Day 1 Keynote address by Winifred Kotin, Country Director of Superfluid Labs, Ghana on the theme: "The promise of Data Science for Economic Transformation".
Presentation on "A Complete Overview of Data Driven Decision Making in a Quickly Changing Business Environment" given by Isaac Aidoo, Head of Data Analytics, Zoona.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
Workshop on "Data Management - The Foundation of all Analytics" given by John Aidoo, Data Analytics Manager at Central Insurance Company, Van Wert, Ohio.
Predictive and prescriptive analytics: Transform the finance function with gr...Grant Thornton LLP
As all businesses continue to collect, store and analyze more data than ever before, they face growing data challenges to support decision-making. Those who can leverage predictive and prescriptive analytics will differentiate themselves in the marketplace and gain a competitive advantage. In this report by Financial Executives Research Foundation Inc. and Grant Thornton LLP, we highlight insights from in-depth interviews with senior-level executives. These organizations use advanced analytics in their businesses to gain significant profit improvements. See more at - http://gt-us.co/1vv2KU9
This document provides an introduction to predictive analytics. It defines analytics and predictive analytics, comparing their purposes and differences. Analytics uses past data to understand trends while predictive analytics anticipates the future. Business intelligence involves using data to support decision making and aims to provide historical, current and predictive views of business. As technologies advanced, business intelligence evolved from being organized under IT to potentially being aligned under strategy management. Effective communication between business and analytics professionals is important for organizations to benefit from predictive analytics. The business case for predictive analytics includes enabling strategic planning, competitive analysis, and improving business processes to work smarter.
Business intelligence systems are also unable to deal with market volatiles. Infosys' business analytics offerings provide the processes, tools and expertise to extract the most from information investments description.
The document discusses the growing importance and opportunities of analytics for businesses. It notes that there is a widening performance gap between top performers and bottom performers in their use of data and analytics. While the amount of data is growing exponentially, there is also a significant skills gap in having enough talent to effectively analyze and use data. The document outlines several major themes where businesses are applying analytics, including customer insights, risk management, operations, and product design. It argues that analytics can drive significant business value when integrated into operations and transformations.
In this presentation Juan M. Huerta talks about big data adoption process at Citi, realising the technical value of big data and global solutions. Huerta goes on to talk about following a hybrid approach, and the future of analytics, expensive algorithms applied to large datasets. With Citi using these approaches in hopes of getting even wider global recognition.
Presentation on "A Complete Overview of Data Driven Decision Making in a Quickly Changing Business Environment" given by Isaac Aidoo, Head of Data Analytics, Zoona.
Day 1 (Lecture 4): Data Science in the Retail Marketing and Financial ServicesAseda Owusua Addai-Deseh
Lecture on "A Practical Exposition of Data Science in the Retail Marketing and Financial Services" delivered by Delali Agbenyegah, Director of Data Science and Analytics, Express, Columbus OH, USA.
Workshop on "Data Management - The Foundation of all Analytics" given by John Aidoo, Data Analytics Manager at Central Insurance Company, Van Wert, Ohio.
Predictive and prescriptive analytics: Transform the finance function with gr...Grant Thornton LLP
As all businesses continue to collect, store and analyze more data than ever before, they face growing data challenges to support decision-making. Those who can leverage predictive and prescriptive analytics will differentiate themselves in the marketplace and gain a competitive advantage. In this report by Financial Executives Research Foundation Inc. and Grant Thornton LLP, we highlight insights from in-depth interviews with senior-level executives. These organizations use advanced analytics in their businesses to gain significant profit improvements. See more at - http://gt-us.co/1vv2KU9
This document provides an introduction to predictive analytics. It defines analytics and predictive analytics, comparing their purposes and differences. Analytics uses past data to understand trends while predictive analytics anticipates the future. Business intelligence involves using data to support decision making and aims to provide historical, current and predictive views of business. As technologies advanced, business intelligence evolved from being organized under IT to potentially being aligned under strategy management. Effective communication between business and analytics professionals is important for organizations to benefit from predictive analytics. The business case for predictive analytics includes enabling strategic planning, competitive analysis, and improving business processes to work smarter.
Business intelligence systems are also unable to deal with market volatiles. Infosys' business analytics offerings provide the processes, tools and expertise to extract the most from information investments description.
The document discusses the growing importance and opportunities of analytics for businesses. It notes that there is a widening performance gap between top performers and bottom performers in their use of data and analytics. While the amount of data is growing exponentially, there is also a significant skills gap in having enough talent to effectively analyze and use data. The document outlines several major themes where businesses are applying analytics, including customer insights, risk management, operations, and product design. It argues that analytics can drive significant business value when integrated into operations and transformations.
