A better business case for big data with Hadoop
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My goal today is to inspire you to make a strong business case for applying big data in your enterprise, a key part of which is taking big data beyond analytics.
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A better business case for big data with Hadoop
- 1. Regroup with Hadoop - A Better Business Case for Big Data CONFIDENTIAL - Copyright © Aptitude Software Ltd. 2014
- 2. Hadoop is Crossing the Chasm Big data is moving beyond the hype. The market is starting to mature, with organizations becoming more realistic about how big data can be useful Copyright © Aptitude Software 2014 Uncertain ROI “Many organizations getting stuck in the experimentation phase - finding interesting insights from new data sources, but often not connecting them to business processes.” 2012 2013
- 3. What is the Business Case? “The top big data challenge across industries for 2013 is how to get value from big data; 56% list it as a top struggle. This comes from not knowing what data sources to analyze, what business problems to solve, and getting stuck trying to make the business case.” Costs of new technology Infrastructure Resources & Training Implementation Consulting, Services Operationalization Security & Governance Copyright © Aptitude Software 2014
- 4. How a Finance Problem Became a Big Data Solution Accurately determining customer profitability at a US investment bank required a multitude of complex allocation rules and the processing of a significant amount of data Copyright © Aptitude Software 2014 Cost Centres Products Channels Customers x00s Cost Centres x000s Account Codes X X X = 250 billion results + many more calculations Cost Centre Monthly Total $18.4 million Cost Allocated to Customer $12.36 Cost Allocation Massive Data Volumes Complexity of cost allocation rules x00s Revenue Pools x,000 Advisors x,000,000 Clients
- 5. Weighing up the Options Copyright © Aptitude Software 2014
- 6. The Journey to the Full Potential of an EDH Operational Efficiency Buys Option on Exploration, Data Science, and Convergence Operational Efficiency Information Advantage ©2014 Cloudera, Inc. All rights reserved. ETL Exploration Data Science Acceleration Cheap Storage EDW Optimization Converged Applications IT Business Big Data Evolves
- 7. Calculating ‘Big’ Royalties • Leading music streaming service uses Hadoop to record transactional streaming data and calculate royalties • Proving Hadoop has matured enough to support high performance, secure, real-time, business critical applications Copyright © Aptitude Software 2014
- 8. The case for using Hadoop in operational applications is more difficult in established enterprises Copyright © Aptitude Software 2014 Your Enterprise Architecture ??
- 9. How do you take advantage of Hadoop within a complex IT landscape? Copyright © Aptitude Software 2014 Requirements 1. Co-exist and integrate with existing systems 2. Access operational data in real-time
- 10. How Much? Copyright © Aptitude Software 2014
- 11. Dynamic Pricing Requirements Copyright © Aptitude Software 2014 Current stock levels Marketing offers Demand & Sentiment Cost & profit models
- 12. Hadoop Ecosystem Emerges Copyright © Aptitude Software 2014
- 13. Aptitude Platform with Cloudera Enterprise A high productivity development environment with a high performance run time engine, Version 5.0 incorporates in-memory, in-database and in-Hadoop processing Copyright © Aptitude Software 2014
- 14. Hadoop Comes of Age The promises of big data are real, but until recently the ecosystem and technology maturity has limited its use in the enterprise Copyright © Aptitude Software 2014
- 15. CONFIDENTIAL Copyright © AptitudeC SOoNftFwIaDreE 2N01T4IAL - Copyright © Aptitude Software Ltd. 2014
Notes de l'éditeur
- Intro My goal today is to inspire you to make a strong business case for applying big data in your enterprise, a key part of which is taking big data beyond analytics
- Hadoop has been working its way through the hype cycle, Early barriers to adoption include availability and cost of Hadoop engineers, technology stability, enterprise support (security, resilience, etc), ecosystem, lack of tooling Many of these challenges have been addressed (largely thanks to the likes of Cloudera pushing enterprise grade features) - now on the slope of enlightenment - starting to deliver on its promises - leading organizations are fully committing to Hadoop However, many organizations still struggle to take Hadoop out of that pet science project status, moving from ‘interesting’ to ‘valuable’
- But part of the challenge is creating a viable business case, one that clearly articulates a return on the range of investments that are required to adopt a new technology within the organization This is underpinned by research from the likes of Gartner, one of the real sticking points is linking capability, the art of the possible, back to real business need and advantage within actual business processes. Big data investments in 2013 continue to rise from 2012, with 64% of organizations investing or planning to invest in big data technology This presentation will show you a few examples of how some of the customers are working with Aptitude Software are adopting Hadoop for operational business applications to become truly data-driven enterprises, where there have been clear business cases to support the introduction of Hadoop
- An investment bank A business requirement not normally associated with big data, to understand cost to serve and true customer profitability When you look at business structure, the broad range of direct and indirect costs, number of customer, etc. you can quickly see how the data challenge builds up So this brings together data integration, process management, business user control and high volume data processing
