THE ANALYTICS EXPERIENCE

Transcription

2 You already know the potential of analytics Productivity Strategic planning, human capital management and IT optimisation $674 billion $1.6 trillion Operations Demand and supply chain management and logistics $486 billion For companies that invest in the technologies, data, people, and practices at levels characteristic of the more innovative organizations, the potential is a 60% improvement on the return on their data assets a significant increase for any organization private or public. Innovations Service, research and development innovation $235 billion Customer-facing Customer acquisition, retention, support and pricing $158 billion Source: IDC Study: Realizing the Data Dividend, 2014 Copyright 2016, SAS Institute Inc. All rights reserved. 2

3 Decision making explored regardless of tech it all boils down to this Value of decisions erode with the time it takes to make them Decision Value Event Decision Value Strategic Gather information Decision latency Expert decision making Lost value Analyse information Make decision Action Automated decision making Operational Lost time Time Complexity Copyright 2016, SAS Institute Inc. All rights reserved. 3

10 Make better decisions 5 forces shaping the future analytics experience - and the SAS response -

11 5 forces shaping the analytics experience Data volume, velocity and variety Everyone is an data scientist The future of analytics is open Data as a corporate asset Changes in consumer expectations Copyright 2016, SAS Institute Inc. All rights reserved. 11

12 Data volume, velocity and variety Data volume, velocity and variety With IoT, text and new ways of tracking customer behavior means organizations need to be able push analytics to the data stream The new digital era calls for new approaches to segmentation like the segment of one Analytics in the new era requires the ability to learn fast, scale quickly and flexible distributed environments Comprehensive support for big data at today s scale A unified, cloud-ready high-performance analytics architecture Empower organizations to harness the power of big data with analytics in real-time. Combine in-memory and on-disk results to maximize analytic throughput An agile platform to enable innovation with zero impact on production ready analytical processes Copyright 2016, SAS Institute Inc. All rights reserved. 12

13 Publish Subscribe Event Stream Processing SAS Event Stream Processing Model Streaming Events Event Actions Continuous Query SAS In-Memory SAS-generated Insights Enrichment Data Analytic Models Copyright 2016, SAS Institute Inc. All rights reserved. 13 Business Rules

15 DESIGNING ESP MODELS Detect when event A is followed by event B and not Event C in a 3min time frame E1 AND E2 OR E3 Build complex network of events using temporal conditions Multiple events in can produce one event out FOLLOWED BY 5 MIN E4 AND NOT E5 FOLLOWED BY 1 HOUR E6 Copyright 2016, SAS Institute Inc. All rights reserved. 15

16 Everyone is an data scientist changing analytics consumption patterns Everyone is an data scientist Data Science and insight creation have the attention of the CEO to front line staff Data and analytics are no longer the domain of the few everyone needs access to insights Organizations need to combine easy to use analytics with the ability to customize and adapt to their governance and performance requirements Support new consumption patterns throughout the enterprise Provide organizations with a visual selfservice interface for all parts of the analytical lifecycle from data management to reporting to advanced analytics Provide data scientists with a coding interface to take advantage of the latest algorithms Ability to embed analytics in third party applications Copyright 2016, SAS Institute Inc. All rights reserved. 16

17 ABILITY TO EXECUTE ABILITY TO EXECUTE ABILITY TO EXECUTE Increasing analytical maturity Enable Approachable analytics The emergence of the Citizen Data Scientist COMPLETENESS OF VISION Business Intelligence Platforms 2012 COMPLETENESS OF VISION Business Intelligence and Analytics Platforms 2013 COMPLETENESS OF VISION Advanced Analytics Platforms 2014 The growing demand for these types of capability is outpacing the supply of expert users, which necessitates higher levels of automation and increases demand for self-service and citizen data scientist tools 2015 Copyright 2016, SAS Institute Inc. All rights reserved. 17

20 The future of analytics is open and flexible The future of analytics is open Organizations need to leverage the best of Open source and SAS to create scalable and well-governed analytics platform Ability to leverage talent regards of programmers preference with deployable analytics Openness at all levels SAS can augment and expand the open source ecosystem Provide robust model governance and comparison tools Ability to monitor model performance Facilitate sharing of code and programs Ability to embed and analytics in applications Copyright 2016, SAS Institute Inc. All rights reserved. 20

21 Attributes of an analytic platform PRODUCTIVITY SCALABILITY DEPLOYMENT Productivity for all users Provides a variety of user interfaces Makes data consumable Extendable and open Enables collaboration across modelers Executes more analytic models with less code Automates models performance Minimizes data movement Scales to any data volume Provides multi-threaded processing Provides scalable performance Ensures models are performing and accurate Extends lifecycle management through all stages of modeling Uses common repository for all models Provides governed models Generates deployable models (in memory and score code) Copyright 2016, SAS Institute Inc. All rights reserved. 21

25 Use SAS to integrate R R MODELS Why? Model Comparison Leverage R for new algorithms Ensembling Generate Score Code Deploy R models Copyright 2016, SAS Institute Inc. All rights reserved. 25 SAS MODELS