In this presentation Juan M. Huerta talks about big data adoption process at Citi, realising the technical value of big data and global solutions. Huerta goes on to talk about following a hybrid approach, and the future of analytics, expensive algorithms applied to large datasets. With Citi using these approaches in hopes of getting even wider global recognition.
The main task of this talk is to see how Data Science can influence big companies to generate new revenue and more profit.
Subjects that will be addressed in this talk are:
• Understanding a value it brings to corporations on long-term (direct revenue generation not only cost reduction);
• Data Science is important part of digital transformation. Are corporations ready?
• Management dedication on investment;
• Lack of Data Science managers acting as a link between Data Scientists and Business managers. Provide motivation/interesting tasks for Data Scientists while validating investments in business environment;
• Lack of skillful Data scientists;
• Compensation of Data Scientists among other Employees (obviously a different scales needs to be applied);
• Examples of Applied Data Science as revenue generators in Telenor Serbia;
The document provides an overview of business intelligence (BI) including definitions, typical architectures, and key concepts. It describes how data is extracted from operational systems via ETL processes and loaded into data warehouses to support OLAP and business analytics. Different data modeling approaches are covered, including star schemas, snowflake schemas, and fact constellations. Dimensional modeling techniques are outlined to transform enterprise data models into structures optimized for analysis and reporting.
Analytics in banking preview deck - june 2013Everest Group
This report provides a comprehensive understanding of the analytics services industry with focus on banking domain. Analytics adoption in the banking industry is covered in depth, exploring various aspects such as market size, key drivers, recent analytics initiatives, and challenges. The report also analyses the trends in analytics deals for various banking subverticals (cards, retail, commercial, and lending) and evaluates analytics capabilities of 20+ service providers in the banking space
Role of business analytics in the banking industryVaisakh Nambiar
Banking analytics can help banks improve customer segmentation, acquisition, and retention. It also enhances risk management, customer understanding, and fraud prevention. Examples show how analytics helped a bank reduce customer churn by 15% through targeted campaigns, increase bank revenues by 8% by correcting unnecessary discounts, and increase products per customer three times over through microsegmentation. In conclusion, analytics provides banks marketing advantages and helps optimize risk, compliance, and decision-making.
Integrating A.I. and Machine Learning with your Demand ForecastSteve Sager
This document provides an overview of Demand Guru, a demand forecasting and predictive analytics solution. Some key points:
- Demand Guru uses machine learning and external data sources to model demand, account for causal factors, and test scenarios. This improves upon traditional statistical forecasting.
- It incorporates over 550,000 external time series datasets on topics like weather, economic, market and other data. This allows for better understanding of demand drivers.
- The solution can model "what if" scenarios to understand how changes might impact demand and make more confident decisions. This is done in a risk-free virtual environment.
- Demand Guru is presented as augmenting rather than replacing existing demand
This document outlines an enterprise artificial intelligence strategy (EAIS). It discusses the growing AI market and organizational benefits of AI like increased efficiency. It proposes establishing a center of excellence (COE) to implement AI projects across the business using a centralized AI engine. The strategy involves selecting business use cases, building historical data, performing proofs of concept, and creating a roadmap. It also describes an end-to-end data science life cycle from data preparation to deployment and monitoring. Finally, it proposes a tool chain for data ingestion, transformation, analytics, and visualization.
A basic presentation of how we can use Machine learning to sort out different problems faced by supply chain management and How we can also use it to model Inventory management.
The document describes case studies of various organizations using IBM analytics solutions to address challenges and gain benefits. It provides examples of how Arad Group used analytics to reduce water loss and costs by detecting leaks, how ASTRON analyzed exabytes of astronomical data to accelerate insights, and how Wimbledon used analytics to enhance the fan experience with real-time data and sentiment analysis.
Big Data & Analytics to Improve Supply Chain and Business PerformanceBristlecone SCC
Prof. David Simchi Levi, Engineering Systems Professor at MIT and Chairman of OPS Rules spoke at Bristlecone Pulse 2017 about delivering customer value through digitization, analytics and automation.
Business Intelligence (BI) enables businesses to make fact-based decisions by aggregating data from various sources, enriching it with context and analysis, and presenting it in reports, dashboards and other formats. BI is becoming increasingly important, ranking as a top 5 priority for businesses. Emerging trends in BI include mobile access, cloud deployment, advanced analytics like predictive modeling, and leveraging social and unstructured data sources. The future of BI will focus more on real-time insights and event-driven analysis to anticipate outcomes.
