Unlocking the Power of Data Science with Excel: Discover the Book „Data Smart“

Exploring the depths of Data Science with Excel: A glimpse into 'Data Smart' by Jordan Goldmeier, a must-read for data enthusiasts.
Exploring the depths of Data Science with Excel: A glimpse into ‚Data Smart‘ by Jordan Goldmeier, a must-read for data enthusiasts.

Data Smart (Amazon) is an exceptional guide that creatively uses Microsoft Excel to teach data science, making complex concepts accessible to business professionals. This 2nd edition, masterfully updated by Jordan Goldmeier, arrives a decade after John Foreman’s highly acclaimed original version, bringing fresh perspectives and contemporary insights to the renowned first edition.

Whether you’re a novice or a seasoned analyst, this book provides valuable insight and skill enhancement without requiring extensive programming knowledge. The practical, problem-solving approach ensures that you not only understand the theory, but also how to apply it in real-world scenarios. That’s why I’ve chosen Data Smart as our latest pick for the #datamustread book club.

Why „Data Smart“ is a #datamustread

Data Smart stands out in the realm of data science literature. Its approachable and practical methodology is a breath of fresh air for business professionals and data enthusiasts alike. Here’s why this book is an indispensable resource:

1. Excel as Your Data Science Laboratory:
The use of Excel, a tool many of us are familiar with, to unravel data science concepts is nothing short of brilliant. This approach significantly flattens the learning curve, making complex techniques more digestible.

2. Practical Learning through Real Business Problems:
Each chapter of the book introduces a different data science technique via a relatable business scenario. This context-driven approach makes the learning experience tangible and immediately applicable.

3. No Programming, No Problem:
The author’s method of teaching data science without delving into programming languages makes the content accessible to a broader audience.

4. Excel Skills Elevated:
In addition to data science concepts, readers will enhance their Excel prowess with advanced tools like Power Query and Excel Tables.

5. A Spectrum of Techniques:
From cluster analysis to forecasting, the book covers a wide array of methods, making it a comprehensive toolkit for any aspiring data scientist.

6. Fresh Perspectives in the Second Edition:
Goldmeier’s updates are not just cosmetic; they incorporate the latest Excel features, ensuring the content remains relevant in today’s fast-paced tech landscape.

Bridging the Gap with „Teach Yourself VISUALLY Power BI“

While exploring Data Smart, you’ll find parallels with the insights shared in my own book, Teach Yourself VISUALLY Power BI. Both texts aim to make data analytics accessible and actionable, providing a solid foundation for anyone looking to make informed decisions based on data.

Your Journey into Data Science Awaits

Data Smart is a gateway to understanding data science through a familiar and powerful tool: Excel. Whether you’re a beginner or a seasoned analyst, this book will enhance your analytical skills and expand your understanding of data in the business world.

Order Data Smart today and support both the authors and my endeavors in bringing such valuable resources to our community. Let’s dive into this journey of discovery together, transforming data into actionable insights.

Join the Conversation

After delving into Data Smart, I’d love to hear your thoughts and takeaways. Share your insights and join the discussion in our vibrant #datamustread community on LinkedIn and Twitter:

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Power BI Tricks: 20 Essential DAX Tricks for Your Power BI Reports – A Comprehensive Guide to Power BI DAX

Even more Power BI DAX tricks in these books: "Datenvisualisierung mit Power BI" and "Teach Yourself Visually Power BI"
Even more Power BI DAX tricks in these books: „Datenvisualisierung mit Power BI“ and „Teach Yourself Visually Power BI“

Power BI DAX (Data Analysis Expressions) is at the core of Microsoft’s Power BI and offers incredible capabilities for data manipulation and insights. In this post, we’ll explore 20 ultimate DAX tricks to elevate your Power BI reports. Whether you’re a beginner or an expert, these tips will help you unlock the full potential of Power BI and Microsoft Fabric.

