Pyramid Solutions presented at IBM Content 2017 and shared how organizations are using cognitive capture to identify handwriting, initiate workflows, understand embedded data tables and even send bookmarked documents to FileNet.
How data empowers member-centric transformationAndy Arends
The document discusses how health plans can transition from business-to-business (B2B) models to consumer-to-business (C2B) models by leveraging "viscous data" - data that flows freely between different sources. It outlines barriers to using viscous data like latency, lack of diversity, and security. However, breaking through these barriers by analyzing diverse real-time data from various sources can help health plans meaningfully engage with individual members and provide accountable care for populations. The document advocates that health plans should understand what they currently know about members, what more they could know, and how they will use additional data insights.
The advent of ‘big data’ has completely changed the way businesses can harness the information about customers to make powerful business decisions. Data could be of any type – campaign information, customer demographics, individual transaction behavior, interactions on social networks, web usage, or satisfaction surveys etc. BRIDGEi2i has the ability and experience to mine this wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross sell and up-sell opportunities and thereby enhance the life time value of customer relationships. To know more visit: http://www.bridgei2i.com/customer-intelligence.html
Bigvue Consulting provides analytics services to banks and financial institutions to improve business outcomes. Analytics can help with improved customer acquisition and retention, increased cross-selling opportunities, better risk management, and enhanced customer value. Bigvue's services include developing predictive models to activate dormant customer accounts and increase credit card cross-selling. Their methodology involves assessing business objectives, analyzing data, building analytical solutions, validating results, and implementing solutions to track outcomes. Bigvue leverages analytics and technology across various banking products and channels to help clients make better strategic and tactical decisions.
The document discusses building a big data analytics strategy in 3 main steps: 1) Gather requirements and objectives to determine a candidate strategy, 2) Select appropriate tools and technology to implement the strategy, and 3) Implement the strategy through operational readiness. It also covers key concepts like the 3V's model of big data, the big data analytics lifecycle, and strategy considerations at each phase like volume, variety and velocity of data. Example case studies of social media analytics on Hadoop are provided.
North American banks extensively use analytics to manage credit risks. More than 1/3 of bank customers buy a product from a competing bank each year. MicroStrategy helps banks analyze large amounts of customer, transactional, and operational data to identify high-risk borrowers and reduce credit risks. It also enables banks to easily comply with regulations.
Marketers Flunk the Big Data Test by Patrick Spenner and Anna BirdVimaleswar Babureddy
Marketing teams are under pressure to adopt new data-driven approaches to gain customer insights as traditional methods rely on data for only 11% of decisions. However, many marketers struggle with using statistics and separating relevant signals from noise. The most effective teams focus on goals and use the right data to make informed decisions.
Big data analytics can provide acquirers with revenue advantages, improved knowledge of customer needs, and greater operational efficiencies. It allows for enhanced fraud management, loyalty programs, and merchant services through analysis of large, diverse transaction datasets. Realizing these benefits requires integrating multiple data sources and deploying analytical tools to glean insights from both structured and unstructured payment information.
1. Analytics is increasingly important in the banking industry for applications like risk management, fraud detection, and customer segmentation. Tools like data mining and predictive analytics help banks understand customer behavior and mitigate risks.
2. Analytics supports decision making to increase revenue, reduce costs, and manage risks. This improves customer retention and understanding. Popular analytics tools in banking include R, SAS, and Python.
3. Use cases for banking analytics include customer analytics, fraud analysis, big data analytics, and risk analytics. Analytics provides insights into areas like marketing, compliance, and optimal performance.
How data empowers member-centric transformationAndy Arends
The document discusses how health plans can transition from business-to-business (B2B) models to consumer-to-business (C2B) models by leveraging "viscous data" - data that flows freely between different sources. It outlines barriers to using viscous data like latency, lack of diversity, and security. However, breaking through these barriers by analyzing diverse real-time data from various sources can help health plans meaningfully engage with individual members and provide accountable care for populations. The document advocates that health plans should understand what they currently know about members, what more they could know, and how they will use additional data insights.
The advent of ‘big data’ has completely changed the way businesses can harness the information about customers to make powerful business decisions. Data could be of any type – campaign information, customer demographics, individual transaction behavior, interactions on social networks, web usage, or satisfaction surveys etc. BRIDGEi2i has the ability and experience to mine this wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross sell and up-sell opportunities and thereby enhance the life time value of customer relationships. To know more visit: http://www.bridgei2i.com/customer-intelligence.html
Bigvue Consulting provides analytics services to banks and financial institutions to improve business outcomes. Analytics can help with improved customer acquisition and retention, increased cross-selling opportunities, better risk management, and enhanced customer value. Bigvue's services include developing predictive models to activate dormant customer accounts and increase credit card cross-selling. Their methodology involves assessing business objectives, analyzing data, building analytical solutions, validating results, and implementing solutions to track outcomes. Bigvue leverages analytics and technology across various banking products and channels to help clients make better strategic and tactical decisions.