What we do; predictive and prescriptive analyticsWeibull AS
Prescriptive Analytics goes beyond descriptive, diagnostic and predictive analytics; by being able to recommend specific courses of action and show the likely outcome of each decision.
Predictive analytics will tell what probably will happen, but will leave it up to the client to figure out what to do with it.
Prescriptive analytics will also tell what probably will happen, but in addition: when it probably will happen and why it likely will happen, thus how to take advantage of this predictive future. Since there are always more than one course of action prescriptive analytics have to include: predicted consequences of actions, assessment of the value of the consequences and suggestions of the actions giving highest equity value for the company.
Business Partner Product Enablement Roadmap, IBM Predictive AnalyticsArrow ECS UK
This document provides an overview of IBM's predictive analytics products and capabilities. It discusses IBM SPSS products like Statistics, Modeler, Data Collection, Text Analytics for Surveys, and Analytic Server. It explains what each product does, such as build predictive models, analyze structured and unstructured data, deploy analytics, and more. The document also highlights the strengths of the IBM predictive analytics portfolio in areas like customer analytics, operational analytics, threat and fraud analytics, and decision management.
The document discusses how organizations can leverage information through an information-led transformation to drive smarter business outcomes. It outlines how analyzing large amounts of structured and unstructured data in real-time can help optimize decisions, predict issues, and improve business performance. The key elements are applying business analytics, establishing a flexible information platform, and creating an information agenda strategy.
Welcome to the Age of Big Data in Banking Andy Hirst
Big Data in banking presentation from Sibos Dubai 2013 . What are use cases driving deployments in Banking ? See the use cases SAP is involved In banking in 2013
This document provides an overview and summary of new features in IBM SPSS Predictive Analytics and IBM Decision Optimization. It discusses how predictive analytics can help organizations in various industries and functional areas. Key new features highlighted include empowering every user, unlocking more data faster, ground to cloud deployment options, optional coding and open source integration, and making predictive analytics accessible everywhere. The document demonstrates how these solutions have provided quantified benefits to customers.
Transforming Business with Smarter AnalyticsCTI Group
Transforming Business with Smarter Analytics by Deb Mukherji @ BPT IBM Innovative Indonesia with Smarter Analytics, 12 June 2013, Shangri-La Hotel Jakarta
DatKnoSys provides business analytics services including customer intelligence, marketing analytics, risk analysis, web analytics, and social media analytics. They help companies make better business decisions by merging internal company data with external market data. Their value proposition is that they are experts in data integration and analysis who can provide clients a clear overview of what is happening in their business and sector, along with actionable recommendations.
5 Ways AI will Revolutionize Supply ChainsMoataz Rashad
This talk covers 5 use-cases in supply chain optimization where AI can have a revolutionary effect on maximizing margins. These include optimizing pricing, production efficiency, demand forecasting, and risk mitigation decisioning.
This document discusses big data and analytics and its value proposition. It outlines the 4 V's of big data - volume, variety, velocity and veracity. It then discusses how big data and analytics can be leveraged across different industries to drive key business imperatives like acquisition, personalization, profitability and retention. It also outlines 5 key analytical use cases and 5 key operational use cases for big data and analytics. Finally, it emphasizes the need to be proactive about privacy, security, governance and building a culture that infuses analytics.
The document discusses Superfluid Labs, a data analytics firm that helps enterprises use data science and machine learning. It outlines their mission and vision, provides examples of case studies where they helped clients with predictive modeling and analytics. The presentation then covers developing a data science strategy, including building a data science team, prioritizing projects, and ensuring executive buy-in. Finally, it discusses the typical data science process and popular tools used.
George Schindler CGI Value Creation CGI Ratkaisu19CGI Suomi
George D. Schindler, President and CEO of CGI Group Inc., gave a presentation on digitization and value creation on January 24, 2019 in Finlandia-talo. He discussed how digitization is redefining value creation by extending it to customers, business partners, and employees. There is an opportunity to more tightly align IT and business functions, which can create more value. CGI assessed companies and found a strong correlation between IT-business alignment and higher earnings performance. Where alignment was strongest, profit and EPS growth were 2-3 times higher. Digital value creation requires culture change enabled by agile ways of working, data, and technology.
The main task of this talk is to see how Data Science can influence big companies to generate new revenue and more profit.