- Significant investment in data warehouse appliance – many, many racks, many, many millions $ Infrastructure heavily utilised (…overloaded). But they were challenged with balancing system resources – between end user reporting and analytics, and processing new data coming in. They wanted to do more …. What-if models, scenario modelling, etc. They had to weigh up their options - continue to invest heavily in the appliance platform, or think differently So they looked to Hadoop as a platform for offloading a range of batch processing jobs The results still loaded into their DW appliance
- So these requirements were no longer just IT driven. Business need and demand created a real viable business case for Hadoop This slide from Cloudera maps the evolution as they see it. Far right being the panacea of big data, where we are bringing together data, analytics and business applications Challenge on the vision to greater value from enterprise- and industry-specific objectives Ensure there’s a tested and relevant incremental growth path to advanced analytics Sustain the journey to scale with an enterprise data hub by letting the savings from operational efficiency projects pay for the downstream information advantage projects Enable at every step of adoption and deployment with training and professional services aligned to objectives, building a center of excellence that spans the organization
- Here is another great example of Hadoop being used for operational business applications: Spotify who have been very open and public about their use of Hadoop to capture, process and calculate all of the royalties owed. From transactionally recording each track that has been streamed in Hadoop, to marrying up streaming data with contractual data and calculating the royalties owed to record labels, music societies, etc. and reporting accordingly. As you can see this is clearly not analytics (well there’s a lot of that as well to improve customer experience and service features), but very transactional in nature, resilient – beyond five 9s, accountable - financial statement of record They tell a great story of their journey, which was not without challenge, but clearly proves that Hadoop is ready for the most demanding operational business applications. All 690 nodes and 28 PT of it !! A great story, but one from a (not quite start-up) but very young company. No legacy, no integration, therefore no complexity, no mess, etc. - greenfield !! The case is not always that easy to make
- But how can you make the same business case within your enterprise when you have a complex landscape, and different attitudes towards new technologies, etc…. How do we take this approach and make it workable in a typical enterprise, one with multiple ERP systems, billing systems, CRM systems, a data warehouse or two You don’t have the benefits of a greenfield, Hadoop is not going to be self contained and in splendid isolation.
- The majority of business centric, big data applications are going to require integration to one or more of your existing systems, access to various operational data points that can’t afford to have the latency of load into Hadoop. They’ll need to plug into existing or modified business processes and interface directly with business users. But of course they have to take advantage of big data platforms and seamlessly integrate with the likes of Hadoop as they would any other technology. So let’s take a look at a final example where all of these requirements come together: Data integration Real-time access – both to Hadoop and operational systems, such as ERP Data processing Analytics Business user control and management
- So let’s imagine a B2C business, one that has the opportunity to dynamically adjust product pricing based on a range of factors. We’re all aware of this with airlines where flight prices are based on day, time, demand and proximity to departure. It’s also done by stealth in retail through store loyalty cards – not dynamic, but with vouchers you are getting an individual price for a product based on a range of factors. But to drive the competitive edge, companies are looking to become more dynamic with their approach, responding in near-real time to a range of factors and conditions. If you’ve noticed, some supermarkets are busy installing digital price tags on their shelves, gearing up for it already. One company we have been working with sells tickets to concerts and events around the world (essentially a ticket agent). They wanted to dynamically adjust the price of tickets based on a range of factors, including trends, demand, remaining available seats, etc. But done in a way that had an eye on cost of sale and profitability for a given set of tickets.
- There is a requirement for Data integration, ERP, CRM for order history, product info, Access to broad data sets, ideally already in Hadoop - e.g. customer and product profitability Pre-processing, e.g. social media to derive trends and demand. E.g. Concert ticket prices fluctuating based on Twitter trends UI interaction – to define pricing models and to analyse pricing Real time access, e.g. through services, to request specific prices Real time access to latest data, e.g. latest customer master record Down stream integration, e.g. to CRM or ERP The breadth and volume of data that can be stored enables pricing engines to go way beyond the traditional approaches and start to leverage a wealth of information to price more competitively and profitably
- Fortunately Hadoop and its ecosystem is at the point of maturity where this is now a reality Aptitude Software is proud to be a partner of Cloudera, selected because of their commitment to making Hadoop suitable for the enterprise. We differentiate by taking big data beyond analytics and embedding across the enterprise, integrated into business applications and in the hands of the business users that will derive the greatest benefit
- Our goal is to provide a platform that enables business and IT teams to deploy data centric applications quickly and collaboratively Where business rules, business process, data and application integration can all be defined graphically without the need to understand the underlying technologies involved. And finally one that can take advantage of whatever processing horsepower you have at your disposal, in-memory, in-database and of course in-Hadoop.