27 SAS Provides Productivity SAS Models (4) Gradient Boost Open Source (2) What if you coded this? Compare 7 models Choose champion Inventory Model Generate score code Deploy in database/hadoop Copyright 2016, SAS Institute Inc. All rights reserved. 27

28 Data as a corporate asset Data as a corporate asset New regulations requires organizations to build well managed and transparent data eco-systems Data needs to be consumable by everyone including Hadoop data Data breaches and data security has a direct and significant influence on brand perception Data transparency and governance for tomorrows world Enable Hadoop ecosystems with easy to use applications for analytics data preparation Allow users to evaluate and assess risk of data sources (SAS and non-sas) Automate and govern data transformation processes to minimize the risk of manual mistakes Track data access and data flows Copyright 2016, SAS Institute Inc. All rights reserved. 28

29 What about Hadoop IN SAS is all on Hadoop Why? Hadoop is everywhere Customers want to extract value from Hadoop Hadoop offers an amazing platform for analytics SAS can embed our analytic power in Hadoop Copyright 2016, SAS Institute Inc. All rights reserved. 29

31 Drastically changing consumer expectations Changes in consumer expectations Digital consumers expect to be recognized and treated consistently across touchpoints Adaptive experiences are no longer a differentiator but a baseline expectation New applications and devices are becoming new points of consumption for analytics Consumers want relevant and analytically driven interactions Organizations need to create insights that make a difference to the frontline interactions with customers in real time. Portable analytics assets run SAS analytics everywhere Apply analytics and decisioning in real-time Integrate seamlessly into customer facing thouchpoints Copyright 2016, SAS Institute Inc. All rights reserved. 31

34 Analytics CONCEPT BEHIND A CUSTOMER DECISION HUB CUSTOMER DECISION HUB Analytical models Events Context Scores Risk Potentials History Hadoop Copyright 2016, SAS Institute Inc. All rights reserved. 34 CDW Cloud POS Web Mobile Data

35 Analytics CONCEPT BEHIND A CUSTOMER DECISION HUB CUSTOMER DECISION HUB Marketing campaigns Service-Activities Sales programs Ad-hoc-actions Regular communications Contact strategies Hadoop Copyright 2016, SAS Institute Inc. All rights reserved. 35 CDW Cloud POS Web Mobile Data

36 Analytics CONCEPT BEHIND A CUSTOMER DECISION HUB CUSTOMER DECISION HUB Priorities Strategic decisions Contact rules Constraints Channel restrictions Budget-Limits Contact Permissions Hadoop Copyright 2016, SAS Institute Inc. All rights reserved. 36 CDW Cloud POS Web Mobile Data

37 How do we deliver this?

38 FOUNDATION SAS OVERVIEW Programming Environment (SAS Display Manager) or Point & Click (SAS Enterprise Guide), Web- Based (SAS Studio) PC or Server Base SAS (Scalable, Integrated Software designed for Data Access, Transformation & Reporting) Statistics (SAS/STAT) Optimization (SAS/OR) Forecasting (SAS/ETS) Reporting (SAS/GRAPH) SAS/FSP SAS/ACCESS Interface (Read, write & update data regardless of source or platform) SAS/CONNECT 4 th generation Programming Language Ready-to-use programs for data manipulation, information storage & retrieval, descriptive statistics & report writing Mainframe Relational Appliances PC Files Copyright 2016, SAS Institute Inc. All rights reserved. 38

39 TOOLS FOUNDATION SAS OVERVIEW REPORTING (Ad-hoc Reporting, Enterprise Business Intelligence, Visualization) ANALYTICS (Data Exploration, Data & Text Mining, Forecasting, Model Governance & Deployment) DATA (Data Integration & Data Quality, Scheduling, Lineage, Data Federation, Metadata Mgmt) Base SAS (Scalable, Integrated Software designed for Data Access, Transformation & Reporting) SAS Data Management SAS Data Loader for Hadoop SAS Enterprise Guide SAS Enterprise Miner SAS Forecast Server SAS Visual Analytics SAS Visual Statistics Statistics (SAS/STAT) Optimization (SAS/OR) Forecasting (SAS/ETS) Reporting (SAS/GRAPH) SAS/FSP SAS/CONNECT SAS/ACCESS Interface (Read, write & update data regardless of source or platform) Mainframe Relational Appliances PC Files 39

40 FOUNDATION SOLUTIONS TOOLS SAS OVERVIEW Financial Crimes Customer Intelligence Risk and Compliance Supply Chain REPORTING (Ad-hoc Reporting, Enterprise Business Intelligence, Visualization) Merchandising Create purpose built analytic applications Solve industry problems with a platform and applications ANALYTICS (Data Exploration, Data & Text Mining, Forecasting, Model Governance & Deployment) DATA (Data Integration & Data Quality, Scheduling, Lineage, Data Federation, Metadata Mgmt) Base SAS (Scalable, Integrated Software designed for Data Access, Transformation & Reporting) Statistics (SAS/STAT) Optimization (SAS/OR) Forecasting (SAS/ETS) Reporting (SAS/GRAPH) SAS/FSP SAS/CONNECT SAS/ACCESS Interface (Read, write & update data regardless of source or platform) Mainframe Relational Appliances PC Files Copyright 2016, SAS Institute Inc. All rights reserved. 40