Data Analytics. Nagesh Madhwal Client Solutions Director, Consulting, Southeast Asia, Dell EMC

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2 Data Analytics Nagesh Madhwal Client Solutions Director, Consulting, Southeast Asia, Dell EMC

3 Last 15 years IT-centric Traditional Analytics Traditional Applications Rigid Infrastructure Internet Next 15 years Business-centric Prescriptive Analytics Cloud-Native Applications Agile Infrastructure Internet of Everything 3 Dell - Internal Use - Confidential

4 Evolution of Workloads 4 Dell - Internal Use - Confidential

5 Your business must evolve. Future success is achieved by unlocking ALL DATA.

6 When it comes to Applications and Data Analytics TIME is everything. 6 Dell - Internal Use - Confidential

7 Value The Power of Now Business Event Moment of Impact Data Captured Real time Batch Big Data Intelligence Delivered Decision Taken Opportunity Missed Opportunity Too Late To Take Action 7 of Y Dell - Internal Use - Confidential Time

8 Traditional Analytics Reactive and slow Limited to static data Restricted sources and access 8 Dell - Internal Use - Confidential

9 Traditional.. Source Systems Analytics Reporting ETL Data Warehouse Data Marts Sources 1 to x Batch Data Sources Existing DBs, ERP Staging Transform ation Files 9 Dell - Internal Use - Confidential

10 Traditional ODS Analytics Reporting Source Systems ETL Data Warehouse Data Marts Sources 1 to x Batch Data Sources Existing DBs, ERP Staging ETL Transform ation Files ETL 10 Dell - Internal Use - Confidential

11 Modern Analytics Deliver anywhere, anytime analytics Analyze ALL data Empower your end users 11 Dell - Internal Use - Confidential

12 Structured Static Schema RDBMS/EDW Managed using SQL data types: numeric, currency, alphabetic, name, date, address Sources: ERP CRM SCM POS Use Cases /APPS The Data Lake Hive HAWQ Kafka Impala Flume Sqoop BigSQL Spark Streaming Application-Integrated Protocols Unstructured Dynamic Schema Hadoop Eco Sys Managed using NoSQL file types: videos, pdf, ppt, mp3, doc, , pics Sources: Social IOT Text Geo Media 12 ETL Offload Analytics as a Service Data Science Decision Support Data Visualization Executive Reporting Predictive Modeling Threat Analysis Dell - Internal Use - Confidential 12

13 Modern Data Lake Environment BI / DWH Environment All Data Fed Into The Data Lake Data Prep & Enrichment ETL HADOOP DATA LAKE ISILON SCALE OUT NAS STORAGE DWH MPP Active Archive Analytics Sandbox - Production - Predictable Load - SLA Drive - Heavily Governed - Standard Tools Analytics / Sandbox Environment - Exploratory, Ad Hoc - Unpredictable Load - Experimentation - Loosely Governed - Best Tools 13 Foundation of your Data Management and Analytics Dell - Internal Use - Confidential Architecture

14 Reference Architectures APPLICATIONS STATISTICAL MODELING/NLP SEARCH/INDEX EXPLORATION BI RDBMS STREAM CEP DATA LAKE (HADOOP) DATA WAREHOUSE SOCIAL MEDIA TRANSFORM ORGANIZE MANAGE/ CATALOG SQL ON HADOOP 3 rd PARTY MACHINE IOT ENTERPRISE LOG ANALYSIS NEAR REAL-TIME MODELS MAY TAKE HOUR OR DAYS QUERIES MAY RETURN IN SECONDS OR MINUTES SECONDS 14 Dell - Internal Use - Confidential

15 Value Big Data Journey To BDaaS Big-Dataas-a-Service Departmental Multi-Tenant Hadoop and Spark Deployment On/Off Premise Prototyping Dev/Test and Pre-Production Lifecycle Management Template Libraries, Shared Data Across Clusters, Rapid Prototyping and Evaluation Multiple Hadoop Distros, Spark, Transient Workloads Hadoop and Spark in a Secure Production Environment Performance, Security, Capacity Prioritization, Compute/ETL Offload, Separate Compute/Storage Improve Utilization, Scaling, Consistent Data Dev/Test/Stage/QA/UAT Multi-Tenancy, Self-Service, Logs, APIs, Tenant/Admin Controls, Shared Data Lake with Access Controls Support Multiple LOBs, Dynamic Resource Management/QoS, Automation Heterogeneous Production Environments, Diverse Tenants and User Groups Dev / Test Lab < 20 Nodes 20+ Nodes 50+ Nodes Agility Control BDaaS 15 Dell - Internal Use - Confidential

16 Multi-Tenant Big-Data-as-a-Service MARKETING R&D MANUFACTURING 360 Customer View Log Analysis Predictive Maintenance Multiple lines of business, multiple user groups Multiple use cases Compute Compute Prod Dev/Test Isolation POC Isolation Prod Dev/Test Multiple ecosystem products (including non-hadoop, BI/ETL tools) Compute isolation between tenants Shared, Centrally Managed Server Infrastructure Multiple environments per tenant Data Isolation Data/Storage Data Isolation MARKETING R&D MANUFACTURING Multiple versions and/or distributions Data isolation by tenant (incl. ability to physically isolate storage) 16 Dell - Internal Use - Confidential

17 Range of solutions 44% of organizations still struggle with how to approach Big Data Analytics Integration Infrastructure 17 Dell - Internal Use - Confidential S e r v i c e s

18 Data Analytics Journey 18 Dell - Internal Use - Confidential

19 Big Data Systems VxRail VxRack Vblock XC Series 19 Dell - Internal Use - Confidential

20 Big Data Foundations Servers Storage Networking Software 20 Dell - Internal Use - Confidential

21 Big Data Solutions Reference Architectures Engineered Solutions Customized Designs 21 Dell - Internal Use - Confidential

22 Global Services ASSESS PROVE DEPLOY BUSINESS Big Data Vision Workshop Big Data Proof of Value Big Data Applied Analytics Implementation DELL EMC Big Data Portfolio Implementation TECHNOLOGY Big Data Technology Advisory Big Data Proof of Technology Big Data Technology Implementation 22 Dell - Internal Use - Confidential

23 Example of a Big Data Workshop Subject Workshop Objective Workshop Vision Details To understand the key business initiatives and requirements for big data in order to understand where and how to start the big data journey How to become data driven through the use of big data and analytics Workshop Duration Half Day or 1 Day on customer site Workshop Agenda 1) Business & IT Goals 2) Business Initiatives 3) Current Environment Review 4) Use Cases 5) Data Sources Review 6) Data Science / Analytics / BI Requirements Recommended types of participants: IT and Business Users Expected Outcomes 1) List of business opportunities and use cases 2) Business Value and Feasibility 3) Identify and prioritize data sources mapped with use cases 4) Prioritized used cases with potential business value and impediments 5) Document workshop results 6) Big Data Technology Roadmap with clear next steps Next Step After Workshop Dell EMC Workshop Team 23 of Y Dell - Internal Use - Confidential Proof of Value (POV) or Proof of Technology (POT) Head of Big Data Practice SEA, Head of Consulting SEA, Dell EMC Account / Sales Manager

24 Customer Success Stories 24 Dell - Internal Use - Confidential

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