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Hadoop Perspectives for 2017

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As users gain more experience with Hadoop, they are building on their early success and expanding the size and scope of Hadoop projects. Syncsort’s third annual Hadoop Market Adoption Survey reflects the fact that Hadoop is no longer considered a technology for the future as it was when we first started conducting this research. Get an in-depth look at the survey results and five trends to watch for in 2017. You’ll also learn: • The best uses for Hadoop in 2017 – real-word examples of how Enterprises are realizing the value of Big Data • Solutions to help you address the challenges enterprises still face in employing Hadoop • What the future of Hadoop means for your business

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Hadoop Perspectives for 2017
Simplifying Big Data Integration
Goals of the Modern Data Architecture • Centralize all your data • Turn raw data into insights • Maintain governance, compliance and security standards • Eliminate complexities within IT
Global Leader in Big Iron to Big Data Solutions 4Syncsort Confidential and Proprietary - do not copy or distribute Deep engineering and go-to-market relationships with strategic partners in Big Iron and Big Data ecosystems Marquee global customer base of leaders and emerging businesses across all major industries PEARL RIVER, NY SINGAPORE JAPAN Trusted Industry Leadership Providing world-class data management software to large enterprises for nearly 50 years with a focus on customer value and unparalleled support Lower Cost, Higher Performance Our fast, efficient software helps power business and operational analytics while optimizing resource utilization to dramatically reduce the cost of managing mainframe and legacy systems Connecting Big Iron To Big Data Our solutions address the complex set of requirements for delivering rich data from mainframe and legacy sources to Big Data environments
Our Strategy: Simplify Big Data Integration • Deploy on premise or in the cloud • Choose among multiple execution frameworks – Hadoop, Spark, Linux, Unix, Windows • Integrate streaming and batch data with a single data pipeline for innovative applications, like IoT • Future-proof applications to avoid re-writing jobs in order to take advantage of innovations in new execution frameworks • Access and integrate ALL enterprise data sources – including mainframe – for advanced analytics
Simplify Big Data Integration with Syncsort 6Syncsort Confidential and Proprietary - do not copy or distribute Access Integrate Comply Simplify Get best in class data ingestion capabilities for Hadoop. Mainframes, RDBMS, MPP, JSON, Parquet, Avro, ORC, NoSQL, Kafka and more. Single interface for streaming and batch processes. Single data pipeline for all enterprise data, batch or streaming. Secure data access, data governance and lineage. Seamless integration with Kerberos, Apache Ranger, Apache Ambari, Cloudera Manager, Cloudera Navigator and Sentry. Design once, deploy anywhere & insulate your organization from rapidly changing eco- system. Future proof your applications for new compute frameworks, on premise or in the cloud.
Hadoop Perspectives for 2017
Polling Question What stage of Hadoop implementation is your organization in? – Researching/Evaluating – Proof of Concept/Pilot – In production – None of the above
About the Survey – Who Responded 270+ IT decision makers 36% with revenue of $1B+ Financial Services 22% Insurance 7% Data Services 5% Government 7% Healthcare 10% Non-profit 3% Retail 8% Software/SaaS 5% Telco 8% Information Technology 16% Travel/Hospitality 3% Other 6% INDUSTRY BI/Data Analyst 12% CIO/CTO/ COO 7% Data Architect 18% Data Scientist 9% Developer 17% Other IT Exec 5% IT Manager 21% Other 11% ROLE
Compute Frameworks and Cloud Deployment Multiple frameworks are the norm – 54% use more than one framework Migration away from MapReduce, toward Spark More organizations are deploying on premises – but almost a third have a hybrid deployment 62% 40% 15% 11% 30% 10% 2% 4% 38% 52% 24% 13% 4% 8% 22% 6%
Polling Question Do you plan on changing execution frameworks in the next 12 months? – Yes – No – I don’t know
Data Sources Traditional data sources are most popular for filling the data lake Newer sources like streaming data and NoSQL databases on the rise Even more pronounced for Financial Services & Insurance: – 2x more likely to ingest MF data – 20% more likely to pull data from RDBMS
Mainframe & Hadoop 71% of the Fortune 500 relies on mainframe data to conduct 30 billion business transactions a day – 96 of the world’s top 100 banks – 9 out of the world’s 10 largest insurance companies – 23 out of the top 25 U.S. retailers New solutions make it easier to take advantage of this critical data with Hadoop HOW VALUABLE IS BEING ABLE TO ACCESS/INTEGRATE MAINFRAME DATA INTO HADOOP?
