Beginning Big Data with Power BI and Excel 2013

Big data is all the rage. So you better buckle down and learn the ins and outs of Hadoop, Hive, Pig, Solr, Spark, and all the other Apache tools people say are absolutely required to take advantage of the revolution. Right? Maybe not. As Neil Dunlop, chair of the Computer Science Department at Berkeley City College in California demonstrates in Beginning Big Data with Power BI and Excel 2013, it turns out that a data analyst or tech-savvy IT or business manager armed with the latest versions of Excel and Power BI can import data into them and perform valuable, professional analyses of a company's Big Data assets.

While Beginning Big Data with Power BI and Excel 2013 covers prominent tools such as Hadoop and the NoSQL database Cassandra, it recognizes that most small and medium-sized businesses don’t have the Big Data processing needs of a Netflix, Target, or Facebook. Instead, it shows how to import data and use the self-service analytics available in Excel with Power BI. As you’ll see through the book’s numerous case examples, these tools—which you already know how to use—can perform many of the same functions as the higher-end Apache tools many people believe are required to carry out in Big Data projects.

To set the business context, veteran programmer/developer, teacher, and Excel/Power BI expert Neil Dunlop starts by reviewing the importance of analyzing data before making important business decisions and then determining when higher-end tools such as Hadoop and Cassandra are necessary. He then shows in great depth how small and medium-sized businesses can meet most of their data analysis needs using Excel with Power BI.

• Import and mash up data from web pages, SQL and NoSQL databases, the Azure Marketplace and other sources.
• Tap into the analytical power of PivotTables and PivotCharts and develop relational data models to track trends and make predictions based on a wide range of data.
• Understand basic statistics and use Excel with PowerBI to do sophisticated statistical analysis—including identifying trends and correlations.
• Use SQL within Excel to do sophisticated queries across multiple tables, including NoSQL databases.
• Create complex formulas to solve real-world business problems using Data Analysis Expressions (DAX).

Along the way, you’ll learn how to present the data using visual tools such as slicers, dashboards that summarize real-time results in relation to goals, data-driven maps, and OLAP cubes for multidimensional analysis. Through the book’s emphasis on real-world cases and examples, you’ll understand how to meet most of your big data analysis and decision needs using Excel and Power BI. That will save you time, money, and effort while providing the answers you need to critical business questions—faster and more accurately than ever.

• ISBN: 978-1-4842-0530-3
• Editorial: Apress
• Encuadernacion: Rústica
• Fecha Publicación: 06/08/2015
• Nº Volúmenes: 1
• Idioma: Inglés