Subjects that will be addressed in this talk are:
• Understanding a value it brings to corporations on long-term (direct revenue generation not only cost reduction);
• Data Science is important part of digital transformation. Are corporations ready?
• Management dedication on investment;
• Lack of Data Science managers acting as a link between Data Scientists and Business managers. Provide motivation/interesting tasks for Data Scientists while validating investments in business environment;
• Lack of skillful Data scientists;
• Compensation of Data Scientists among other Employees (obviously a different scales needs to be applied);
• Examples of Applied Data Science as revenue generators in Telenor Serbia;
The document provides an overview of business intelligence (BI) including definitions, typical architectures, and key concepts. It describes how data is extracted from operational systems via ETL processes and loaded into data warehouses to support OLAP and business analytics. Different data modeling approaches are covered, including star schemas, snowflake schemas, and fact constellations. Dimensional modeling techniques are outlined to transform enterprise data models into structures optimized for analysis and reporting.
Analytics in banking preview deck - june 2013Everest Group
This report provides a comprehensive understanding of the analytics services industry with focus on banking domain. Analytics adoption in the banking industry is covered in depth, exploring various aspects such as market size, key drivers, recent analytics initiatives, and challenges. The report also analyses the trends in analytics deals for various banking subverticals (cards, retail, commercial, and lending) and evaluates analytics capabilities of 20+ service providers in the banking space
Role of business analytics in the banking industryVaisakh Nambiar
Banking analytics can help banks improve customer segmentation, acquisition, and retention. It also enhances risk management, customer understanding, and fraud prevention. Examples show how analytics helped a bank reduce customer churn by 15% through targeted campaigns, increase bank revenues by 8% by correcting unnecessary discounts, and increase products per customer three times over through microsegmentation. In conclusion, analytics provides banks marketing advantages and helps optimize risk, compliance, and decision-making.
Integrating A.I. and Machine Learning with your Demand ForecastSteve Sager
This document provides an overview of Demand Guru, a demand forecasting and predictive analytics solution. Some key points:
- Demand Guru uses machine learning and external data sources to model demand, account for causal factors, and test scenarios. This improves upon traditional statistical forecasting.
- It incorporates over 550,000 external time series datasets on topics like weather, economic, market and other data. This allows for better understanding of demand drivers.
- The solution can model "what if" scenarios to understand how changes might impact demand and make more confident decisions. This is done in a risk-free virtual environment.
- Demand Guru is presented as augmenting rather than replacing existing demand
This document outlines an enterprise artificial intelligence strategy (EAIS). It discusses the growing AI market and organizational benefits of AI like increased efficiency. It proposes establishing a center of excellence (COE) to implement AI projects across the business using a centralized AI engine. The strategy involves selecting business use cases, building historical data, performing proofs of concept, and creating a roadmap. It also describes an end-to-end data science life cycle from data preparation to deployment and monitoring. Finally, it proposes a tool chain for data ingestion, transformation, analytics, and visualization.
A basic presentation of how we can use Machine learning to sort out different problems faced by supply chain management and How we can also use it to model Inventory management.
The document describes case studies of various organizations using IBM analytics solutions to address challenges and gain benefits. It provides examples of how Arad Group used analytics to reduce water loss and costs by detecting leaks, how ASTRON analyzed exabytes of astronomical data to accelerate insights, and how Wimbledon used analytics to enhance the fan experience with real-time data and sentiment analysis.
Big Data & Analytics to Improve Supply Chain and Business PerformanceBristlecone SCC
Prof. David Simchi Levi, Engineering Systems Professor at MIT and Chairman of OPS Rules spoke at Bristlecone Pulse 2017 about delivering customer value through digitization, analytics and automation.
Business Intelligence (BI) enables businesses to make fact-based decisions by aggregating data from various sources, enriching it with context and analysis, and presenting it in reports, dashboards and other formats. BI is becoming increasingly important, ranking as a top 5 priority for businesses. Emerging trends in BI include mobile access, cloud deployment, advanced analytics like predictive modeling, and leveraging social and unstructured data sources. The future of BI will focus more on real-time insights and event-driven analysis to anticipate outcomes.
What we do; predictive and prescriptive analyticsWeibull AS
Prescriptive Analytics goes beyond descriptive, diagnostic and predictive analytics; by being able to recommend specific courses of action and show the likely outcome of each decision.
Predictive analytics will tell what probably will happen, but will leave it up to the client to figure out what to do with it.
