeted analysis!
  2. 🔗 Accessing Related Data
    Grab related product names:
    ATTR([Product Name])
    Simplifies data relationships!
  3. 🧠 Row Context Calculations
    Calculate sales amount per Sales ID:
    {FIXED [Sales ID]: SUM([Sales Amount])}
    Unlock the power of context!
  4. 🏅 Ranking Values
    Rank sales amounts in descending order:
    RANK(SUM([Sales Amount]), 'desc')
    See who’s on top!
  5. 🧮 Safe Division
    Avoid division by zero:
    IF [Total Units] != 0 THEN [Total Sales] / [Total Units] END
    No more errors!
  6. 🔄 Multiple Conditions
    Use CASE for multiple conditions:
    CASE [Rating] WHEN 1 THEN "Poor" WHEN 2 THEN "Average" WHEN 3 THEN "Good" ELSE "Unknown" END
    Keep it clean!
  7. 🚫 Removing Filters
    Exclude filters from a calculation:
    {EXCLUDE [Sales]: SUM([Sales Amount])}
    Take control of your filters!
  8. 🧵 String Aggregation
    Concatenate product names:
    CONCATENATE([Product], ", ")
    String it together!
  9. 📆 Year-Over-Year Comparisons
    Calculate the difference in years:
    DATEDIFF('year', [Date], TODAY())
    Time travel with data! #Tableau #Analytics
  10. 🕳️ Handling Missing Data
    Replace zeros with NULL:
    IF [Sales Amount] = 0 THEN NULL ELSE [Sales Amount] END
    Clean up those blanks!
  11. 🎨 Custom Date Formatting
    Format dates your way:
    DATEPARSE("MMM-YYYY", [Sales Date])
    Make dates work for you!
  12. 🎯 Single Value Validation
    Check for a single unique value:
    IF COUNTD([Region]) = 1 THEN [Region] ELSE "Multiple Regions" END
    Validate with ease!
  13. 🕵️‍♀️ Filter Detection
    Detect if a field is filtered:
    IF SIZE() > 1 THEN "Filtered" ELSE "Not Filtered" END
    Be a filter detective!
  14. 📈 Maximum Values in a Table
    Find the max sales amount:
    WINDOW_MAX(SUM([Sales Amount]))
    Reach the peak!
  15. 📉 Minimum Values in a Table
    Find the min sales amount:
    WINDOW_MIN(SUM([Sales Amount]))
    Find the floor!
  16. 🧮 Counting Rows in a Table
    Count rows in a table:
    SIZE()
    Count on it!
  17. 🎲 Counting Unique Values
    Count unique products:
    COUNTD([Product])
    Uniqueness counts!
  18. 🔍 Lookup Scenarios
    Check if a product exists:
    IF CONTAINS([Product], "Product A") THEN "Exists" ELSE "Does Not Exist" END
    Look it up!
  19. 📊 Creating a Series of Numbers
    Generate a series of numbers:
    INDEX()
    Count it out!
  20. 📝 Conditional Formatting
    Apply conditional formatting based on sales performance:
    IF SUM([Sales Amount]) > 10000 THEN "High" ELSEIF SUM([Sales Amount]) > 5000 THEN "Medium" ELSE "Low" END
    Visualize performance at a glance!

Even More Tableau Tricks

📚 If you want to dive even deeper into the world of Tableau, check out my Tableau books 🔗 Visual Analytics with Tableau (Amazon) and 🔗 Datenvisualisierung mit Tableau (Amazon)! These books are packed with even more Tableau Calculated Field tips, tricks, and tutorials to help you master Tableau. Don’t miss out on these invaluable resources!

Want to stay updated with the latest Tableau insights? Follow me on Twitter and LinkedIn. Share your thoughts, ask questions, and engage with a community of Tableau enthusiasts like yourself.

Feel free to leave a comment, ask questions, or share these Tableau tweets:

Tableau Berechnungen: 20 Unverzichtbare Tricks für deine Dashboards

Tableau Berechnungen: Noch mehr Tableau Tricks in diesen Büchern: “Datenvisualisierung mit Tableau” and “Visual Analytics with Tableau”
Tableau Berechnungen: Noch mehr Tableau Tricks in diesen Büchern: “Datenvisualisierung mit Tableau” and “Visual Analytics with Tableau”

Möchten Sie Ihre Fähigkeiten in Tableau Berechnungen verbessern? Hier sind einige unserer Lieblings-Tricks, die Ihnen dabei helfen werden, Ihre Tableau Dashboards auf das nächste Level zu heben.