20 Ultimate DAX Tricks – Simply Explained

  1. Use CALCULATE for Context Modification 🛠️
    CALCULATE is a powerful function that changes the context in which data is analyzed.
    Example:CALCULATE(SUM('Sales'[Sales Amount]), 'Sales'[Region] = "West")
    This calculates the sum of sales in the West region.
  2. Use RELATED for Accessing Data from Related Tables 🔄
    RELATED function allows you to access data from a table related to the current table.
    Example: RELATED('Product'[Product Name])
    This fetches the product name related to the current row.
  3. Use EARLIER for Row Context 🕰️
    EARLIER is a useful function when you want to access data from an earlier row context.
    Example: CALCULATE(SUM('Sales'[Sales Amount]), FILTER('Sales', 'Sales'[Sales ID] = EARLIER('Sales'[Sales ID])))
  4. Use RANKX for Ranking 🏅
    RANKX function allows you to rank values in a column.
    Example: RANKX(ALL('Sales'), 'Sales'[Sales Amount], , DESC)
    This ranks sales amounts in descending order.
  5. Use DIVIDE for Safe Division 🧮
    DIVIDE function performs division and handles division by zero.
    Example: DIVIDE([Total Sales], [Total Units])
    This divides total sales by total units and returns BLANK() for division by zero.
  6. Use SWITCH for Multiple Conditions 🔄
    SWITCH function is a better alternative to nested IFs.
    Example: SWITCH([Rating], 1, "Poor", 2, "Average", 3, "Good", "Unknown")
    This assigns a label based on the rating.
  7. Use ALL for Removing Filters 🚫
    ALL function removes filters from a column or table.
    Example: CALCULATE(SUM('Sales'[Sales Amount]), ALL('Sales'))
    This calculates the total sales, ignoring any filters.
  8. Use CONCATENATEX for String Aggregation 🧵
    CONCATENATEX function concatenates a column of strings.
    Example: CONCATENATEX('Sales', 'Sales'[Product], ", ")
    This concatenates product names with a comma separator.
  9. Use USERELATIONSHIP for Inactive Relationships 🔄
    USERELATIONSHIP function allows you to use inactive relationships.
    Example: CALCULATE(SUM('Sales'[Sales Amount]), USERELATIONSHIP('Sales'[Date], 'Calendar'[Date]))
    This calculates sales using an inactive relationship.
  10. Use SAMEPERIODLASTYEAR for Year-Over-Year Comparisons 📆
    SAMEPERIODLASTYEAR function calculates the same period in the previous year.
    Example: CALCULATE(SUM('Sales'[Sales Amount]), SAMEPERIODLASTYEAR('Calendar'[Date]))
    This calculates sales for the same period last year.
  11. Use BLANK for Missing Data 🕳️
    BLANK function returns a blank.
    Example: IF('Sales'[Sales Amount] = 0, BLANK(), 'Sales'[Sales Amount])
    This returns a blank if the sales amount is zero.
  12. Use FORMAT for Custom Formatting 🎨
    FORMAT function formats a value based on a custom format string.
    Example: FORMAT('Sales'[Sales Date], "MMM-YYYY")
    This formats the sales date as „MMM-YYYY“.
  13. Use HASONEVALUE for Single Value Validation 🎯
    HASONEVALUE function checks if a column has only one distinct value.
    Example: IF(HASONEVALUE('Sales'[Region]), VALUES('Sales'[Region]), "Multiple Regions")
    This checks if there is only one region.
  14. Use ISFILTERED for Filter Detection 🕵️‍♀️
    ISFILTERED function checks if a column is filtered.
    Example: IF(ISFILTERED('Sales'[Region]), "Filtered", "Not Filtered")
    This checks if the region column is filtered.
  15. Use MAXX for Maximum Values in a Table 📈
    MAXX function returns the maximum value in a table.
    Example: MAXX('Sales', 'Sales'[Sales Amount])
    This returns the maximum sales amount.
  16. Use MINX for Minimum Values in a Table 📉
    MINX function returns the minimum value in a table.
    Example: MINX('Sales', 'Sales'[Sales Amount])
    This returns the minimum sales amount.
  17. Use COUNTROWS for Counting Rows in a Table 🧮
    COUNTROWS function counts the number of rows in a table.
    Example: COUNTROWS('Sales')
    This counts the number of rows in the Sales table.
  18. Use DISTINCTCOUNT for Counting Unique Values 🎲
    DISTINCTCOUNT function counts the number of distinct values in a column.
    Example: DISTINCTCOUNT('Sales'[Product]) This counts the number of distinct products.
  19. Use CONTAINS for Lookup Scenarios 🔍
    CONTAINS function checks if a table contains a row with certain values.
    Example: CONTAINS('Sales', 'Sales'[Product], "Product A")
    This checks if „Product A“ exists in the Sales table.
  20. Use GENERATESERIES for Creating a Series of Numbers 📊
    GENERATESERIES function generates a series of numbers.
    Example: GENERATESERIES(1, 10, 1)
    This generates a series of numbers from 1 to 10 with a step of 1.