Prescriptive analytics will also tell what probably will happen, but in addition: when it probably will happen and why it likely will happen, thus how to take advantage of this predictive future. Since there are always more than one course of action prescriptive analytics have to include: predicted consequences of actions, assessment of the value of the consequences and suggestions of the actions giving highest equity value for the company.
Business Partner Product Enablement Roadmap, IBM Predictive AnalyticsArrow ECS UK
This document provides an overview of IBM's predictive analytics products and capabilities. It discusses IBM SPSS products like Statistics, Modeler, Data Collection, Text Analytics for Surveys, and Analytic Server. It explains what each product does, such as build predictive models, analyze structured and unstructured data, deploy analytics, and more. The document also highlights the strengths of the IBM predictive analytics portfolio in areas like customer analytics, operational analytics, threat and fraud analytics, and decision management.
The document discusses how organizations can leverage information through an information-led transformation to drive smarter business outcomes. It outlines how analyzing large amounts of structured and unstructured data in real-time can help optimize decisions, predict issues, and improve business performance. The key elements are applying business analytics, establishing a flexible information platform, and creating an information agenda strategy.
Welcome to the Age of Big Data in Banking Andy Hirst
Big Data in banking presentation from Sibos Dubai 2013 . What are use cases driving deployments in Banking ? See the use cases SAP is involved In banking in 2013
This document provides an overview and summary of new features in IBM SPSS Predictive Analytics and IBM Decision Optimization. It discusses how predictive analytics can help organizations in various industries and functional areas. Key new features highlighted include empowering every user, unlocking more data faster, ground to cloud deployment options, optional coding and open source integration, and making predictive analytics accessible everywhere. The document demonstrates how these solutions have provided quantified benefits to customers.
Transforming Business with Smarter AnalyticsCTI Group
Transforming Business with Smarter Analytics by Deb Mukherji @ BPT IBM Innovative Indonesia with Smarter Analytics, 12 June 2013, Shangri-La Hotel Jakarta
DatKnoSys provides business analytics services including customer intelligence, marketing analytics, risk analysis, web analytics, and social media analytics. They help companies make better business decisions by merging internal company data with external market data. Their value proposition is that they are experts in data integration and analysis who can provide clients a clear overview of what is happening in their business and sector, along with actionable recommendations.
5 Ways AI will Revolutionize Supply ChainsMoataz Rashad
This talk covers 5 use-cases in supply chain optimization where AI can have a revolutionary effect on maximizing margins. These include optimizing pricing, production efficiency, demand forecasting, and risk mitigation decisioning.
This document discusses big data and analytics and its value proposition. It outlines the 4 V's of big data - volume, variety, velocity and veracity. It then discusses how big data and analytics can be leveraged across different industries to drive key business imperatives like acquisition, personalization, profitability and retention. It also outlines 5 key analytical use cases and 5 key operational use cases for big data and analytics. Finally, it emphasizes the need to be proactive about privacy, security, governance and building a culture that infuses analytics.
The document discusses Superfluid Labs, a data analytics firm that helps enterprises use data science and machine learning. It outlines their mission and vision, provides examples of case studies where they helped clients with predictive modeling and analytics. The presentation then covers developing a data science strategy, including building a data science team, prioritizing projects, and ensuring executive buy-in. Finally, it discusses the typical data science process and popular tools used.
George Schindler CGI Value Creation CGI Ratkaisu19CGI Suomi
George D. Schindler, President and CEO of CGI Group Inc., gave a presentation on digitization and value creation on January 24, 2019 in Finlandia-talo. He discussed how digitization is redefining value creation by extending it to customers, business partners, and employees. There is an opportunity to more tightly align IT and business functions, which can create more value. CGI assessed companies and found a strong correlation between IT-business alignment and higher earnings performance. Where alignment was strongest, profit and EPS growth were 2-3 times higher. Digital value creation requires culture change enabled by agile ways of working, data, and technology.
The document discusses emerging technologies and their opportunities in Gilgit-Baltistan (GB). It outlines intelligent sensors, intelligent cars, telehealth, microelectromechanical systems, nanotechnology, clean technology, and robotics as emerging technologies. It then provides examples of applications and opportunities for each technology. The document also discusses challenges in GB related to limited jobs, agriculture land, industry, infrastructure, and skills. It proposes initiatives like GB-Invent Today to train youth in skills and the Pakistan Business Incubation Centre to help startups. The KIU is highlighted for its blended learning programs and partnerships to promote freelancing and digital skills in GB.
