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01 necto introduction_ready


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01 necto introduction_ready

  1. 1. Necto TrainingModule 1:Introduction to Necto
  2. 2. Training Plan
  3. 3. Training Plan Administrators End User Analysts and Training Training Developers Training Introduction to Necto Analytics Necto Necto – Advanced Architecture Features The Necto Necto Application Administration Creating New Installing and Data Sources Workboards Migration Necto Analytics Panorama and Basics Support Working with Building a KPIs Panorama Social Network SDK
  4. 4. Introduction to Necto
  5. 5. Objectives By the end of this lesson you will be able to: Describe fundamental BI concepts List Panorama Necto’s advantages over traditional BI solutions Choose training modules that fit your needs
  6. 6. Agenda What is BI? Necto Product overview OLAP Fundamentals
  7. 7. What is Business Intelligence(BI)
  8. 8. Business Intelligence (BI) Overview Business Intelligence Infrastructure • A wide category of applications and technologies for: • Gathering, storing, analyzing, OLAP • Providing access to data (MDX, DAX) • Help enterprise users make better business decisions BI Applications • Include the activities of: • Decision support systems • Query and reporting • Visualizations • Exceptions, statistical analysis Panorama Necto delivers a BI application on Microsoft BI Infrastructure (connectivity to other BI tools also available)
  9. 9. Necto Overview
  10. 10. Welcome to the Next Generation of BI – BI 3.0
  11. 11. Panorama NectoTM BI 3.0: Build Your Corporate IntelligenceSELF-SERVICEInteractive UIAutomated analytics & RELEVANTrich visualization tomake powerful BIsimple Intelligent BI Engine A system that learns to automatically generate relevant insights by understanding user’s behavior SOCIAL Social Intelligence Engaging platform for collaborative decision making
  12. 12. Panorama Necto Architecture Reporting Social Automated End User Analytics Workboards Intelligence Insights Client Intelligence Necto Server AIDEN Layer BI MDX Engine (Automated Intelligence • Business Logic Driving Engine) • Administration, security Modeling,aggregations, semantics and / or and / or Analysis Services PowerPivot Universal Data Connector Source, operational raw data MS SQL SAP Oracle Flat Files Applications SSAS
  13. 13. Bringing Contextual Discovery to BI Data & Insights Workboards People Discussions & Notes Automated Intelligence
  14. 14. End-to-End BI Suite Intuitive & Interactive for Business Users Social Automated WorkBoardsAnalytics Intelligence InsightsReporting KPI’s Visuals Office (i.e treemaps) Integration Complete Web-based Experience
  15. 15. Demonstration
  16. 16. Value Proposition Simple, self-service BI for the Business User More power to the Analyst / the power user Easy solution to deploy and maintain for the IT Enable organizations build their Corporate Intelligence On top of any data source!
  17. 17. OLAP Fundamentals
  18. 18. OLAP – Online Analytical Processing OLAP (Online Analytical Processing) A class of applications to quickly answer multi-dimensional analytical queries OLAP Cube Multidimensional set of data used for dynamic analysis
  19. 19. OLAP Analysis Business Purpose Grapes Atlanta Cherries Product Denver Detroit Melons Location Apples Pears Q1 Q2 Q3 Q4 Time
  20. 20. OLAP Database Components Measure Represents factual data related to a specific business process Examples: sales, cost, profit Dimension Identifies and categorizes measures Example: Location, Product, and Time
  21. 21. OLAP Database Components LEVELSHierarchy: A logical structure that groups All Products Total Product dimension members for the purpose of aggregating data Category Hardware Software Example: Product Categories Subcategory PCs Laptops Server Client Product Model1 Model 2 Word ExcelLevel A position in the hierarchy Example: Category, SubcategoryMembers Lowest level in a hierarchy Example: PCs, Laptops, MonitorsAttributes Descriptive information about the dimension members Examples: Color, Size, Weight
  22. 22. Thank youAny Questions?