FNB was facing business pressures from expansion, regulation, and customer demand that their old rules engine could not handle. It was inflexible, could not use analytics on big data, and was not integrated into their mainframe system. FNB selected IBM's Operational Decision Manager (ODM) as its new decision management platform because it could seamlessly integrate with FNB's mainframe environment, support agile changes to regulations and business needs, and deploy rules from a centralized source to multiple environments. The implementation was successful and helped FNB accelerate business value through improved decision management.
Progress Corticon delivers the agility needed to move quickly and stay compliant, while serving the ever-changing needs of businesses.
Progress Corticon separates business rules from code, so both IT and business people can quickly create or modify rules using an intuitive interface. In collaboration with IT, business analysts can identify and deploy automated business rules, freeing IT to focus on innovation.
Progress Corticon delivers the agility needed to move quickly and stay compliant, while serving the ever-changing needs of businesses.
Progress Corticon separates business rules from code, so both IT and business people can quickly create or modify rules using an intuitive interface. In collaboration with IT, business analysts can identify and deploy automated business rules, freeing IT to focus on innovation.
Accelerating Machine Learning Applications on Spark Using GPUsIBM
Matrix factorization (MF) is widely used in recommendation systems. We present cuMF, a highly-optimized matrix factorization tool with supreme performance on graphics processing units (GPUs) by fully utilizing the GPU compute power and minimizing the overhead of data movement. Firstly, we introduce a memory-optimized alternating least square (ALS) method by reducing discontiguous memory access and aggressively using registers to reduce memory latency. Secondly, we combine data parallelism with model parallelism to scale to multiple GPUs.
Results show that with up to four GPUs on one machine, cuMF can be up to ten times as fast as those on sizable clusters on large scale problems, and has impressively good performance when solving the largest matrix factorization problem ever reported.
Best practices in IBM Operational Decision Manager Standard 8.7.0 topologiesPierre Feillet
This deck has been presented at IBM InterConnect conference in 2016. It describes the ODM 8.7.x architecture, integration touchpoints, and recommended topologies for DevOps.
ICT Cost Management And Savings General2control4IT
ICT costs are increasigly becoming an issue. This presentation shows option for getting most value out of your ICT at reasonable cost levels. Transparancy in costs and volumes are key.
Bomt model- Technology Business AcceleratorLeo TechnoSoft
BOMT model is an innovative hybrid partner product development model by Leo TechnoSoft that offers a low-risk, hassle-free, cost-effective global sourcing strategy, that blends the advantages of traditional outsourcing and captive centers .
The Unique Selling Point (USP) of BOMT model is to aid Startups and ISVs’ in reducing their time-to-market. BOMT also creates opportunities for increasing revenue and maximizing ROI at minimum risk.
We deliver self funding services in the areas of cost recovery, contract compliance, review and negotiation, and billing optimization for voice, data and wireless communications services.
Organizations are looking to cloud computing solutions to improve the flexibility of their IT. But in today’s marketplace you still need to control operating expense, improve performance and maintain reliability. You need a cloud infrastructure solution that can help you manage costs and risk.
As information technology evolves, your data center faces a range of pressures from growing complexity. Energy usage and costs are rising; keeping your systems reliable is becoming more difficult; managing the whole system is time-consuming and expensive. You need your IT environment to be simple to manage, responsive to changing needs and cost effective.
Dell Direct Model & Virtual Integration
The Dell Direct Model
Dell's award-winning customer service, industry-leading growth and financial performance continue to differentiate the company from competitors. At the heart of that performance is Dell's unique direct-to-customer business model.
"Direct" refers to the company's relationships with its customers, from home-PC users to the world's largest corporations. There are no retailers or other resellers adding unnecessary time and cost, or diminishing Dell's understanding of customer expectations. Why are computer-systems customers and investors increasingly turning to Dell and its unique direct model?
Dell taking maximum benefits from various competitive strategies to counter act the competitive forces prevalent in the PC market.
• Price for Performance. By eliminating resellers, retailers and other costly intermediary steps together with the industry's most efficient procurement, manufacturing and distribution process Dell offers its customers more powerful, more richly configured systems for the money than competitors.
• Customization. Every Dell system is built to order. Customers get exactly, and only, what they want.
• Service and Support. Dell uses knowledge gained from direct contact before and after the sale to provide award-winning, tailored customer service.
• Latest Technology. Dell's efficient model means the latest relevant technology is introduced in its product lines much more quickly than through slow-moving indirect distribution channels. Inventory is turned over every 10 or fewer days, on average, keeping related costs low.
• Superior Shareholder Value. During the last fiscal year, the value of Dell common stocks more than doubled. In 1996 and 1997, Dell was the top-performing stock among the Standard & Poor's 500 and NASDAQ 100, and represented the top-performing U.S. stock on the Dow Jones World Stock Index.
