Wsta event 3 19-2015.v6
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1) The document discusses how financial services companies can better manage large amounts of data (big data) through automation and flexible platforms. 2) It recommends that companies derive their big data strategy from corporate strategy and educate workforces. It also stresses the importance of failing and iterating quickly. 3) The document promotes Attunity's data management solutions for automating tasks like data integration, replication, and movement between data warehouses and Hadoop in order to more efficiently analyze data and accelerate innovation.
Wsta event 3 19-2015.v6
- 1. Attunity Better Data Management For Faster Innovation Wall Street Technology Association March 19, 2015 Kevin Petrie Senior Director and Technology Evangelist
- 2. The Big Data Mandate For Financial Services “Operations for profit should be based not on optimism but on arithmetic.” - Benjamin Graham, Value Investor
- 3. State Of The Big Data Business In Finance Adoption Drivers Proliferating Data Mobile Apps IT Cost Declines Disruptive Competition Customer Churn Upside Customer Retention Improved Risk Analysis New Customers & Products Stronger Governance Better Trades
- 4. Key Use Cases For Financial Services Smart Payments | Smart Cards | ATM Monitoring Digital Signage | Data Lineage & Governance | Compliance Algorithmic Trading | Risk Management | Fraud Protection
- 5. Big Data Best Practices For Financial Services • Derive Big Data Strategy From Corporate Strategy, Not Vice Versa • Educate Workforces • Fail And Iterate Fast • Invest In Flexible Platforms • Automate Data Management Tasks
- 6. Your Competitors Are Taking The Plunge Unclear Reduce Cost Increase Revenue Both 2% 20% 23% 55% Big Data Project Drivers 31% 28% 41% ProductionEvaluation Pilot/POC Status Source: Wikibon 2014
- 7. Infrastructure And Process Must Change • Costly storage for cold data • Manual coding for data moves • Duplicate data copies • Disruptive app/platform rollouts • BU initiatives tied down by IT Average Big Data ROI: 55 cents on the $* Source: Wikibon 2014 Choke Points
- 8. How Do We Scale?
- 9. It Is Time To Retool And Accelerate Innovation Shorten Analytics Preparation, Cycle Time Iterate and Learn Faster Efficiently Evaluate HANA Enable Real-Time Analytics Understand and Tune Your Environment Automate Data Moves and Data Warehousing Improve Big Data Economics
- 10. Best Practice: Automate Key Data Management Tasks Data Warehouse Hadoop Identify Cold EDW Data Sets For Offloading to Hadoop Automate Data Integration Across EDW, RDBMS, Hadoop, MF Orchestrate Workflows
- 11. Dynamically Manage Your Data With Attunity 11 • Manage iterative cycle over time • Adapt data placement as you learn • Respond to changing business requirements • Exploit new platforms and capabilities Move Right Data Analyze Business Impact Evaluate Data
- 12. 12 NEW: Appfluent – Your Data Dashboard Completely Analyze Workloads And Data Usage Reduce Cost | Optimize Performance | Justify Investments 24
- 13. Typical Enterprise Data Warehouse Appfluent Visibility – Case Studies 30 Day History Unused Tables Loaded Daily CPU Cycles Used By ETL/ELT Large Telecom Carrier 37 TB 60% National Retail Chain 45 TB 55% Extract Transform Load Cold Tables 13
- 14. Automate Your Data Moves With Attunity Replicate More Data Less Time Advanced Monitoring & Control | Click-2-Replicate Design Fast Loading & Real-time CDC | Broadest Platform Support Non-intrusive Architecture Lower Cost 14
- 15. Case Study: Equifax Protects Customers By Continuously Scanning… Your Social Security number (if you choose) Alerts: • Unusual transactions • Usage of personal data on Internet • Auto fraud alertsto lenders to double-check your identity before authorizing new credit Up to 5 bank accounts Up to 6 credit/ debit cards Thousands of web sites where personal data might be sold
- 16. Equifax Now Uses Attunity Replicate • We automate and accelerate batch loading to DW • Equifax correlates data faster and more accurately • Customers receive real-time fraud notifications
- 17. Earning Your Trust We Serve Half Of The Fortune 100 And Many Financial Services Leaders
- 18. THANK YOU
- 19. Recent Awards February 2014 CRN Names Attunity One of itsTop 100 Coolest Vendors of 2014 December 2014 Attunity Maestro Named in DBTA Magazine’s List of Trendsetting Products in Data for 2015 June 2014 Attunity Selected as a CRN 2014 ‘Big Data 100’ Company December 2013 Attunity Replicate Named a Trendsetter in DBTA Magazine's List of the Trendsetting Products in Data for 2014 January 2015 CRN Names Attunity One of its Top 100 Coolest Vendors of 2015 June 2014 Attunity Selected as a CIO Review 2014 ‘Big Data 100’ Company January 2015 Business Intelligence Group Names Attunity a Top 16 Innovator in 2015 June 2014 Attunity Named ‘One of the Most Important Companies in Data Today’ by Database Trends and Applications (DBTA) Magazine
Editor's Notes
- #2: Today’s financial services organization understands the potential of Big Data analytics to drive innovation with top line and bottom line benefits. But the logistics of data management often interfere, thanks to competing platforms, manual coding for data moves, duplicate copies and inefficient test procedures. Learn about best practices and automation techniques to more efficiently consolidate data, economize resources, test new platforms and manage data warehousing. Free up your resources to innovate and build a competitive Big Data advantage.
- #8: This is why we cannot accelerate – what slows value, speed bumps, etc. Need a map Viking ship with many oarsmen Legacy infrastructure cannot scale to handle increasing data volume, velocity, variety IT personnel spend more time on data management and less on analytics Slower iterations mean learning curve flattens Analytics projects are delayed and narrower in scope Opportunities are unaddressed
- #9: How do I get there? How do I extract value? Refer back to two dimensions – economics and analytics preparation
- #13: Appfluent (an Attunity Company) provides data usage analytics for Data Warehouse Optimization. With Appfluent, enterprises can completely analyze workloads and data usage across platforms … to reduce costs, optimize performance and justify investments, With analysis provided by Appfluent, organizations can develop a roadmap to: 1)Rebalance the right data and right workloads onto the right platform, 2) Tune and optimize the performance of the systems based on how data is used and 3) Continuously measure and audit utilization and provide transparency to the business. Appfluent’s flagship software product is called Appfluent Visibility that provides the most comprehensive solution designed for Enterprise Data Administration. Appfluent Visibility is the ONLY solution in the market that supports multiple platforms supports including Teradata..Oracle…DB2…Netezza and now…Hadoop as well. Giving you the only solution that provides the needed insight across these platforms to move data and workloads to the right platform, optimize your systems based on data sets used and measure and audit usage and utilization of your diverse information assets…. to reduce overall costs and increase performance.
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