Outrun Your Competition With SAS In-Memory Analytics Sascha Schubert Global Technology Practice, SAS

Transcription

1 Outrun Your Competition With SAS In-Memory Analytics Sascha Schubert Global Technology Practice, SAS

2 Topics AGENDA Challenges with Big Data Analytics How SAS can help you to minimize time to value with In-Memory Analytics SAS Viya

3 Big Data Analytics Why is it so important now? Data Computing Power Algorithms

4 Big Data Analytics BUSINESS APPLICATIONS

5 In the new world, it is not the big fish which eats the small fish, it s the fast fish which eats the slow fish. Klaus Schwab Founder and Executive Chairman World Economic Forum Copyr i g ht 2016, SAS Ins titut e Inc. All rights res er ve d.

6 Lost Value Data to Decisions Reduce Time to Decision Producing a new model or adjusting an existing model for the business often takes too long to meet fast changing markets. Value Complexity is added as many stakeholders are involved in the predictive analytics process. Big data is adding to the complexity. Implementation of a process model is needed to provide fast, repeatable and high-quality results Data Latency Modeling Latency Deployment Latency Decision Latency Time Lost Time

7 Decisions at Scale THE ANALYTIC LIFECYCLE PREPARE DEPLOY Lots of Data New Data Experimentation Fail Fast Test & Learn Interactive Iterative Innovation Flexibility Data Science EXPLORE Discovery & Development of Analytics MODEL ASK Deployment & Execution of Analytics MONITOR EXECUTE Regulated Automated Governed Embed Reliable Decisions Consistent Documented Actions IT

8 Factors to Speed up Data to Decisions Time Support for complete analytical lifecycle Standardized transparent processes Minimize data movement for big data volumes In-memory processing on modern distributed platforms Easy to use persona-based self service software Automation of repetitive steps

9 Bring SAS Processing to the Data SAS/Access to Big Data Extract data into SAS Push down SQL queries into data environment Analytics Server SQL SAS SAS In-Database Technologies Push SAS processing into data environment Run natively in data environment Analytics Server SAS In-DB Code SAS In-Memory Analytics SAS native distributed in-memory computing for fast advanced analytics In-memory data exchange Analytics Server SAS High Speed High Speed High Speed High Speed Network Network Data Data Data Traditional Operational Transformational

10 SAS In-Database Technologies SAS Scoring Accelerator Aster DB2 Pivotal Hadoop Netezza Oracle SAP HANA SAS Scalable Performance Data Server Teradata SAS Data Quality Accelerator Teradata Hadoop SAS In-Database Code Accelerator Hadoop Pivotal Teradata

11 CUSTOMER CASE STUDY COLLECTIONS MANAGEMENT Solution Approach : SAS In-Database Technologies DATA EXPLORATION M O D E L D E V E L O P M E N T MODEL DEPLOYMENT 40M records 84 SECONDS 12 min Score all 40 million records compared to the limit of in the past Reduced Data movement Increased data governance Better business results: $1M to $3M extra collections a month

12 Usability SAS In-Memory Analytics Offerings In-Memory Analytics Coding In-Memory Statistics Visual Data Mining and Machine Learning PROC hpbnet data = creditdata structure = markovblanket; model default = x1 LTV income age; selction = Y RUN; In-Memory Statistics High Performance Analytics Visual Data Mining and Machine Learning GUI Data Loader for Hadoop Visual Statistics Enterprise Miner & HPA Factory Miner Text Miner & Contextual Analysis Decision Manager Analytics in Action

13 SAS In-Memory Analytics - Execution Distributed Data and Software on Multiple Servers Data Scientist SAS In-Memory Machine Learning algorithms are designed to run on single machine (multi-threaded) or on a compute cluster

14 SAS In-Memory Analytics SINGLE MACHINE VERSUS MASSIVE PARALLEL PROCESSING

15 CUSTOMER CASE STUDY CUSTOMER BEHAVIOR MODELING Standard Data Mining Process Final model is based on a single analytical algorithm Neuronal Net (NN) 7 training iterations of the neuronal net take ~5 hours (~1.4 iterations/h.) One analyst can generate one model per day low productivity low confidence low model accuracy Model lift was 1,6 for top 10% High-Performance Data Mining Final model is based on comparison of several analytical algorithms (NN, SVM, logistic regression,...) 5000 training iterations of neural net take 70 minutes (~71,4 iterations/min.) One analyst can generate many models per day High productivity High confidence High model accuracy Model lift improved to 2,5 for top 10%

16 SAS Viya SAS Viya is a new, open analytic platform built for analytics innovation It is designed for all analytic professionals, regardless of skills or experience. It scales for data of any size, speed and complexity.

17 SAS Viya SAS VISUAL DATA MINING AND MACHINE LEARNING SAS Visual Data Mining and Machine Learning combines data wrangling, data exploration, visualization, feature engineering, and modern statistical, data mining, machine-learning and text analytics techniques all in a single, scalable in-memory processing environment SAS Viya.

18 SAS Viya SAS VISUAL DATA MINING AND MACHINE LEARNING K-means and K-modes Clustering Principal Component Analysis Logistic Regression Linear Regression Generalized Linear Models Nonlinear Regression Decision Trees Random Forest Gradient Boosting Neural Networks Support Vector Machines Factorization Machines Network Analytics/Community Detection Text Mining Boolean Rules Autotuning Discovery Data Deployment Assess Supervised Models Complete Score Code Multi Threaded Data Step DS2 SQL Variable Binning Variable Cardinality Analysis Sampling and Partitioning Missing Value Imputation Variable Selection Transpose

19 SAS Viya SAS VISUAL DATA MINING AND MACHINE LEARNING Hyperparamters Highly data dependent Related to model complexity Auto Tuning: Automate hyperparameters search and find the optimal set Maximize predictability on independent data set Aims to avoid over-fitting by controlling model complexity Creates more accurate models faster vs hand tuning SAS auto tuning leverages SAS optimization engines

20 SAS Viya SAS VISUAL DATA MINING AND MACHINE LEARNING SAS STUDIO - WEB-BASED USER INTE SAS Visual Data Mining and Machine Learning on SAS Studio

21 SAS Viya OPEN ACCESS TO SAS FROM JUPYTER NOTEBOOK SAS language APIs Other programming languages SAS Visual Data Mining and Machine Learning with Python Demo

22 SAS Viya SAS VIYA AND SAS 9 & It s an AND strategy Can co-exist on same hardware (physical or virtual) Data, models, and code can be accessed via bridges

23 SAS Viya MORE INFORMATION

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