Even more Power BI DAX Tricks

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

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

Feel free to leave a comment, ask questions, or share my Power BI DAX tweets:

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#datamustread Data Viz Essentials: The Must-Read Books to Master Data Visualization

#DataVizEssentials 2023: The Must-Read Books to Master Data Visualization
#DataVizEssentials 2023: The Must-Read Books to Master Data Visualization

Building on the previous #datamustread recommendations, I’m excited to present the data viz edition of #datamustread. In this post, we’re focusing on the indispensable skill of data visualization. Whether you’re a beginner or a seasoned pro, these five books will guide you to mastery:

  1. 📖 The Big Book of Dashboards
  2. 📖 Storytelling with Data
  3. 📖 The Truthful Art
  4. 📖 Show Me the Numbers
  5. 📖 Teach Yourself VISUALLY Power BI

The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios

A comprehensive guide filled with real-world solutions for building effective business dashboards across various industries and platforms. It’s a go-to resource for matching great dashboards with real-world scenarios.

Storytelling with Data: A Data Visualization Guide for Business Professionals

Cole Nussbaumer Knaflic shares practical guidance on creating compelling data stories. Learn how to make your data visually appealing, engaging, and resonant with your audience.

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Power BI Data Visualization Mastery: Unlocking Insights with „Teach Yourself VISUALLY Power BI“

Power BI Data Visualization Mastery with the book "Teach Yourself VISUALLY Power BI" by Alexander Loth
Power BI Data Visualization Mastery with the book „Teach Yourself VISUALLY Power BI“

If you’ve been on the lookout for a comprehensive guide to unlock the potential of data visualization using Microsoft’s Power BI, you’ve come to the right place. Our latest pick for the #DataMustRead book club is a special one – Teach Yourself VISUALLY Power BI (Amazon), which recently hit Amazon’s #1 New Release in Information Management. Authored by myself, this book is your pathway to understand and implement Power BI, regardless of whether you’re a beginner or a seasoned professional.

Why Choose „Teach Yourself VISUALLY Power BI“ for Your Power BI Journey?

Microsoft’s Power BI is a dynamic tool, breathing life into your company’s data through rich visuals and interactive dashboards. As powerful as it is, though, it can also present a daunting learning curve, especially if you’re new to data visualization. „Teach Yourself VISUALLY Power BI“ is designed to help you conquer this curve and emerge as a Power BI maestro.

This book is more than just a typical guide. It’s a visually-rich journey that transports you from Power BI basics to advanced features, equipping you with a strong foundation. Here’s a peek into what you can expect:

  1. Connect with Various Data Sources: Learn to prepare your data for visualization and connect seamlessly to multiple data sources.
  2. Transform and Process Data: Understand the transformation of raw data into valuable, decision-driving information.
  3. Create Customizable Charts and Graphs: Design visually striking, easy-to-understand charts and graphs with hands-on guidance.
  4. Apply Analytics and Machine Learning: Uncover the realm of analytics and machine learning, and learn how to apply these concepts in Power BI.
  5. Craft Interactive Dashboards: Master the creation of interactive dashboards that effectively narrate your data’s story.

Each topic is presented using full-color screenshots, step-by-step instructions, and practical tips, ensuring that you’ll be able to follow along no matter your current skill level.

The Data Visualization Guide for Any Power BI Project

The reviews for „Teach Yourself VISUALLY Power BI“ speak for themselves. Many readers have found the book to be an excellent resource, praising its unique approach to teaching both, data visualization and Power BI. From the detailed explanation of requirements gathering – a crucial step in any Power BI project – to providing insightful exploration of the current BI job market, this book aims to equip readers with a comprehensive understanding of Power BI and its practical applications.

Your Next Step in Power BI Mastery

Whether you’re a data rookie or a seasoned expert seeking to upskill, „Teach Yourself VISUALLY Power BI“ is a must-read. It doesn’t just enable you to understand Power BI, it inspires you to craft your own data visualizations and drive impactful decisions.

Are you ready to dive deep into Power BI? Order your copy here to support my future book projects. Happy reading, data enthusiasts!

I’m eager to hear your thoughts as you delve into this comprehensive guide to Power BI. Don’t forget to use the hashtag #datamustread to share your insights and experiences on LinkedIn or Twitter!

