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Power BI Blog

  • Getting Started with Excel and Power BI Series

    Over the next couple of weeks, we'll introduce you to the basic usage of all the latest and greatest features in Excel and Power BI. How do you know if this is the right series for you? Here are a few questions to help you decide:

    • Are you new to Power BI?
    • Did you sign up for the trial but don't know where to start?
    • Have you been using Excel for a long time, but you don't know where to start to use the new BI and visualization features?

    If you answered "yes" to any of them, then this is the right place for you to get started!

    Whether you're an Excel pro or you just downloaded the latest version of Excel, we decided to create this Power BI and Excel Getting Started series to get you up and running with our new set of features and services in no time.

    Our goal is to help you learn about and understand the features in Excel and Power BI following the natural path of getting some data in your hands (It doesn't matter where it comes from), shaping it, creating a model, visualizing your data to finally share it and consume it anytime, anywhere taking advantage of Power BI in the cloud.

    What should you expect to see in this series?

    The natural path of data analysis is a perfect match to the process of analyzing data. This series will cover the following features/processes:

    Excel

    Discover and Combine Data

    • Getting Started with Power Query

    Model and Analyze

    • Getting Started with Power Pivot

    Visualize

    • Getting Started with Power View
    • Getting Started with Power Map

    Power BI for Office 365

    Share and Collaborate

    • Getting Started with Power BI Sites
    • Getting Started with Power View Forecasting Capabilities
    • Getting Started with Sharing Queries and Data Stewardship
    • Getting Started with Connecting On-Prem data to Power BI

    Ask Questions

    • Getting Started with Q&A

    Access your data anywhere

    • Getting Started with the Power BI App
    • Getting Started with Power BI HTML5

     

    You can always come back to this post to find the latest getting started post or to access past posts of this series.

    Enjoy and please let us know what we can do to make this series better for you!

    #power query#Power BI#Power Pivot#Power View#Excel#Power BI app#Getting Started#power bi sites

    Tue, 08 Jul 2014 18:35:00 GMT byPower BI Team1 Comment

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  • World Cup: comparing contrast 20 years worth of data with natural language

    June 26th marked the end of the Round Robin stage, and we saw the World’s best teams crash out early while seeing other teams fight their way to the next round. There is no easy path to winning the World Cup, and we’re in for a treat for the next 16 games.

    Try PowerBI Q&A on World Cup 1990-2010 Data

    But, how did the 2014 Group Stage games compare with previous World Cups and could we potentially use these as an indicator for the games to come? PowerBI Q&A investigates and highlights key statistics surrounding World Cup’s most popular facts: goals, cards, and game performance. 

    2014 Performances

     

    Key insights: From the top 5 most winningest teams, Italy and Spain suffered an unfortunate fate. However, they have had similar performances before—Italy in 2002 and Spain in 1998. Their premature exit from the tournament is balanced by a bulk of the middle-tier teams doing really well (ex. Belgium, Colombia, Mexico, Switzerland, Costa Rica, etc.).

     

    Key insight: Taking a look at the club teams that Spanish players play for, we see that all of them play for the best teams in the world. All of these club teams play an average of 45-50 games a year so when the World Cup starts, they are not mentally or physically prepared. Also, this graph points out that there isn’t necessarily a correlation between playing for the same club team (or same league) for the entire year and World Cup performance. The Guardian did a great post on this as well using a complete data set from FIFA to show national team performance based on club teams.

     

    Key Insight: Scoring a lot of goals helps leading to victory, but at the end of the day, you have to stay consistent and win. Taking a look at Belgium and Croatia, they both scored 4 goals, but Croatia scored all those 4 goals in 1 game. Although Belgium didn’t score many goals, they won every game. One question I have looking at this graph is, can Colombia continue their perfect form?

    Goals, Cards, Attendance Statistics

    Key Insight: This year, compared to other World Cups, has been one of goals, not cards.

     

    Key Insight: Adding to the insight found from the above picture, this clearly has been a World Cup of goals, not cards.

     

    Key Insight: Longevity has helped Miroslav Klose tie the record for most goals scored (he has played in 4 world cups as opposed to Ronaldo’s 3). Also, Messi may be the best player in the world, but he isn’t yet the best in Argentina. Gabriel Batistuta has the most goals for Argentina, and Messi needs to continue his form this year. Thomas Muller, last year’s top goal scorer, is proving to be a consistently lethal threat.

      

    Key Insight: Although the United States held the World Cup in 1994, it still is today the highest attended World Cup. Due to existing infrastructure, USA has potential to host another World Cup. Maybe FIFA can make 2026 in the US.

    Can I Play With This Data

    When the World Cup is finished, we will make the 2014 data available to play with on Q&A. Currently, we have a demo experience live of 1990-2010 data that you can experience here:

    Try PowerBI Q&A on World Cup 1990-2010 Data

    *Note: Data is provided by Opta Sports and this documents 1990-2014 statistics.

    #Power BI#2014 world cup#Brazil#football#soccer#World Cup#QA

    Tue, 01 Jul 2014 16:00:00 GMT byPower BI Team0 Comment

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