20 ultimative Tableau-Tricks für Ihre Tableau Berechnungen – einfach erklärt

  1. 📊 Summieren nach Bedingungen
    Berechne die Summe der Verkäufe für eine bestimmte Region:
    IF [Region] = "West" THEN SUM([Sales Amount]) END
    Tolle Analyse!
  2. 🔗 Zugriff auf verwandte Daten
    Hole verwandte Produktnamen:
    ATTR([Product Name])
    Vereinfacht Datenbeziehungen!
  3. 🧠 Zeilenkontext-Berechnungen
    Berechne den Verkaufsbetrag pro Verkaufs-ID:
    {FIXED [Sales ID]: SUM([Sales Amount])}
    Nutze den Kontext!
  4. 🏅 Werte Rangieren
    Rangiere Verkaufsbeträge in absteigender Reihenfolge:
    RANK(SUM([Sales Amount]), 'desc')
    Sieh, wer oben ist!
  5. 🧮 Sichere Division
    Vermeide Division durch Null:
    IF [Total Units] != 0 THEN [Total Sales] / [Total Units] END
    Keine Fehler mehr!
  6. 🔄 Mehrere Bedingungen
    Verwende CASE für mehrere Bedingungen:
    CASE [Rating] WHEN 1 THEN "Schlecht" WHEN 2 THEN "Durchschnittlich" WHEN 3THEN "Gut" ELSE "Unbekannt" END
    Halte es sauber!
  7. 🚫 Filter Entfernen
    Schließe Filter von einer Berechnung aus:
    {EXCLUDE [Sales]: SUM([Sales Amount])}
    Kontrolliere deine Filter!
  8. 🧵 String-Aggregation
    Verkette Produktnamen:
    CONCATENATE([Product], ", ")
    Füge es zusammen!
  9. 📆 Vergleiche mit dem Vorjahr
    Berechne den Unterschied in Jahren:
    DATEDIFF('year', [Date], TODAY())
    Zeitreise mit Daten!
  10. 🕳️ Umgang mit Fehlenden Daten
    Ersetze Nullen durch NULL:
    IF [Sales Amount] = 0 THEN NULL ELSE [Sales Amount] END
    Räume die Leerstellen auf!
  11. 🎨 Benutzerdefiniertes Datumsformat
    Formatiere Daten nach deinen Wünschen:
    DATEPARSE("MMM-YYYY", [Sales Date])
    Lass Daten für dich arbeiten! #Tableau #Datenvisualisierung
  12. 🎯 Validierung von Einzelwerten
    Überprüfe auf einen einzelnen eindeutigen Wert:
    IF COUNTD([Region]) = 1 THEN [Region] ELSE "Mehrere Regionen" END
    Validiere mit Leichtigkeit!
  13. 🕵️‍♀️ Filtererkennung
    Erkenne, ob ein Feld gefiltert ist:
    IF SIZE() > 1 THEN "Gefiltert" ELSE "Nicht Gefiltert" END
    Sei ein Filterdetektiv!
  14. 📈 Maximale Werte in einer Tabelle
    Finde den maximalen Verkaufsbetrag:
    WINDOW_MAX(SUM([Sales Amount]))
    Erreiche den Gipfel!
  15. 📉 Minimale Werte in einer Tabelle
    Finde den minimalen Verkaufsbetrag:
    WINDOW_MIN(SUM([Sales Amount]))
    Finde den Boden!
  16. 🧮 Zeilen in einer Tabelle Zählen
    Zähle Zeilen in einer Tabelle:
    SIZE()
    Zähle darauf!
  17. 🎲 Einzigartige Werte Zählen
    Zähle einzigartige Produkte:
    COUNTD([Product])
    Einzigartigkeit zählt!
  18. 🔍 Lookup-Szenarien
    Überprüfe, ob ein Produkt existiert:
    IF CONTAINS([Product], "Product A") THEN "Existiert" ELSE "Existiert Nicht" END
    Suche es!
  19. 📊 Erstellen einer Zahlenreihe
    Generiere eine Zahlenreihe:
    INDEX()
    Zähle es!
  20. 📝 Bedingte Formatierung
    Wende bedingte Formatierung basierend auf Verkaufsleistung an:
    IF SUM([Sales Amount]) > 10000 THEN "Hoch" ELSEIF SUM([Sales Amount]) > 5000 THEN "Mittel" ELSE "Niedrig" END
    Visualisiere Leistung auf einen Blick!

