Senior Consultant, SQLBI, Italy
Alberto Ferrari started working with SQL Server in 2000 and immediately focused his interest in the Business Intelligence area. After a few years, he started developing BI solutions with SSAS 2005 and it was a true love. At the beginning, he worked with SSIS, SSAS and SQL Server, spending most of his time in the development of a solid methodology to build data warehouses. In the meantime, he and Marco Russo create the SQLBI brand and website, where they publish their daily thoughts and topics about BI.
He studied and adopted both Kimball and Inmon architectures, before developing the new SQLBI methodology which is basically the union of those two well-known architectures, along with some creative ideas. In 2009 he published his first book: “Expert Cube Development with SSAS 2008” with Marco Russo and Chris Webb, which became a best-seller for seasoned SSAS developers.
In 2010 he started working with the new SSAS Tabular engine in Power Pivot for Excel and focused his interest in the VertiPaq engine and in-memory BI. He published several books on Power Pivot, SSAS Tabular and the DAX language, to educate the community on this new, amazing technology. He joined project Botticelli to share video lessons about Tabular and the DAX language. In the meantime, he achieved the SSAS Maestro title, the highest level of certification on Microsoft SSAS technology.
Today, his main activities are in the delivery of DAX, and SSAS Tabular workshops all around the world, consulting on large and complex data warehouses, to provide assessments and validation of project analysis or to perform specific problem-solving activities.
www.sqlbi.com, the website he founded with Marco Russo, became the main source for DAX programming and modeling techniques for developers all around the world, with thousands of users accessing it every day in search for articles, whitepapers and DAX solutions. He published Power Pivot video courses on Udemy to reach all those people who cannot attend classroom workshops.
He is a well-known speaker at many international conferences, like SQL PASS, SQL Bits, Teched and he loves to be on the stage both at large events and at smaller user groups meetings, exchanging ideas with other SQL and BI fans.
He and Marco are currently working on a new book on the DAX language: “The definitive guide to DAX”, due to publish later in 2015.
|Session Title & Code||Abstract||Level||Track||Inside xVelocity In-Memory Analytics Engine – (BIA-01A)||The xVelocity engine used by SQL Server Analysis Services Tabular, Power BI, and Power Pivot, is a columnar database capable of incredible performances, both in speed and compression ratio. In this session, we will perform a deep dive in the internals of the database architecture, discovering how Vertipaq stores information, in order to gain better insights into the engine and understand the best way to model your data warehouse to leverage the features of VertiPaq. We will show common and useful techniques to increase the compression ratio and obtain better performances from your Tabular data model.||Advanced||BIA|
|Budgeting with Power Pivot – (BIA-01I)||Budgeting is one of the most challenging scenarios in the Power Pivot arena. For example, you might need to summarize sales in previous years and to allocate the budget forecasts. You have to work with data at different granularities and to find a way to author DAX code to compute the forecasts at the desired granularity.
When it comes to budgeting, each company is a unique scenario. In this session, Alberto will show you some common techniques to use when building a budget model with Power Pivot and Power Query, including previous year allocation, multiple-step budgeting with linked back tables, handling of budget on products that do not yet exist.
|Tabular vs. Multidimensional in SQL Server Analysis Services – (BIA-02I)||Since 2012, SQL Server Analysis Services has two engines: Tabular and Multidimensional. Somebody believes Multidimensional is granny stuff and aim to learn only Tabular. Somebody trust only the good-old well-debugged code of Multidimensional, and ignores Tabular. We try to use a more informed approach: by looking at the difference in features, hardware requirements, scalability, required knowledge and business needs, we will discuss which engine to use for which kind of project. The goal is to teach when to use what, and to avoid the common mistakes of choosing the wrong technology, which might be a very expensive error.||Intermediate||BIA|
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