Traditional businesses are struggling to keep up in an increasingly digital world where customers expect fast and seamless interactions. Many industries are adopting digital technologies and processes to improve operations and drive new revenue. As a result, companies are looking to third-party software solutions to partner with their existing systems and gain new digital capabilities. BMC partnered with PSFK to create a playbook exploring industry trends, opportunities, and best practices for digital transformation. The playbook identifies four key opportunities including enabling rapid application innovation through cross-team collaboration and agile development processes.
CFO’s Sharing: Is this possible to turn technology Capex to Opex for Growth ...Wendy Wan
Technological advances are disrupting the status quo and creating huge turbulence. Industries are converging, and new competitors emerging, at breakneck speed.
The role of the CFO is evolving. CFOs must aid in strategy development to pursue profitable growth by capitalizing technology.
How do the leading enterprise drive top-line growth and also bottom-line savings?
Stephen Abbott - Peoplescout - Assessing your current and future state positi...Jayne Corbett
The document discusses assessing an organization's talent lifecycle and moving it to a future state. It covers evaluating the current environment and maturity levels across sourcing, hiring and retaining talent. A framework is provided for assessing each stage of the lifecycle, developing a roadmap to the future state, and leveraging people analytics to improve outcomes. Talent acquisition technology and delivery models are also addressed to help transform processes.
Building the Digital Business: The 2016 CIO AgendaTesora
This presentation discusses how organizations can build a digital platform and business. It recommends that organizations think differently by creating a portfolio of algorithms, data, and patents to exploit network effects. It also recommends innovating through a bimodal delivery platform to drive speed and scale, and modernizing the core IT infrastructure with an open platform to capitalize on network effects. Recommended actions include investing in a bimodal delivery platform, connecting across delivery modes, and adding IoT and ecosystems to the core infrastructure platform to architect a digital business.
Digital transformation is needed for the local insurance industry to catch up with international best practices. Internationally, insurers provide more than 80% of quotes and over 20% of insurance purchases online. This has led to 50% lower operating expenses and 60% faster quoting/underwriting. In South Africa, less than 5% of insurance is purchased online. A powerful solution exists through the data and analytics capabilities of TU Africa. Combining extensive data sources with automation, AI, and advanced analytics can help insurers improve customer experience, increase efficiency, enhance underwriting and pricing, detect fraud, and turn data into valuable insights. Further digital transformation is needed in areas like automated onboarding, telematics, social media distribution, and
Abodoo presents their innovative Skills Mapping and Matching technology empowering local governments such as Cork County Council to support sustainable low carbon economic recovery from Covid-19, new job creation and inclusion through real time access to skills data intelligence
Connected Autonomous Planning: a continuous touchless model enabling an agile...Capgemini
Phil Davies, Head of Consumer Products, Retail and Distribution, Capgemini Invent and Michael McCullough, Supply Chain Lead, Capgemini US discussed “How using Intelligent Automation drives a step change in planning effectiveness and efficiency” at Kinexions 2019, the annual destination for users and supply chain innovators to showcase how to accelerate innovation, shorten time-to-value and maximize competitive advantage.
Capgemini’s Connected Autonomous Planning is a holistic approach to develop touchless planning solutions that creates a more easily automated, agile and responsive supply chain to support the needs of the future consumer and channels.
Digital Foundations to Transform Customer Experiences Through Process Optimiz...Jared Hill
The document provides an agenda for a webinar on digital foundations to transform customer experiences. The agenda includes introductions of presenters, an overview of how to start a customer experience initiative by documenting key business processes, and how to build a business case for process documentation using Signavio software. It also discusses accelerating adoption of customer experience management among stakeholders and cost savings from process documentation.
This document summarizes a presentation by PwC on data and analytics in the digital age. PwC consists of data professionals who help clients leverage their data and manage risks. Recent projects include analyzing payroll, designing websites, and building systems to visualize customer orders. The presentation covers how digital transformation allows companies to use analytics to stay competitive. It also demonstrates a data visualization tool to support digital transformations.
Loras College 2014 Business Analytics Symposium | Daniel Rebella, Phil Pillsb...Cartegraph
Learn about monetizing big data financials, performance insights and performance management in the cloud.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
As technology has evolved IT has transitioned from a background support function to a core driver of value creation and competitive edge. This shift has placed senior technologists at the heart of the organisation where they are increasingly critical to decision making, strategy and leadership.