Accelerating Machine Learning Applications on Spark Using GPUsIBM
Matrix factorization (MF) is widely used in recommendation systems. We present cuMF, a highly-optimized matrix factorization tool with supreme performance on graphics processing units (GPUs) by fully utilizing the GPU compute power and minimizing the overhead of data movement. Firstly, we introduce a memory-optimized alternating least square (ALS) method by reducing discontiguous memory access and aggressively using registers to reduce memory latency. Secondly, we combine data parallelism with model parallelism to scale to multiple GPUs.
Results show that with up to four GPUs on one machine, cuMF can be up to ten times as fast as those on sizable clusters on large scale problems, and has impressively good performance when solving the largest matrix factorization problem ever reported.
Best practices in IBM Operational Decision Manager Standard 8.7.0 topologiesPierre Feillet
This deck has been presented at IBM InterConnect conference in 2016. It describes the ODM 8.7.x architecture, integration touchpoints, and recommended topologies for DevOps.
ICT Cost Management And Savings General2control4IT
ICT costs are increasigly becoming an issue. This presentation shows option for getting most value out of your ICT at reasonable cost levels. Transparancy in costs and volumes are key.
Bomt model- Technology Business AcceleratorLeo TechnoSoft
BOMT model is an innovative hybrid partner product development model by Leo TechnoSoft that offers a low-risk, hassle-free, cost-effective global sourcing strategy, that blends the advantages of traditional outsourcing and captive centers .
The Unique Selling Point (USP) of BOMT model is to aid Startups and ISVs’ in reducing their time-to-market. BOMT also creates opportunities for increasing revenue and maximizing ROI at minimum risk.
We deliver self funding services in the areas of cost recovery, contract compliance, review and negotiation, and billing optimization for voice, data and wireless communications services.
Organizations are looking to cloud computing solutions to improve the flexibility of their IT. But in today’s marketplace you still need to control operating expense, improve performance and maintain reliability. You need a cloud infrastructure solution that can help you manage costs and risk.
As information technology evolves, your data center faces a range of pressures from growing complexity. Energy usage and costs are rising; keeping your systems reliable is becoming more difficult; managing the whole system is time-consuming and expensive. You need your IT environment to be simple to manage, responsive to changing needs and cost effective.
Dell Direct Model & Virtual Integration
The Dell Direct Model
Dell's award-winning customer service, industry-leading growth and financial performance continue to differentiate the company from competitors. At the heart of that performance is Dell's unique direct-to-customer business model.
"Direct" refers to the company's relationships with its customers, from home-PC users to the world's largest corporations. There are no retailers or other resellers adding unnecessary time and cost, or diminishing Dell's understanding of customer expectations. Why are computer-systems customers and investors increasingly turning to Dell and its unique direct model?
Dell taking maximum benefits from various competitive strategies to counter act the competitive forces prevalent in the PC market.
• Price for Performance. By eliminating resellers, retailers and other costly intermediary steps together with the industry's most efficient procurement, manufacturing and distribution process Dell offers its customers more powerful, more richly configured systems for the money than competitors.
• Customization. Every Dell system is built to order. Customers get exactly, and only, what they want.
• Service and Support. Dell uses knowledge gained from direct contact before and after the sale to provide award-winning, tailored customer service.
• Latest Technology. Dell's efficient model means the latest relevant technology is introduced in its product lines much more quickly than through slow-moving indirect distribution channels. Inventory is turned over every 10 or fewer days, on average, keeping related costs low.
• Superior Shareholder Value. During the last fiscal year, the value of Dell common stocks more than doubled. In 1996 and 1997, Dell was the top-performing stock among the Standard & Poor's 500 and NASDAQ 100, and represented the top-performing U.S. stock on the Dow Jones World Stock Index.
Case Study: Salesforce CPQ (Configure Price Quote) for Software as a Service ...Jade Global
Salesforce CPQ Case Study:
Business Requirements
Migrate all quote templates from existing tools to Salesforce CPQ as the main tool for the booking and Sales process
Support project lifecycle activities, including Requirement Gathering, Design, Development, Testing and Deployment
Configure Products based on business needs
An adaptable configuration of validation and pricing rules to prevent booking errors
Upgrade User Experience with guided flow
Enable core CPQ functions on mobile platforms
Business Challenges
OOTB functionality did not meet certain business requirements
Business changed requirements frequently causing rework
Business testing was not completed as quickly as items were being developed
Not able to properly format quotes Formatting of quote generation
Products being selected together incorrectly
Long list of products without any groupings - poor user experience
Approvals were not tracked, Lack of mobile approvals
Solution – Salesforce CPQ (Steelbrick)
Customizable quote templates
Validations to prevent users from selecting products that shouldn’t be selected together
Prompts to guide the user to review products before continuing with product selection
Enabled approvals with mobile capabilities
Connect with us:
Info@jadeglobal.com 1 877-523-3448
Website: http://www.jadeglobal.com
LinkedIn: http://www.linkedin.com/company/jade-...
