Self-Service Business Intelligence and Analytics

Course Description

This course focuses on principles, concepts and practices of self­service business intelligence and analytics. It discusses the primary functionality of self­service BI that includes retrieving and collecting data from data sources, creating business data analysis models and insights, building interactive reports and visualization. Practices with self­service BI tools using Power BI and Excel will be performed in the course. In addition, it explores data analytics with DAX and SQL Server Data Mining add­in for Excel. Guidelines of self­service BI implementation and tool selection criteria are also discussed.

Duration: 3 days (9:00-­16:00)

Fee : 11,900 Baht  exclude VAT (9,900 Baht exclude VAT with your own computer)

(Fee includes Course Material + Coffee Break and Lunch)

Training Schedule:

• 23 - 25 March 2016

• 12-14 October 2016

Software Tools

• Power BI and Excel 2013

• SQL Server 2016 CTP

Prerequisites: -

Who Should Attend

• Data analyst

• BI analyst/designer

• Technical/business manager/lead

• Ones who are interested in BI analytics

Course Outline

Day 1: Self-Service BI Fundamentals, Power BI for Excel

• Principles and concepts of self­service BI and analytics

• Importances of empowering BI users

• Critical factors and guidelines of self­service BI implementation

• Self­service BI with Power BI for Excel

• Architecture and components of Power BI for Excel

• Data query, transformation and integration with Power Query

• Data modeling for analysis with Power Pivot

• Data visualization with Power View

Day 2: Exploring Capabilities of Power BI

• Data manipulation with Power Query

• DAX analytics

• Power BI service and its components

• Building and sharing dashboard

• Power BI for mobile

• Exploring and visualizing data with Power Map

Day 3: Self-Service Analytics with Data Mining Add-in for Excel

• Architecture of SQL Server Data Mining Add­in for Excel

• Principles and concepts of various data mining algorithms

• Applying mining for business analytics

• Analyzing data behaviors and patterns

• Mining algorithm parameters

• Trends of self­service BI and analytics

Online Registration >> HERE