University of Western Australia

Guest Lecture

SAP Business Intelligence

Joshua Fletcher

SAP Mentor

16th October 2013

Agenda

1. Introduction

2. SAP Overview

3. SAP's Analytics & IM Platform

4. Industry Trends

– Mobile Analytics

– In-memory Databases

– Predictive / Statistical Analysis

5. Questions & Answers

Introduction

• Twelve years experience with BI tools

• Recently spent seven years as a

Principal Consultant and Team Lead (up

to 10 consultants) including recruiting

graduates

• Now contracted to BHP Billiton Iron Ore

as a BI Architect in their new BICC

• Experienced across the lifecycle of

Business Intelligence and Enterprise

Information Management

SAP Mentor Initiative

SAP Mentor Initiative

• SAP Mentors are the top community

influencers of the SAP Ecosystem

• Most of the ~130 mentors work for

customers or partners of SAP

• All of them are hands-on experts of an SAP

product or service, as well as excellent

champions of community-driven projects

• Focus is on engagement, co-innovation and

advocacy

Channels

Unprofessional

journalism at its

finest

Recorded by a

bunch of guys in

the SAP BI

community

Podcasts on

product news,

technology usage

and interviews with

other BI people

@dslayered

dslayer.net

dslayered

Who is SAP? • SAP is the world leader in enterprise applications in

terms of software and software-related service

revenue

• More than 238,000 customers in 188 countries

• More than 65,500 employees – and locations in

more than 130 countries

• A 41-year history of innovation and growth as a true

industry leader

• Annual revenue (IFRS) of € 16,22 billion

• Listed under the symbol "SAP" on stock exchanges,

including the Frankfurt Exchange and NYSE

• SAP recently celebrated it’s 40th anniversary (video)

SAP’s Analytics Platform

Gartner Magic Quadrant 2013

Business Intelligence

Gartner Magic Quadrant 2013

Data Warehouse

Information Management

Trend 1 – Mobile Analytics • 1 in 3 Americans now own a tablet (Mashable Jun

2013)

• Australians have the most tables per capita in

study across 16 countries (SMH Dec 2012)

• What are the hot areas for mobile BI?

– Self-service report & dashboard consumption

– Spatial analysis

– Exploration of information

– Simple ad-hoc analysis

• Most vendors have mobile apps that are free to

download and use trial data with

Mobile BI Demonstration

Trend 2 – In-memory Databases • Gartner note 60 vendors who provide

forms of in-memory databases (IMDB)

• Major vendors who now support (or have

announced planned support) include:

– SAP with HANA

– Oracle with Oracle DB In-memory Option

– IBM with IBM DB2 Blu

– Microsoft with SQL Server 2012 Hekaton

• Some vendors are adding to existing

tech, others are building new

SAP HANA

• Natively in-memory with MPP architecture

• Designed to support OLTP & OLAP

workloads simultaneously (write

individuals record while querying billions)

• Unstructured & structured data storage

• High compression with column & row store

• On-premise or cloud deployment options

SAP HANA Capabilities

• Advanced calculation/semantic layer

• Unstructured text analytics

• Statistical algorithms

• Data quality algorithms

• Spatial querying supported

• Smart Data Access allows querying of

Hadoop, Sybase IQ and other databases

SAP HANA – More Than a DB

SAP HANA Performance

3 billion scans per second per core

12.5 million aggregates per second per core

1.5 million inserts per second

SAP HANA Performance

• 1 PB Performance Benchmark

– 100 Nodes, 100 TB in DRAM

– 10 Years of Sales & Distribution Data

– 1.2 trillion Rows (330 Million transactions / day)

– Ad-hoc Simple Queries (e.g. Month Report)

• 430ms – 647ms, Drill-down: 142ms, Complex Queries

(e.g. YoY report): 1.2s – 3.1s

– Query Throughput (Queries per Hour)

• 7,547 for 1 stream, 57,202 for 10 streams, 112,602 for

60 streams

SAP HANA Demonstration

Trend 3 - SAP Predictive Analytics

• Desktop analyst tool which provides data

acquisition, cleansing, statistical analysis and

visualisation capabilities

• Integrates with local R engine or pushes

analysis to HANA and Predictive Algorithm

Library (PAL)

• Able to handle big data by leveraging HANA’s

capabilities

• New possibilities such as McLaren F1 (video)

Predictive Needs & Examples

• Anomalies – what anomalies or groupings/clusters exist?

• Forecasting – how does historical information translate to future performance?

• Relationships – are there correlations in data, or opportunities to cross-sell or up-sell?

• Key Influencers – what are main influencers of customer satisfaction or customer churn?

• Trends – what are emerging trends or sudden step changes that will impact business?

Integration with R Library

• Open source statistical programming

language with over 3,500 packages and

ability to write your own functions

• Used by growing number of data analytics

in industry, government, consulting and

academia

• Free, comprehensive and many learn at

college or university

HANA Synergies

• Leverage complimentary capabilities of Predictive Analytics and HANA PAL

• Integrated and optimised for interoperability, enabling combination of real-time and operational analytics, access to big data, and predictive capabilities

• If it's available through HANA, it can be used for data mining and predictive analysis: gain real-time access to BPC, BW, ERP, Analytic Applications and more

Common Algorithms

• Association (Apriori)

– Find frequent item patterns in transactional

datasets ie market basket analysis

• Clustering (K-Means)

– Cluster observations into related groups

• Decision Trees (CNR Tree)

– Classify observations into groups and predict

discrete variables

Common Algorithms

• Neural Network (MONMLP Neural Network)

– Forecast, classify and undertake statistical

pattern recognition

• Outliers (Nearest Neighbour Outlier)

– Find patterns in data that aren’t expected

• Regression (Exponential Regression)

– Finds trends in data

• Time Series (Single Exponential Smoothing)

– Smooth (trend) or forecast time series data points

SAP Predictive Analysis Demonstration

Useful Links – Mobile BI

• Explorer iPad App

• Mobile BI iPad App

• Lumira Cloud Free

• Lumira Desktop Personal Edition Free

Useful Links – HANA

• SAP HANA Startup Program

• Access Your Own HANA Server

– Free 30 day trial

– Cloud development access (Amazon EC2

PAYG)

• HANA Academy

• NBA Statistics (powered by HANA)

Useful Links – Predictive

• SAP Predictive Analysis Trial

• Try R School

• Free book ‘Learning Statistics with R’

Useful Links – General

• SAP Mentor Initiative Introduction

• Diversified Semantic Layer

Any questions?

You can reach me on:

@josh_fletcher

josh@geek2live.net