Facebook: https://www.facebook.com/jadeglobal/
Twitter: https://twitter.com/JadeGlobal
The concept of BPR was first introduced in the late Michael Hammer's 1990 Harvard Business Review article and received increased attention a few years later, when Hammer and James Champ published their best-selling book, Reengineering the Corporation. The authors promoted the idea that sometimes-radical redesign and reorganization of an enterprise is necessary to lower costs and increase quality of service and that information technology is the key enabler for that radical change.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
2. Company overview
• The oldest bank in South Africa formed in 1838
• Listed on the South African Stock Exchange and the Namibian
Stock Exchange
• One of the largest financial institutions in South Africa providing
banking and insurance to retail, commercial, corporate and public
sector customers
1
3. Business Problem
• FNB was facing increased business pressure due to
expansion, regulation and consumer demand
• The old rules engine:
• was inflexible
• could not effectively apply analytics to take advantage of “Big
Data”
2
5. Business Problem
• Rapid international expansion 2009
• Multiple developers could not work simultaneously on the engine
• Therefore, forced to create instance’s of the engine per country to
allow for project throughput
• Affordability rules (best practice) replicated in each instance of engine
• Poor reusability
• Testing inefficiencies as each instance of the engine had to be tested
6. Business Requirement
• FNB needed an engine that was:
• Agile in order to rapidly cope with new regulations and business
conditions
• Adaptive to seamlessly fit into the existing complex FNB
architecture
5
7. Business Requirement
• Reduction in time taken to code, develop and deploy rules
• Ability to deploy rules and parameters from a centralised source
to multiple distributed environments with central control
• Ability to execute rules/decisioning real-time through a single
unit of work
• Decisioning engine integration into FNB Mainframe Cobol
environment
6
8. Business Requirement
• Shift focus from Business Rules to Decision Management
• Not credit rules specific
• Incorporate fraud (both application and transactional)
• Loyalty program incorporation
• Cater for prototyping, model driven requirements and reverse
engineering of specification
• Manage business decisions in natural language
• Decouple development and business decision change lifecycles
• Single version of the Truth
• Maintainable with a Center of Competency model
• Focus on decisions that need to change often and quickly
7
9. Technical requirement
• Solution needed the capability for current and future integration
into FNB’s
• Warehouse’s
• Data mining systems
• Analytical and modeling systems
• Support and integrate with FNB’s existing mainframe
technologies:
• Hogan Cobol
• JBOSS /Tomcat and Linux
• zLinux
• Support a role-based security model
8
10. 9
Selection criteria that led to ODM
. Product Technology
environment
Interface Seamless
Integration with
FNB mainframe
FICO Blaze Advisor JVM or .NET Proprietary API or
Web Service
Message switch
IBM ODM zOS, JVM Cobol, XML and
JAVA API
Direct
Jboss Enterprise
BRMS
Jboss Middleware JAVA API Message switch
Apama JVM or .NET JAVA, C, C++, .NET Message switch
Experian
Powercurve
JVM JAVA, C Message switch
SAP NetWeaver JVM JAVA, ABAP Message switch
Oracle Business
Rules
Oracle Fusion
Middleware
XML, JAVA or Oracle Message switch
11. What led to ODM product selection
• Improved separation of business logic from mainframe
• Java flexibility scalability – run within or out of mainframe
• FNB has a low maturity in the generation of requirements
• IDE Integration with industry standards (e.g. Eclipse)
10
12. What led to ODM product selection
11
•Service-oriented architecture (SOA) driven
13. What led to ODM product selection
12
• Old engine had too many nested if then statements
• ODM relies on more atomic rules
16. Journey
Stage
CustomersGoals&
Context
Identify Business
Challenge & Value
Established business
priorities & objectives.
Build a plan for your
BPM/BRM skills &
potential.
Define the
Opportunity
Succeed with an
Initial Project
Deliver your first
solution successfully.
Build foundational
platform skills.
Use early win to foster
new adoption.
Accelerate
Business Value
Establish a
Program
Increase scope & impact
of mission.
Establish critical mass of
platform skills.
Establish governance &
delivery consistency.
Scale Delivery
Capability
Adopt within
LOB/Enterprise
Line-of-business /
Enterprise focus.
Align strategy and
execution goals.
Mature platform skills &
solution discipline.
Scale Business
Impact
Value
Time
The Smarter Process Adoption Journey
17. Technical Milestones
1. Proof integration with mainframe (through COBOL)
2. Deliver value consistently across various technical environments
• Batch / real-time
• Mainframe / distributed
• Same rule services running consistently
3. Address change and complexity by revamping a strategic system
• Not compromising business agility; independent decision services
combined through composite services
• Preserving a manageable governance model; avoiding too many fine
grain services across functions / countries
4. Expand and spread across the company (ongoing)
• Monthly events, ...
• Commercial, First Rand Group, ...
5. Explore additional value gain through related technologies (future)
• Decision Server Insights, ...
16
18. Dev
Infrastructure setup
17
(eg SVN)
Rule Designer
Rule Designer
Rule Designer
Rule
Execution
Server (RES)
(zRES on z/OS or RES
on distributed)
QA / INT PROD
zRES zRES
Decision Center
ruleapp
archive
Change
Management( through ant scripts)1
2
3
4
5 6
7
19. Future Plans
18
• Better leverage data through analytics
• Expand the scope of decision management
• Explore new value gains through technology
20. Thank You
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