The DIGIT Leader Summit will explore the evolution of the IT & Digital profession, considering the key technology and business trends and the profound impact they are having on the role. The programme will also examine the crucial components of leadership, looking at culture; team building, upskilling and communication.
The Summit is geared for senior IT & Digital leaders, and designed to provide an opportune forum for practitioners to share their experiences, learn from their peers and discuss best-practice approaches to leadership.
Core topics
Trends: Key technology trends and business trends
IT Evolution: How the IT and Digital role is changing and evolving
Leadership: Empowering, engaging, motivating and inspiring teams
Culture: Creating a culture of inclusion, innovation and exploration
Impact: Technology as a driver of innovation, improvement and problem solving
IT Management: Investment, ITAM, cost control, vendor management
Building Skills for the Changing Workforce: AWS Global Digital Skills StudyFairTechInstitute
Covering 12 countries globally (Australia, Brazil, Canada, Germany, India, Indonesia, Japan, New Zealand, Singapore, South Korea, the United Kingdom and the United States), this study surveyed employers and workers to understand the benefits of digital skills training, the barriers to training and the gap in digital skills training actions undertaken in organizations and among workers to meet future digital skill needs in the economy.
The study developed an indicator, the AWS Global Digital Skills Index, which explores the global training shortfall – referring to the gap between digital skills training efforts in organizations and among workers, and the identified training needs. Given that skills take time to build, employers and workers need to be forward-looking in their training efforts. However, this Index finds a significant global training shortfall: digital skills training efforts are not currently sufficient to meet evolving business needs.
Using data analytics to drive BI A case studyPhoenixraj
Using historical trip data from a bike share company, the study analyzed trends to help convert casual riders to annual members. Key findings include:
- Casual riders ride more on weekends while members prefer weekdays.
- Summer months see peak casual riding.
- The most used station, Streeter Dr & Grand Ave, had over 100,000 casual rides.
Recommendations include offering member incentives and discounts during peak casual riding periods, and partnering with local businesses near popular stations to advertise to casual riders. The study demonstrates how data analytics can provide business intelligence to improve marketing strategies.
On-switch: Applied Lessons on Moving up the Digital Maturity CurveCognizant
What separates digital beginners from leaders? No matter what your starting point is, our recent research sheds light on where and how much to invest, and the ROI and performance gains to expect.
The document summarizes the response of The Business Cafe to two government reports on supporting small and medium enterprises (SMEs) through developing digital skills and communities. The Business Cafe aims to address SME needs for networking, digital skills training, and accessible workspaces. One report reviewed publicly-funded digital qualifications and emphasized the need for relevance, flexibility, and ensuring all individuals can develop digital skills for an increasingly digital economy and workforce. The Business Cafe's focus on the community and delivering digital skills training locally aligns with the reports' findings on supporting SMEs and digital inclusion.
The document summarizes the key findings of two government reports on digital skills for small and medium enterprises (SMEs). It discusses how the Business Cafe aims to address the need for accessible digital skills training and networking identified in the reports. The reports found that digital skills are required across all industries and job roles. They will continue growing in importance with technological changes. The Business Cafe's goals of providing local SMEs with digital skills training and a community space align well with the reports' recommendations to improve relevance, flexibility and inclusion of digital skills support.
Similar to Day 1 Keynote Address-GDSS 2019 (IndabaX Ghana) (20)
Day 2 (Lecture 1): Introduction to Statistical Machine Learning and ApplicationsAseda Owusua Addai-Deseh
Shakir Mohamed discusses building machine learning and AI capacity in Africa through IndabaX Ghana. The document outlines Shakir's work since 2017 strengthening ML/AI through community partnerships and local leadership development across the continent. It also summarizes a talk given in April 2019 on statistical machine learning principles and their application in areas like science, healthcare, and fairness.
Day 2 (Lecture 3): Deep Learning Fundamentals - Architecture and ApplicationsAseda Owusua Addai-Deseh
Presentation on "Deep Learning Fundamentals - Architecture and Applications" delivered by Kwadwo Agyapon-Ntra, Entrepreneur in Training, Meltwater Entrepreneurial School of Technology.
Lecture on "Machine Learning Applications in Healthcare" delivered by Darlington Akogo, Founder, CEO, and Director of Artificial Intelligence, minoHealth AI Labs.
Workshop on "Building Successful Pipelines for Predictive Analytics in Healthcare" delivered by Danielle Belgrave, PhD, Researcher at Microsoft Research, Cambridge, UK.
This is the welcome address presentation of the maiden Ghana Data Science Summit 2019 (IndabaX Ghana) delivered by Delali Agbenyegah, Chairman of the organizing team.
