This is the Rough Cut version of the printed book.
With The world of data is changing rapidly. The growing demands of end users (Consumerization of IT) and availability of new types of data (Data explosion - 85% of this new data is coming from new data types e.g. sensors, RFIDs, WebLogs, high-definition video streaming, oil and gas exploration etc.) is causing a widening gap between our ability to store vast amounts of data and our ability to get meaningful insight and drive decision making based on this vast amount of data. This data explosion, combined with the fact that the cost of storage has practically gone to zero has landed us in a world where we need to have the ability to store all this data and get insight into it. This makes sense for companies to make better business decisions by enabling data scientists and other users to analyze huge volumes of transaction data as well as other data sources that may be left untapped by traditional business intelligence (BI) programs.
On the analytics front there is a shift from traditional BI to predictive analytics as well - traditional BI helps customers to understand what has happened in past (rear view mirror) whereas predictive analysis allows customer to understand what would happen in future (forward-looking view). Predictive analysis has been effective in areas such as fraud detection, sales targeting, customer churn analysis, Ad Placement to increase revenue etc.
This book is going to cover in detail about storing vast amount of data (big data) on hadoop on windows (in Windows Azure platform) and getting insight into it with familiar Microsoft BI tools.
It addresses questions such as, "What is Big Data and how can Hadoop be used by an organization to tap into it? What are some of the important tools and technologies around the Hadoop ecosystem and Microsoft's partnership with Hortonworks?"
From this book you will learn:
• Ease of installation, configuration and monitoring of Hadoop (HDInsight) cluster on cloud platform
• Distributed storage and processing of unstructured data or big data
• Programming to do big data analytics with MapReduce, Hive, PIG
• Integration of Hadoop with Microsoft BI (MSBI) tools
• Analyze and create visualization reports your with Microsoft Power BI