The Role of Hadoop Hadoop & the Data Warehouse – 70% of all EDW’s are performance and capacity constrained – Shifting ELT workloads to Hadoop is a popular remedy – However, most don’t expect Hadoop to replace their existing EDWs Nearly half of respondents see Hadoop as a: – Way to power better, faster analytics – Cost effective storage/data archive strategy
Top Use Cases for Hadoop
Polling Question What are the top use cases for Hadoop in your organization? – Active archive – Advanced/predictive analytics – Data discover/visualization – ETL – Clickstream/social media data analysis – Internet of Things – EDW/Mainframe offload – Operational analytics – Real-time analytics
Significant Business Benefits Expected
Polling Question What is the #1 challenge/barrier for implementing Hadoop in your organization? – Lack of skills/staffing – Cost – Connectivity to existing data sources/apps – Rapid change in tools/technology – Difficulty moving data in/out of Hadoop – Uncertainty
Top 3 Challenges/Barriers to Hadoop Adoption Skills/Staffing: – 58% of respondents ranked it as a significant challenge – Top challenge reported for the 3rd year in a row Rapid Change: – 53% of respondents ranked it as a significant challenge – Difficulty keeping up with evolving compute frameworks and Hadoop- related tools Connectivity: – 48% of respondents ranked it as a significant challenge 1 2 3
What’s coming in 2017 1 2 3 4 5 Success begets success Big Data insights will take their seat in the boardroom Data governance grows in importance Tools will become more flexible to adapt to changing and hybrid environments Organizations will seek simplicity to sustain & scale early success
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Hadoop Perspectives for 2017

  • 2. Simplifying Big Data Integration
  • 3. Goals of the Modern Data Architecture • Centralize all your data • Turn raw data into insights • Maintain governance, compliance and security standards • Eliminate complexities within IT
  • 4. Global Leader in Big Iron to Big Data Solutions 4Syncsort Confidential and Proprietary - do not copy or distribute Deep engineering and go-to-market relationships with strategic partners in Big Iron and Big Data ecosystems Marquee global customer base of leaders and emerging businesses across all major industries PEARL RIVER, NY SINGAPORE JAPAN Trusted Industry Leadership Providing world-class data management software to large enterprises for nearly 50 years with a focus on customer value and unparalleled support Lower Cost, Higher Performance Our fast, efficient software helps power business and operational analytics while optimizing resource utilization to dramatically reduce the cost of managing mainframe and legacy systems Connecting Big Iron To Big Data Our solutions address the complex set of requirements for delivering rich data from mainframe and legacy sources to Big Data environments
  • 5. Our Strategy: Simplify Big Data Integration • Deploy on premise or in the cloud • Choose among multiple execution frameworks – Hadoop, Spark, Linux, Unix, Windows • Integrate streaming and batch data with a single data pipeline for innovative applications, like IoT • Future-proof applications to avoid re-writing jobs in order to take advantage of innovations in new execution frameworks • Access and integrate ALL enterprise data sources – including mainframe – for advanced analytics
  • 6. Simplify Big Data Integration with Syncsort 6Syncsort Confidential and Proprietary - do not copy or distribute Access Integrate Comply Simplify Get best in class data ingestion capabilities for Hadoop. Mainframes, RDBMS, MPP, JSON, Parquet, Avro, ORC, NoSQL, Kafka and more. Single interface for streaming and batch processes. Single data pipeline for all enterprise data, batch or streaming. Secure data access, data governance and lineage. Seamless integration with Kerberos, Apache Ranger, Apache Ambari, Cloudera Manager, Cloudera Navigator and Sentry. Design once, deploy anywhere & insulate your organization from rapidly changing eco- system. Future proof your applications for new compute frameworks, on premise or in the cloud.
