Data Warhouse rješenje za banke

Information Management The IBM Netezza Appliance: Revolutionizing Analytics What is Netezza? © 2013 IBM

Information Management Appliances make it simple, completely transforming the user experience. § Dedicated device § Optimized for purpose § Complete solution § Fast installation § Very easy operation § Standard interfaces § Low cost 3 © 2013 IBM Corporation

Information Management The IBM Netezza Appliance: Revolutionizing Analytics Ø Purpose-built analytics engine Ø Integrated database, server & storage Ø Standard interfaces Ø Low total cost of ownership Ø Speed: 10 -100 x faster than traditional systems Ø Simplicity: Minimal administration Ø Scalability: Peta-scale user data capacity Ø Smart: High-performance advanced analytics © 2013 IBM Corporation

Information Management Some of the customers § Zavarovalnica Maribor § Zavarovalnca Triglav § Telekom Slovenije § Tuš Mobil § Petrol § Informatika § NLB § MKZ § Fabrika Duvana Sarajevo © 2013 IBM Corporation

Information Management Digital Media Financial Services Governme nt Health & Life Sciences Retail /

Information Management Business case – financial institution Evolution of DWH environment § Year 2000 – first “real” data warehouse – 1 power user, 20 common users, 1 IT developer § Years 2001 – 2005 – Number of users increased – 3 IT professionals, 100 common users, 10 power users – Enlargment of the data warehouse by factor 3 – DWH/BI becomes invloved in all crucial processes § Years 2005 – 2007 – Enlargment of the data warehouse by 100 – Increasing the number of common users to 250 – By end of 2007 DWH/BI declared as a key business process at ZM © 2013 IBM Corporation

Information Management Users expectations § High demand for information from the DWH system – the users expect that the system contains everything § “Immediate” responsiveness • Daily or even shorter frequencies for data loading • Real time BI • Sophisticated iterative analysis: marketing analysis, product or customer profitability analysis etc. • Quick ad-hoc reporting for various purposes © 2013 IBM Corporation

Information Management Main issues with existing DWH • More and more administration: database servers, application servers, BI tools, BI applications. . . • Higher and higher ownership costs (HW; SW licences. . . ) • Smaller and smaller time window for ETL • More and more end users • Continously increased complexity of the reports and analysis - killer queries which can only be run in the evening hours , “freeze” the server, even on DWH server. © 2013 IBM Corporation

Information Management Main challenges with building fully mature DWH/BI infrastructure • Cost boost • Entering in the upper cost-range of DWH servers • Unfavorable licensing policy for database SW (number of users, CPU licensees) • Complex administration of database servers • Required 1 - 4 employees to manage DWH © 2013 IBM Corporation

Information Management Benefits • Considered by the management as one of the best IT investments in the last 10 years • The same DWH/BI team is capable to manage even larger BI infrastructure. • Vast simplification of many complex queries and batch jobs • Development of new BI solutions • Users completely changed the way of thinking what they can get out of DWH © 2013 IBM Corporation

Information Management Smart Predicts what shoppers are likely to buy in future visits Coupon redemption rates as high as 25% “Because of (Netezza’s) in-database technology, we believe we'll be able to do 600 predictive models per year (10 X as many as before) with the same staff. " Eric Williams, CIO and executive VP © 2013 IBM Corporation

Appliance Simplicity © 2013 IBM Corporation

Information Management Managing The Netezza Appliance No software installation No storage administration No database

Information Management OLE-DB The Netezza Appliance – Loading Data Integration Ab Initio JDBC Business Objects/SAP Composite Software Expressor Software Informatica IBM Information Server Sunopsis (Oracle) Data In ODBC Golden. Gate Software (Oracle) SQL Wisdom. Force © 2013 IBM Corporation

Information Management OLE-DB The Netezza Appliance – Querying © 2013 IBM Corporation ODBC Data Out SQL Actuate Business Objects/SAP Cognos (IBM) Information Builders Kalido KXEN Micro. Strategy Oracle OBIEE Qlik. Tech Quest Software SAS SPSS (IBM) Unica (IBM) JDBC Reporting & Analysis

Information Management Simple to Deploy and Operate Ø Operations Simply load and go. … it’s an appliance Ø Installation to Business Value in ~2 days Ø Ease of Evaluation and Perform As Advertised Ø Ø BI Developers Data model agnostic Ø No configuration or physical modeling Ø No indexes or tuning – out of the box performance Ø Focus on business value, not physical design Ø Ø ETL Developers Faster load and transformation times Ø No aggregate tables needed – simpler ETL logic Ø In-database transformation – ‘ELT’ Ø Ø Business Analysts On-Stream processing by 100’s of nodes Ø Train of thought analysis – 10 to 100 x faster Ø True ad hoc queries Ø Lower latency – load & query simultaneously Ø 17 © 2013 IBM Corporation

Information Management Appliance Architecture © 2013 IBM Corporation

Information Management IBM Netezza True Appliance Architecture SOLARIS AIX TRU 64 HP-UX WINDOWS LINUX Client Database Server Storage DATA SQL ETL Server DBA CLI Source Systems SQL 3 rd Party Apps I/O CACHE Data High Performance Loader © 2013 IBM Corporation

Information Management IBM Netezza True Appliance Architecture SOLARIS Client AIX TRU 64 HP-UX Database WINDOWS Storage Server LINUX ODBC 3. X JDBC Type 4 SQL-92 SQL-99 Analytics ETL Server DBA CLI Source Systems CACHE 3 rd Party Apps I/O CACHE Database, Server, Storage - in one I/O High Performance Loader © 2013 IBM Corporation CACHE

