Manoj Kolhe - Presentation - ITW_PPT_Big_Data_Testingv1.6
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The document discusses the concept of big data, emphasizing its high volume, variety, and velocity, which present challenges in data management and analysis. It outlines a case study in the telematics domain, showcasing a solution that improved predictive analytics efficiency and marketing campaign effectiveness through advanced technologies like MongoDB and predictive analytics software. Additionally, it details the testing landscape for big data environments, including data validation strategies and necessary technologies for successful implementation.
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Manoj Kolhe - Presentation - ITW_PPT_Big_Data_Testingv1.6
- 1. LOGO www.unicomlearning.com Manoj Kolhe Project Lead, Testing Service Line, L&T Infotech India Testing Week 2013 Big Data Testing December 10, 2013 Mumbai www.unicomlearning.com www.nextgentesting.org
- 2. www.unicomlearning.com www.nextgentesting.org Introduction to Big Data Web Logs Social N/W Data Transactional Data Statistical Data Database Cluster Database of Databases Big Data BI Reporting Trend Analysis Decision Making
- 3. www.unicomlearning.com www.nextgentesting.org Wikipedia: Big Data term is applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process within a tolerable elapsed time. Gartner - Big Data are high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization Gartner ..the real issue is making sense of big data and finding patterns in it that help organizations make better business decisions. “look for patterns that support business decisions in what we call Pattern-Based Strategy” Forrester Opportunities to improve the bottom line exist in a flood of information; however, gaining insight from data becomes challenging as it grows extremely large. Emerging technology applies the power of distributed, virtual computing to the problem of large data, SAS With Big Data Analytics, organizations can make better and faster decisions based not only on what has happened, but what will happen next. They can also predict the best possible outcome while remaining agile in swiftly changing times Defining Big Data
- 4. www.unicomlearning.com www.nextgentesting.org How Big is Big data? 175 million tweets a day 465 million user accounts 30+ PB User Data 100TB daily uploads 50 billion user photos 20+ PB Daily Data 300 billion videos Total runtime 47 million years 48 hrs of video each minute of the day 5 billion users are calling, texting, browsing data 2.9 millions of mails exchanged every second 1.3 Exabyte's ~1018 bytes Popular 5Vs: Big Data • Volume • Variety • Velocity • Viability • Value 90% of the data in the world today has been created in the last two years alone
- 5. Market Statistics & Applications of Big Data www.unicomlearning.com www.nextgentesting.org
- 6. www.unicomlearning.com www.nextgentesting.org Big Data – Use Case Case Study – Telematics Domain Objectives Create a state-of-the-art analytic environment to support and fuel fast growing telematics industry Increase operational efficiency Solution Built a comprehensive scalable and reliable service platform to support an end-to-end analytic environment everything from operational data to robust predictive analytic applications Technology Implemented MongoDB Enterprise Service Bus Big Data predictive analytics software Outcome Reduced end-to-end predictive analytics process from months to days Improved marketing campaign effectiveness with 65% model accuracy and efficacy
- 7. www.unicomlearning.com www.nextgentesting.org Traditional RDBMS vs NoSQL…. RDBMS NoSQL Feature Row-Column & Structured Semi-structured & Unstructured in Parallelism – Batch processing Scalability Vertical by adding systems Horizontal by replicating nodes Data Handling / Extraction Slower for large data volumes in analytical – Partitioning Fast access in both operational and analytical - Sharding Price Mostly proprietary e.g. Oracle, DB2, SQL Server Open Source e.g.Hadoop, CloudEra, Amazon, Hortonworks
- 8. Big Data – Test Environment www.unicomlearning.com www.nextgentesting.org Test Environment Setup • Infrastructure: • Cluster Setup – Evaluate Data nodes • Software / Platform • File System, NoSQL DB • Test Data • Off peak hours traffic testing • Staging environments / Scaled down models • Historical Data / Test data generation using utilities • Test Infrastructre • Test strategy, testing release cycle • Volume of data consideration • 3rd party tools • Load Simulators • jMeter for multi-threaded users • Load simulation using Cloud • Monitoring • Hadoop Performance Monitoring • ECL Watch (HPCC)
- 9. www.unicomlearning.com www.nextgentesting.org Testing Requirements in Big Data Logging Data Data Streams Social Data Traditional RDBMS Store Process Analyze Reporting Hadoop HDFS Enterprise Data Warehouse Big Data Analytics BI Reporting Processed Data Pre-Hadoop Validation 1 HDFS Data Validation 2 ETL Data Validation 3 Reports Data Testing 4 Ref: Infosys Big Data Solutions
- 10. Testing Approach for Data Validation www.unicomlearning.com www.nextgentesting.org Data Loading in HDFS Unstructured Data Structured Data HDFS Managing the data Processed Data Data Validation Expected Results 1 2 3 4
- 11. www.unicomlearning.com www.nextgentesting.org Testing Landscape •Acquire all available data ACQUIRE •Organize and Clean data with parallel processing ORGANIZE •Analyze all data, at once ANALYZE •Take business decisions based on active data BUSINESS USE Tapping unused , new datasets Build new relationship , understanding Data driven business decisions
- 12. www.unicomlearning.com www.nextgentesting.org Testing Landscape – Acquire •Acquire all available data Acquire •Organize and Clean data with parallel processing Organize •Analyze all data, at once Analyze •Take business decisions based on active data Business Use Data Validation • Data Comparison • Extraction of right data • HDFS loading • Data replication
- 13. www.unicomlearning.com www.nextgentesting.org Testing Landscape – Organize •Acquire all available data Acquire •Organize and Clean data with parallel processing Organize •Analyze all data, at once Analyze •Take business decisions based on active data Business Use Data Validation • Data Comparison • Extraction of right data • HDFS loading • Data replication MR Job Validation • MR Job Logic • Aggregation and consolidated data • Job Output against source files
- 14. www.unicomlearning.com www.nextgentesting.org Testing Landscape – Analyze •Acquire all available data Acquire •Organize and Clean data with parallel processing Organize •Analyze all data, at once Analyze •Take business decisions based on active data Business Use Data Validation • Data Comparison • Extraction of right data • HDFS loading • Data replication MR Job Validation • MR Job Logic • Aggregation and consolidated data • Job Output against source files Data Transformation • Transformation Logic • Data cleansing • Data transfer • Data integrity
- 15. www.unicomlearning.com www.nextgentesting.org Testing Landscape – Business Use •Acquire all available data Acquire •Organize and Clean data with parallel processing Organize •Analyze all data, at once Analyze •Take business decisions based on active data Business Use Data Validation • Data Comparison • Extraction of right data • HDFS loading • Data replication MR Job Validation • MR Job Logic • Aggregation and consolidated data • Job Output against source files Data Transformation • Transformation Logic • Data cleansing • Data transfer • Data integrity Reports Definition • Report data validation • OLAP cube testing • Dashboard testing
- 16. www.unicomlearning.com www.nextgentesting.org Big Data Testing Readiness… People Training Certifications Knowledge Base Process Data Centric Testing Process Risk Based Testing Approach Good Practices Knowledge TDM Test Data Generation Data Masking Requirements Data Profiling & Extraction Utilities Technology Non-traditional automation End to End testing Adaptability to existing solutions
- 17. Organized by UNICOM Trainings & Seminars Pvt. Ltd. [email protected] Speaker name: Manoj Kolhe Email ID: [email protected] www.unicomlearning.com Thank You www.nextgentesting.org