This document provides an overview of the Necto Training module. It includes training plans for end users, analysts, administrators and developers. The Introduction to Necto section describes fundamental BI concepts and Necto's advantages over traditional BI solutions. It also outlines the agenda, which defines what BI is, provides a Necto product overview and covers OLAP fundamentals like dimensions, measures, hierarchies and levels.

1. Necto Training
Module 1:
Introduction to Necto

2. Training Plan

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. Introduction to Necto

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. Agenda
What is BI?
Necto Product overview
OLAP Fundamentals

7. What is Business Intelligence
(BI)

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. Necto Overview

10. Welcome to the Next Generation of BI
– BI 3.0

11. Panorama NectoTM
BI 3.0: Build Your Corporate Intelligence
SELF-SERVICE
Interactive UI
Automated analytics & RELEVANT
rich visualization to
make powerful BI
simple
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. 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

14. Bringing Contextual Discovery to BI
Data & Insights Workboards
People
Discussions
& Notes
Automated
Intelligence

15. End-to-End BI Suite
Intuitive & Interactive for Business Users
Social Automated WorkBoards
Analytics
Intelligence Insights
Reporting KPI’s Visuals Office
(i.e treemaps) Integration
Complete Web-based Experience

16. Demonstration

17. 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!

18. OLAP Fundamentals

19. 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

20. OLAP Analysis Business Purpose
Grapes
Atlanta Cherries Product
Denver
Detroit Melons
Location
Apples
Pears
Q1 Q2 Q3 Q4
Time

21. 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

22. OLAP Database Components
LEVELS
Hierarchy:
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 Excel
Level
A position in the hierarchy
Example: Category, Subcategory
Members
Lowest level in a hierarchy
Example: PCs, Laptops, Monitors
Attributes
Descriptive information about the
dimension members
Examples: Color, Size, Weight

23. Thank you
Any Questions?