Information Management IBM Netezza True Appliance Architecture Optimized Hardware+Software Purpose-built for high performance analytics; requires no tuning Streaming Data Hardware-based query acceleration for blistering fast results True MPP Deep Analytics All processors fully utilized for maximum speed and efficiency Complex analytics executed indatabase for deeper insights 21 © 2013 IBM Corporation

Information Management IBM Netezza True Appliance Massively Parallel Processing SOLARIS TRU 64 Client AIX HP-UX WINDOWS 1 LINUX ODBC 3. X JDBC Type 4 OLE-DB SQL/92 S-Blade Processor & streaming DB logic SQL Compiler 2 S-Blade Processor & streaming DB logic Query Plan Execution Engine 3 S-Blade Processor & streaming DB logic Optimize Admin ETL Server DBA CLI Source Systems Ÿ Ÿ Ÿ High-Speed Loader/Unloader 960 Front End DBOS 3 rd Party Apps SMP Host High Performance Loader © 2013 IBM Corporation High-Performance Database Engine Streaming joins, aggregations, sorts S-Blade Processor & streaming DB logic Network Fabric Massively Parallel Intelligent Storage

Information Management IBM Netezza True Appliance Massively Parallel Processing™ SOLARIS TRU 64 Client AIX HP-UX WINDOWS 1 LINUX SQL Compiler Snippets 1 2 3 S-Blade Processor & 2 3 streaming DB logic 2 S-Blade 2 3 Processor & streaming DB logic Query Plan Execution Engine 3 S-Blade 2 3 Processor & streaming DB logic Optimize ETL Server DBA CLI Source Systems High-Speed Loader/Unloader Ÿ Ÿ Ÿ Admin SQL 960 Front End DBOS 3 rd Party Apps SMP Host High Performance Loader © 2013 IBM Corporation High-Performance Database Engine Streaming joins, aggregations, sorts S-Blade 2 Processor & 3 streaming DB logic Network Fabric Massively Parallel Intelligent Storage

Information Management IBM Netezza True Appliance Massively Parallel Processing™ SOLARIS AIX TRU 64 HP-UX Client WINDOWS 1 LINUX Consolidate S-Blade Processor & 2 3 streaming DB logic SQL Compiler 2 S-Blade 2 3 Processor & streaming DB logic Query Plan Execution Engine 3 S-Blade 2 3 Processor & streaming DB logic Optimize Admin ETL Server DBA CLI Source Systems Ÿ Ÿ Ÿ High-Speed Loader/Unloader 960 Front End DBOS 3 rd Party Apps SMP Host High Performance Loader © 2013 IBM Corporation High-Performance Database Engine Streaming joins, aggregations, sorts S-Blade 2 Processor & 3 streaming DB logic Network Fabric Massively Parallel Intelligent Storage

Information Management Our Secret Sauce select DISTRICT, PRODUCTGRP, sum(NRX) from MTHLY_RX_TERR_DATA where MONTH = '20091201' and MARKET = 509123 and SPECIALTY = 'GASTRO' FPGA Core Uncompress Project CPU Core Restrict, Visibility Complex ∑ Joins, Aggs, etc. Slice of table MTHLY_RX_TERR_DATA (compressed) select DISTRICT, where MONTH = '20091201' PRODUCTGRP, and MARKET = 509123 sum(NRX) and SPECIALTY = 'GASTRO' © 2013 IBM Corporation sum(NRX)

Information Management Appliance family for data life-cycle management Skimmer Cruiser Dev & Test System Data Warehouse High Performance Analytics Queryable Archiving Back-up / DR 1 TB to 10 TB 26 N 1001/N 2001 1 TB to 1. 5 PB 100 TB to 10 PB © 2013 IBM Corporation

Advanced Analytics © 2013 IBM Corporation

Information Management Advanced Analytics the Netezza Way SPSS ü complex analytics üSAS, SPSS, R, Java, etc ü implicit parallelism SQL ü petabyte scalability ü appliance simplicity Demand Forecasting Fraud Detection R, S+ SQL © 2013 IBM Corporation

Pre-Built In-Database Analytics Statistics § Descriptive Statistics+ § Distance Measures* § Hypothesis Testing* § Chi-Square & Contingency Tables* § Univariate & Multivariate Distributions+ Transformations § Data Profiling / Descriptive Statistics+ § General Diagnostics Time Series § Autoregressive+ § Forecasting* § Statistics+ § Sampling § Data prep § Monte Carlo Simulation* Data Mining Predictive Mathematical § Basic Math* § Permutation and Combination* § Greatest Common Divisor and Least Common Multiple* § Conversion of Values* § Exponential and Logarithm* § Gamma and Beta Functions § Matrix Algebra+ § Area Under Curve* § Interpolation Methods* Geospatial § Association Rules+ § Linear Regression+ § Geospatial Data Type § Clustering+ § Logistic Regression+ § Geometric Functions § Feature Extraction+ § Classification § Geometric Analysis § Discriminant Analysis* § Bayesian § Sampling § Model Testing © 2013 IBM Corporation * Fuzzy Logix DB Lytix capabilities + Netezza Analytics and Fuzzy Logix DB Lytix capabilities

IBM Netezza: bold claims, backed up © 2013 IBM Corporation

Information Management Bold Claims, but. . . We Prove Them! Ø We prove we are simpler Ø We prove we deliver performance Ø We prove we work within your environment Ø We prove we integrate with your 3 rd party tools Ø We prove we are “easy to do business with” Ø We prove we have the lowest TCO Ø We prove business value © 2013 IBM Corporation

Data Warhouse rješenje za banke — IBM Netezza