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Transforming Business in a Digital Era with Big Data and Microsoft


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The socially integrated world, the rise of mobile, the Internet of Things - this explosion of data can be directed and used, rather than simply managed. That's why Big Data and advanced analytics are key components of most digital transformation strategies.

In the last year, Microsoft has made key moves to extend its data platform into this realm. Stalwart platforms like SQL Server and Excel join up with new PaaS offerings to make up a dynamic and powerful Big Data/advanced analytics ecosystem.

In this webinar, our experts covered:

-Why you should include Big Data and advanced analytics in your digital transformation strategy
-Challenges facing digital transformation initiatives
-What options the Microsoft toolset offers for Big Data (Hadoop) and advanced analytics
-How to leverage products and services you already own for your digital transformation

Published in: Technology
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Transforming Business in a Digital Era with Big Data and Microsoft

  1. 1. Transforming Business in a Digital Era with Big Data and Microsoft
  2. 2. 2 Perficient is a leading information technology consulting firm serving clients throughout North America. We help clients implement business-driven technology solutions that integrate business processes, improve worker productivity, increase customer loyalty and create a more agile enterprise to better respond to new business opportunities. ABOUT PERFICIENT
  3. 3. 3 PERFICIENT PROFILE Founded in 1997 Public, NASDAQ: PRFT 2014 revenue $456 million Major market locations: Allentown, Atlanta, Ann Arbor, Boston, Charlotte, Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Lafayette, Milwaukee, Minneapolis, New York City, Northern California, Oxford (UK), Southern California, St. Louis, Toronto Global delivery centers in China and India >2,600 colleagues Dedicated solution practices ~90% repeat business rate Alliance partnerships with major technology vendors Multiple vendor/industry technology and growth awards
  4. 4. 4 INDUSTRIES Healthcare Financial Services Life Sciences Consumer Markets Automotive & Transportation High Tech Telecom Energy & Utilities Manufacturing Media & Entertainment PORTAL Portal Frameworks Search Security Web Analytics Web Content Management Social & Collaboration Mobility Experience Design INTEGRATION Integration Frameworks Cloud Architecture Reference Architecture Application Integration Enterprise Application Integration Service Oriented Architecture Process & Content Integration Business Process Management Complex Event Processing Rules Engines DATA & CONTENT Business Analytics Business Intelligence Predictive Analytics Reporting Structured Data Management Data Integration, Quality & Governance Enterprise Data Warehouse Master Data Management Product & Information Management Unstructured Data Management Big Data Content Intelligence Content Management Enterprise Search CUSTOMER EXPERIENCE Customer 360 Multi Channel Enablement Relationship Management Social Engagement Commerce Marketing Strategy Implementation Order Management Supply Chain Management Service & Support Managed Hosting Sales & Service Support Customer Service, Sales Force Automation Experience Design Strategic Roadmaps & Envision Workshops User Research & Metrics Analysis Creative & Interaction Design Custom & Responsive UI Development Digital Marketing Search Engine Marketing Online Advertising Content Strategy Conversion Optimization Management Consulting BUSINESS OPERATIONS Corporate Performance Management Budgeting, Forecasting & Planning Business Analysis & Predictive Analytics Enterprise Business Solutions Oracle EBS Vertex Tax Solutions Human Resource Solutions Employee Portals Human Resource Management Talent Management Enterprise Social Platforms Social Strategy Lync Unified Communications Office 365 Management Consulting OUR SOLUTIONS PORTFOLIO
  6. 6. 6 SPEAKERS Shankar RamaNathan Perficient Senior Enterprise Architect, Strategic Advisors Team Andrew Tegethoff Perficient Practice Lead, Microsoft Business Intelligence
  7. 7. 7 7  Introduction  Digital Transformation & Big Data  Big Data Challenges  Big Data & Microsoft  In the Cloud with HDInsight  In the Data Center with APS AGENDA
  8. 8. 8 DIGITAL TRANSFORMATION Source: McKinsey Global Survey
  9. 9. 9 DIGITAL TRANSFORMATION Source: McKinsey Global Survey
  10. 10. 10 DIGITAL TRANSFORMATION Source: McKinsey Global Survey
  11. 11. 11 BIG DATA CHALLENGES: How to get value from Big Data? Governance & Security Concerns/ Issues Analytical / Technology Talent Integrating different sources of Data Integrating Enterprise Data with Big Data Defining Strategy Funding
  12. 12. 12 VALUE CREATION FACTORS Source: McKinsey Global Survey
  14. 14. 14 Customer Databases Service Records Text Documents Product Databases POS Data Weblogs Social Media Clickpaths Callcenter Payment Database CUSTOMER EXPERIENCE Omni Channel Strategy Integrating Enterprise Data Big Data: At rest & in motion
  15. 15. 15 BIG DATA RISKS AND OPTIONS Not able to show business value Difficulty in finding the resources IT/HW/SW installation bottle-neck
  16. 16. 16 BIG DATA PLAYERS
  17. 17. 17 BIG DATA PLAYERS
  18. 18. 18 BIG DATA & MICROSOFT Andrew Tegethoff, Microsoft BI Practice Lead