  • 8. Polling Question What stage of Hadoop implementation is your organization in? – Researching/Evaluating – Proof of Concept/Pilot – In production – None of the above
  • 9. About the Survey – Who Responded 270+ IT decision makers 36% with revenue of $1B+ Financial Services 22% Insurance 7% Data Services 5% Government 7% Healthcare 10% Non-profit 3% Retail 8% Software/SaaS 5% Telco 8% Information Technology 16% Travel/Hospitality 3% Other 6% INDUSTRY BI/Data Analyst 12% CIO/CTO/ COO 7% Data Architect 18% Data Scientist 9% Developer 17% Other IT Exec 5% IT Manager 21% Other 11% ROLE
  • 10. Compute Frameworks and Cloud Deployment Multiple frameworks are the norm – 54% use more than one framework Migration away from MapReduce, toward Spark More organizations are deploying on premises – but almost a third have a hybrid deployment 62% 40% 15% 11% 30% 10% 2% 4% 38% 52% 24% 13% 4% 8% 22% 6%
  • 11. Polling Question Do you plan on changing execution frameworks in the next 12 months? – Yes – No – I don’t know
  • 12. Data Sources Traditional data sources are most popular for filling the data lake Newer sources like streaming data and NoSQL databases on the rise Even more pronounced for Financial Services & Insurance: – 2x more likely to ingest MF data – 20% more likely to pull data from RDBMS
  • 13. Mainframe & Hadoop 71% of the Fortune 500 relies on mainframe data to conduct 30 billion business transactions a day – 96 of the world’s top 100 banks – 9 out of the world’s 10 largest insurance companies – 23 out of the top 25 U.S. retailers New solutions make it easier to take advantage of this critical data with Hadoop HOW VALUABLE IS BEING ABLE TO ACCESS/INTEGRATE MAINFRAME DATA INTO HADOOP?
  • 14. The Role of Hadoop Hadoop & the Data Warehouse – 70% of all EDW’s are performance and capacity constrained – Shifting ELT workloads to Hadoop is a popular remedy – However, most don’t expect Hadoop to replace their existing EDWs Nearly half of respondents see Hadoop as a: – Way to power better, faster analytics – Cost effective storage/data archive strategy
  • 15. Top Use Cases for Hadoop
  • 16. Polling Question What are the top use cases for Hadoop in your organization? – Active archive – Advanced/predictive analytics – Data discover/visualization – ETL – Clickstream/social media data analysis – Internet of Things – EDW/Mainframe offload – Operational analytics – Real-time analytics
  • 18. Polling Question What is the #1 challenge/barrier for implementing Hadoop in your organization? – Lack of skills/staffing – Cost – Connectivity to existing data sources/apps – Rapid change in tools/technology – Difficulty moving data in/out of Hadoop – Uncertainty
  • 19. Top 3 Challenges/Barriers to Hadoop Adoption Skills/Staffing: – 58% of respondents ranked it as a significant challenge – Top challenge reported for the 3rd year in a row Rapid Change: – 53% of respondents ranked it as a significant challenge – Difficulty keeping up with evolving compute frameworks and Hadoop- related tools Connectivity: – 48% of respondents ranked it as a significant challenge 1 2 3
  • 20. What’s coming in 2017 1 2 3 4 5 Success begets success Big Data insights will take their seat in the boardroom Data governance grows in importance Tools will become more flexible to adapt to changing and hybrid environments Organizations will seek simplicity to sustain & scale early success