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
1. 1
GHANA DATA SCIENCE SUMMIT 2019
The Promise Of Data Science For Economic Transformation
KEYNOTE SPEECH
25th April, 2019
WINIFRED KOTIN
www.superfluid.io | winifred@superfluid.io
4. My Solution -
A web-based telephone and
address directory to manage
data from Ghana Post and
Ghana Telecom with search
algorithms and user-friendly
interfaces.
5. And that is not a trivial feat or mission!
SUPERFLUID LABS LTD | Copyright (c) | 5
6. Today…
Director at SUPERFLUID LABS
MISSION:
Expanding opportunity for people and
businesses through the power of
predictive data analytics, ML and AI by
leveraging both traditional and
alternative data sources.
6
8. 2019 Growth projection of 8.8% from IMF
SUPERFLUID LABS LTD | Copyright (c) | 8
Data Analytics is transforming all aspects of human lives globally
and it is time Ghana leverages this powerful resource to propel
our growth agenda beyond traditional resource sectors
Sectors contributing highly
Oil Agriculture Manufacturing Mining and Services
9. Data Opportunity
• New globally available data
• Historical public data in Ghana
• Digital agenda of Government
• Existing/internal enterprise
data (often ignored)
SUPERFLUID LABS LTD | Copyright (c) | 9
10. Where can we harness the power of Data, ML and AI?
SUPERFLUID LABS LTD | Copyright (c) | 10
Job Creation Economic Productivity
Financial Inclusion
Sustainable & Equitable
Development
12. SUPERFLUID LABS LTD | Copyright (c) | 12
New skills = new additional roles
& jobs
New Ventures = more
employment opportunities and
add to GDP growth.
Unlocking New Opportunities for
existing enterprises = growth in
additional jobs & profits
Job Creation
Outcomes
13. Great Examples – And did not exist just 30 years ago
SUPERFLUID LABS LTD | Copyright (c) | 13
14. Scaling Outputs with Data Science
in existing sectors driving economic growth
SUPERFLUID LABS LTD | Copyright (c) | 14
Predictive Analysis Robotics & IoT Business Intelligence Customer Insights &
Data-driven Initiatives
Increase Output via operational efficiency and
targeted marketing
15. How BMW is scaling
production
https://www.youtube.com/
watch?v=J_cwrmaVtF4
SUPERFLUID LABS LTD | Copyright (c) | 15
16. Example - Use Case in Manufacturing at
BMW
https://www.youtube.com/watch?v=SUIcf
2U6pu4
• Optimizing vehicle assembling
• Robotics
• Predictive maintenance
• Intelligent component testing
• Quality control
• Personnel training
• Business Intelligence
SUPERFLUID LABS LTD | Copyright (c) | 16
17. Enable Financial Inclusion
SUPERFLUID LABS LTD | Copyright (c) | 17
7.3m Ghanaians
Inclusive financial services can be designed based on data on
demography, lifestyle, gender, income and education levels of the
unbanked and underbanked Ghanaian population.
18. How Nepal is Driving
Financial Inclusion
with Data
https://www.youtube.com/
watch?v=J_cwrmaVtF4
SUPERFLUID LABS LTD | Copyright (c) | 18
19. How do we preserve and empower the most
important driver of economic growth with data?
SUPERFLUID LABS LTD | Copyright (c) | 19
20. Data-driven policies on health and sustainable
livelihood empowerment initiatives
SUPERFLUID LABS LTD | Copyright (c) | 20
21. Call To Action
SUPERFLUID LABS LTD | Copyright (c) | 21
Data Science Summit should inspire us to leverage data better for greater impact
Easy access to varied data sources can help unlock this potential
Enhancement of data collection and management practices is key
Few/No APIs available for public data sets for innovation or experimentation
A collection of stakeholders, including many who are gathered here, are needed to
fully realise the vision of a digital and data-driven economic transformation
Delivering this keynote speech at Kofi Annan Center of Excellence in ICT of great significance to me and sends me back to memory lane because I discovered a Data Problem and later on built a solution for it almost two decades ago when I was an intern at the center.
As an intern here, I was part of a group researching on the penetration of ICT in Ghana and had to collect data on businesses that solve devices or provided services in Accra.
The data existed at Ghana Post and Ghana Telecom at that time but was not easily available for our research, we will roam round streets in Accra and rely on our networks to show us businesses they know who offered these services.
Google’s mission: To organize the world’s information and make it useful