Noch mehr Tableau Tricks

📚 Wenn Sie noch tiefer in die Welt von Tableau eintauchen möchten, schauen Sie sich unsere Tableau Bücher an: 🔗 Datenvisualisierung mit Tableau (Amazon) und 🔗 Visual Analytics with Tableau (Amazon). Beide sind vollgepackt mit noch mehr Tipps, Tricks und Anleitungen, die Ihnen helfen, das Beste aus Ihren Tableau Dashboards herauszuholen.

Haben Sie Fragen oder Anregungen zu Tableau Berechnungen? Lassen Sie es uns gerne wissen, und vergessen Sie nicht, unsere Tableau-Tweets zu teilen:

#datamustread 2022 Essentials: How to Level Up In Your Data Journey

Best Data Science Books: Top 5 Essential Reads for 2022 - #datamustread
Best Data Science Books: Top 5 Essential Reads for 2022 – #datamustread

For some time now, I have been using the hashtag #datamustread on LinkedIn and Twitter to regularly recommend books that are essential for a data journey. At the end of this year, I would like to put together some absolute highlights that I consider to be absolute #datamustread books:

📖 True or False by Cindy L. Otis
📖 Info We Trust by RJ Andrew
📖 Tools and Weapons by Brad Smith
📖 Data Science for Business by Foster Provost and Tom Fawcett
📖 Decisively Digital by 24 thought leaders interviewed by me

True or False: A CIA Analyst’s Guide to Spotting Fake News

True or False by Cindy L. Otis covers the entire spectrum of misinformation and disinformation, why we fall for it, and what we can do about it. Even though some concepts are familiar to me, I still learned quite a lot. The book contains a wealth of unexpected examples, current and from history, and is more relevant than ever in today’s world.

Info We Trust: How to Inspire the World with Data

Info We Trust by RJ Andrews is an inspiring journey of data storytelling, but it’s also written in an extremely entertaining way, making this #datamustread the perfect companion for relaxing days. RJ’s enjoyable writing style, by the way, has been a guiding light for my own books.

„#datamustread 2022 Essentials: How to Level Up In Your Data Journey“ weiterlesen

How to Create a Skyscraper Map in Power BI using Azure Maps: a Guide to Bar Chart Mapping

Skyscraper Map in Power BI, aka. bar chart map, or bar chart on a map
Skyscraper Map in Power BI, aka. bar chart map, or bar chart on a map

Have You Ever Seen a Bar Chart on a Map?

Welcome to the fascinating world of data visualization, where even maps can take the form of bar charts! I prefer to call this visualization a Skyscraper Map because you can picture these bars on a map as skyscrapers. Also known as a Bar Chart Map, this type of visualization brings your geodata to life, giving it the appearance of skyscrapers dotting a cityscape.

Why Use a Skyscraper Map?

You can use a skyscraper map to display geodata along with its corresponding values. This innovative visualization combines a map indicating various locations (be it a city, a country, or any geographical place) with a bar chart. Like a traditional bar chart, the height or volume of each bar in a skyscraper map is proportionate to the values it signifies.

Crafting a Skyscraper Map with Azure Maps in Power BI

First, you need to make sure that the Azure Maps preview feature is enabled in Power BI to create a skyscraper map. Here’s a step-by-step guide using the Retail Analysis Sample dataset:

Step 1. Click on the Azure Map icon in the Visualization pane.

Step 2. Drag the lower right corner to extend the filled map visual.

Step 3. From the Fields Plane, select PostalCode.

Power BI assigned Country to the Location field.
Power BI assigned Country to the Location field.

Step 4. Now, choose TotalSales from the Fields Plane.

Power BI assigned Sales to the Bubble size field.
Power BI assigned Sales to the Bubble size field.

Step 5. Head over to the Format your Visual section.

Step 6. Toggle off the Bubble layer switch.

Step 7. Enable the Bar chart layer switch.

Power BI with enabled Bar chart layer switch.
Power BI with enabled Bar chart layer switch.

Step 8. Expand the Bar chart layer pane.

Step 9. Expand the Size pane.

Step 10. Under the Size pane, set the Height to 4 px.

Step 11. Under the Size pane, set the Width to 3 px.

Power BI showing a skyscraper map.
Power BI showing a skyscraper map.

With these steps, you’ve created a skyscraper map showing sales by zip codes in your dataset. Want to try it out? Download the PBIX file here.

Teach Yourself VISUALLY Power BI book cover

If you’re keen on diving deeper into Power BI, don’t miss my book, Teach Yourself VISUALLY Power BI (Amazon), filled with more insightful tutorials like this one. Got any feedback, ideas, or questions about creating bar chart maps in Power BI? I’d love to hear from you:

„How to Create a Skyscraper Map in Power BI using Azure Maps: a Guide to Bar Chart Mapping“ weiterlesen