  19. 19. 19 19 Consulting on strategic and tactical aspects of BI with the Microsoft Data Platform MICROSOFT BUSINESS INTELLIGENCE
  20. 20. 20 20 • Volume o Terabytes, petabytes, exabytes • Velocity o How much data is created every minute? • Variety o Social, Web, Internet of Things, etc. BIG DATA
  21. 21. 21 21 BIG DATA What types of data are we talking about? People to People Online forums Social networks Blogs SMS threads Email threads People to Machine E-commerce Bank cards Credit cards Mobile devices Digital TV Machine to Machine Medical devices GPS devices Bar code scanners Sensors Surveillance cams
  22. 22. 22 22 An open source framework for the storage and processing of very large data sets. The Hadoop ecosystem consists of many additional tools that perform functions like: • Resource management • Extract, Transform and Load (“ETL”) and/or Extract, Load and Transform (“ELT”) • Full text search • Workflow scheduling • SQL querying ENTER HADOOP
  23. 23. 23 23 WHAT CAN HADOOP DO? • Allow you to keep pace with more volume, more variety, and greater velocity of data. • Allow you to store all of data in its raw form, so you can ask questions later that were not thought of when the data was captured. • Enable you to ask questions of your data that previously couldn’t be answered – as well as capture data that previously couldn’t be captured.
  24. 24. 24 24 INTRODUCING HDINSIGHT • Key part of Microsoft’s Big Data/Hadoop story • “PaaS” option for cloud Hadoop • Azure wraps an Apache Hadoop implementation created by Hortonworks and Microsoft partnership • Uses Azure Storage (Tables) for scalable “NoSql” cloud storage • Integrates Big Data into existing applications, BI solutions, reporting environments, Excel
  25. 25. 25 25 • Establish an Azure Storage account • Set up an HDInsight cluster • Account cost relates directly to size of cluster & uptime! • Upload data • Using native JavaScript, Hadoop command line, Sqoop connection from SQL Server or Azure SQL Database or a raft of third-party tools • Connect and analyze • Use SQL Server and/or Excel via ODBC, • Integrate with applications via Hadoop.NET or Azure SQL Database via Sqoop HOW DOES IT WORK?
  26. 26. 26 26 CLOUDERA ON AZURE • CDH – Cloudera Hadoop distribution • Installed on Azure Virtual Machines running Linux • Cloudera’s preferred cloud platform • “IaaS” option for cloud-based Hadoop
  27. 27. 27 27 WHERE DOES IT FIT?
  28. 28. 28 28 ADVANCED ANALYTICS WITH AZURE ML CLOUD-BASED DATA SCIENCE & PREDICTIVE ANALYTICS • Fully-managed Azure offering • Browser-based development environment • Deploy predictive models as a Web Service with Azure ML API • Data sources: Use HDInsight, Azure Storage, local data files, HTTP • Includes best in Class Algorithms from Xbox & Bing • Built-in support for the R language, includes over 350 packages, or “BYO” R code • Deploy in minutes
  30. 30. 30 30 Connect to an HDInsight cluster using Power Query Extract data into Power Pivot, join with other datasets from a variety of sources to create powerful mashups Easily translate Big Data into compelling visualizations with Power View ANALYZE BIG DATA WITH POWER BI
  31. 31. 31 31 CLOUD HADOOP: THE VALUE PROP • Enables Big Data/Hadoop proposition, but on a scalable pay-as- you-go basis • Enhances analytical capability over “loosely structured” data • Expands scope and type of analysis possible across a wide variety of use cases • Integrates easily with existing data systems
  32. 32. 32 32 • Turnkey, on-premises Big Data analytics appliance • Relational Data • Massively Parallel Processing (MPP) with SQL Server Parallel Data Warehouse (PDW) • Non-Relational Data • 100% Hadoop installation via on-premises version of HDInsight • Seamless Querying • Polybase – query Big Data using SQL • Performance • In-Memory Columnstore • Scale up to 6 PB ANALYTICS PLATFORM SYSTEM (APS)
  33. 33. 33 33 APS ARCHITECTURE
  34. 34. 34 34 – Massively Parallel Processing (MPP) • Fundamentally different than typical RDBMS Symmetric Multi-Processing (SMP) • “Shared nothing” architecture • Large number of dedicated processors • Every CPU has its own storage – Better query and load performance • Amplified by inclusion of In-Memory Columnstores – Fault-tolerant, inexpensive, yet comprehensive VLDW solution SQL SERVER PDW
  35. 35. 35 35 ONCE AGAIN… HDInsight – Fundamentally the same product, but deployed within the APS appliance – 100% Apache Hadoop – Query with SQL via Powerbase – Fully integrated with Microsoft platform • User authentication with ADFS • High availability • WS Failover Clustering
  36. 36. 36 36 ON-PREMISES HADOOP: THE VALUE PROP • Relational and non-relational data management in one turnkey solution • Lowest cost per TB for a data warehouse appliance in the industry • Hardware choices: Dell, HP, Quanta • Integrates into Windows infrastructure • Performance, security, and scalability
  37. 37. 37 37 PLANNING FOR THE FUTURE • Establishing target problems • Identifying resources (i.e. Azure, on premises) • Defining and acquiring required skillsets • Bringing it all together
  38. 38. 38 38 POLL Where do you feel you need help with Big Data technology? a. Establishing a business case b. Transitioning from POC to production c. Establishing a Solution Architecture d. Hadoop/Open Source toolset e. Microsoft toolset f. Other
  39. 39. 39 WHAT’S NEXT Follow along: Next up: Microsoft Ignite May 4-8 | Chicago, IL Booth 330 Download: Guide to IT Modernization