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Die Schlüsselrolle der Datenkompetenz in der digitalen Transformation: Ein Gespräch mit Dilyana Bossenz – Neue Folge von „Die Digitalisierung und Wir“

Datenkompetenz: es gibt viele Möglichkeiten Daten zu visualisieren (Illustration von Dilyana Bossenz)
Datenkompetenz: es gibt viele Möglichkeiten Daten zu visualisieren (Grafik von Dilyana Bossenz)

In unserer neuesten Folge von „Die Digitalisierung und Wir“ haben wir Dilyana Bossenz zum Thema Datenkompetenz interviewt. Dilyana ist Dozentin für Data Visualization & Communication an der Digital Business University of Applied Sciences (DBU) in Berlin und Gründerin von Datenkompetenz-Online, einer Schulungsplattform für Unternehmen, die ihre Mitarbeiter in die Welt der Daten einführen wollen. Dilyana hat mit ihren Reviews einen wertvollen Beitrag zu den Büchern Datenvisualisierung mit Tableau (Amazon) und Datenvisualisierung mit Power BI (Amazon) geliefert.

Wir haben uns zunächst über Dilyanas beruflichen Hintergrund unterhalten und ihren Weg in die Welt der Daten nachgezeichnet. Mit ihrer langjährigen Erfahrung als BI-Beraterin und Enablement Managerin in verschiedenen Unternehmen hat sie eine Menge Wissen und Einblicke zu teilen, insbesondere im Bereich der Daten und Datenanalyse.

Effektive Kommunikation von Daten

Ein Gespräch mit Dilyana Bossenz – Neue Folge von "Die Digitalisierung und Wir"
Ein Gespräch mit Dilyana Bossenz – Neue Folge von „Die Digitalisierung und Wir“

Datenkompetenz, erklärt Dilyana, ist mehr als nur Toolkompetenz. Es geht darum, Daten nicht nur zu verstehen und zu analysieren, sondern sie auch effektiv zu kommunizieren und für fundierte Entscheidungen zu nutzen. Das Schöne ist, dass Datenkompetenz erlernbar ist und alle, unabhängig von der bisherigen Erfahrung, diese Fähigkeit verbessern kann.

Die meisten deutschen Unternehmen stehen noch vor großen Herausforderungen, wenn es um die Datenkompetenz ihrer Mitarbeiterinnen und Mitarbeiter geht. Dilyana hat jedoch einige konkrete Vorschläge, wie sich Unternehmen hier noch deutlich besser aufstellen können. Eine starke Datenkompetenz kann sich positiv auf die Entscheidungsfindung in Unternehmen auswirken und spezifische Bereiche wie Marketing, Vertrieb und Produktentwicklung deutlich voranbringen.

Datenkompetenz ist entscheident für Digitalisierung

Datenkompetenz spielt neben Sicherheit und Stabilität bei der Digitalisierung von Unternehmen eine entscheidende Rolle. In einer Welt, in der Data Driven Companies die neue Norm sind, ist es unerlässlich, die Datenkompetenz der Mitarbeiter zu fördern. Doch wie können Unternehmen dies sicherstellen? Und welche Auswirkungen kann eine starke Datenkompetenz auf die Unternehmenskultur haben? Auf all diese Fragen gibt Dilyana in unserer Podcast-Episode detaillierte Antworten.

Dilyana erzählt uns auch von ihrer Motivation ein Unternehmen zu gründen und wie die Entscheidung, alles online anzubieten, die Ausrichtung des Unternehmens beeinflusst hat. Wenn du darüber nachdenkst, dich selbstständig zu machen, wirst du ihre Erfahrungen und Ratschläge sicher sehr wertvoll finden. Passend zum Thema Datenanalyse und Statistiken hat Dilyana auch eine spannende Buchempfehlung: Money Ball: The Art of Winning an Unfair Game von Michael Lewis.

Wenn du dich in der Welt der Daten zurechtfinden willst oder einfach nur neugierig bist, was Datenkompetenz bedeutet, solltest du diese Episode nicht verpassen! Hör dir die ganze Geschichte in unserer neuesten Podcast-Episode an. Und wenn du die vorherige Episode über Alex‘ Reise in die USA und die neuesten Entwicklungen in der Technologiebranche verpasst hast, kannst du sie hier nachhören.

Bleibt dran für weitere spannende Themen rund um die Digitalisierung und ihre Auswirkungen auf unsere Gesellschaft. Kommentare sind immer willkommen! 👇

„Die Schlüsselrolle der Datenkompetenz in der digitalen Transformation: Ein Gespräch mit Dilyana Bossenz – Neue Folge von „Die Digitalisierung und Wir““ weiterlesen