The document discusses building a big data analytics strategy in 3 main steps: 1) Gather requirements and objectives to determine a candidate strategy, 2) Select appropriate tools and technology to implement the strategy, and 3) Implement the strategy through operational readiness. It also covers key concepts like the 3V's model of big data, the big data analytics lifecycle, and strategy considerations at each phase like volume, variety and velocity of data. Example case studies of social media analytics on Hadoop are provided.
North American banks extensively use analytics to manage credit risks. More than 1/3 of bank customers buy a product from a competing bank each year. MicroStrategy helps banks analyze large amounts of customer, transactional, and operational data to identify high-risk borrowers and reduce credit risks. It also enables banks to easily comply with regulations.
Marketers Flunk the Big Data Test by Patrick Spenner and Anna BirdVimaleswar Babureddy
Marketing teams are under pressure to adopt new data-driven approaches to gain customer insights as traditional methods rely on data for only 11% of decisions. However, many marketers struggle with using statistics and separating relevant signals from noise. The most effective teams focus on goals and use the right data to make informed decisions.
Big data analytics can provide acquirers with revenue advantages, improved knowledge of customer needs, and greater operational efficiencies. It allows for enhanced fraud management, loyalty programs, and merchant services through analysis of large, diverse transaction datasets. Realizing these benefits requires integrating multiple data sources and deploying analytical tools to glean insights from both structured and unstructured payment information.
1. Analytics is increasingly important in the banking industry for applications like risk management, fraud detection, and customer segmentation. Tools like data mining and predictive analytics help banks understand customer behavior and mitigate risks.
2. Analytics supports decision making to increase revenue, reduce costs, and manage risks. This improves customer retention and understanding. Popular analytics tools in banking include R, SAS, and Python.
3. Use cases for banking analytics include customer analytics, fraud analysis, big data analytics, and risk analytics. Analytics provides insights into areas like marketing, compliance, and optimal performance.
This document discusses effective practice management. It describes Med e Mass, a leading practice management company in South Africa that provides software and services to 9500 doctors. Effective practice management involves implementing long-term strategic plans, protocols, and controls to improve organization, reduce reactivity, and allow doctors to make informed decisions for practice growth while managing risks like data security. A practice management system can deliver improved efficiency, productivity, financial information, correspondence capabilities, and mitigate cash flow risks through features like electronic billing, reporting, user-friendly interfaces, and innovation.
Frederieke Jacobs on GDPR & digital health @ Health 2.0 Amsterdam, June 2018 kasiarab
Frederieke Jacobs (journalist, SmartHealth), "Overview of recent developments re privacy & digital health" https://www.linkedin.com/in/frederieke-jacobs
This is a presentation from a Health 2.0 Amsterdam "GDPR & healthcare: towards harvesting health from our data" event that took place on the 18th of June 2018
https://www.meetup.com/Health-2-0-Amsterdam/events/250870609/
The document discusses data warehousing, knowledge discovery in databases (KDD), and data mining. It defines a data warehouse as a subject-oriented collection of integrated and non-volatile data used to support management decision making. Data mining is extracting knowledge from large amounts of data and has applications in business transactions, ecommerce, healthcare, and more. Specifically for banking, data mining can be used for marketing, risk management, and customer acquisition/retention by identifying patterns in large customer data sets.
Lower Total Cost of Care and Gain Valuable Patient Insights through Predictiv...Perficient, Inc.
Learn how predictive analytics for healthcare can enable your organization to make proactive decisions that can have a profound impact for both patients and care providers. We discuss current and emerging healthcare trends and the positive impact that predictive analytics can have on your organization by:
Optimizing Resource Utilization: Better allocate nurses, clinicians, diagnostic machinery and other resources by predicting future admission volumes
Enhancing Patient Care: Proactively treat patients by more accurately predicting the chance of a chronic condition or the response to medications and therapies
Improving Clinical Outcomes: Analyze treatment success rates to improve treatment plans, minimizing complications and readmissions
Increasing Income and Revenue: Prevent fraudulent behavior and identify opportunities to collect missing income
This document discusses data warehousing, knowledge discovery in databases (KDD), and data mining. It defines a data warehouse as a subject-oriented collection of integrated and non-volatile data used to support management decision making. Data mining is extracting knowledge from large amounts of data and has two main uses: making sense of too much data with too little information and extracting useful information from data to interpret it. The document also discusses applications of data mining in areas like banking, marketing, risk management, and customer acquisition/retention.
The document discusses the digital health agenda and strategy for collecting, aggregating, and analyzing patient data across the NHS. It makes the following key points:
1) The NHS interacts with over 1 million patients every 36 hours, and the goal is to capture data from each interaction, convert it to digital format, and aggregate it.
2) This aggregated data can be analyzed to generate knowledge that improves patient outcomes, addresses sustainability challenges, and enhances the healthcare system.
3) A digital maturity program called "Paperless 2020" provides the strategy, which includes standards for data sharing, security, analytics and other domains to realize this vision.
Penser Consulting answers the key questions:
- What is big data, and why does it matter?
- How can big data drive business decisions?
- How can you build data analytics capabilities in your organisation?
Augmented intelligence pietro_leo_sole24_ore_schoolPietro Leo
This document discusses using artificial intelligence and cognitive computing to make precise decisions. It begins by explaining how AI techniques like natural language processing, knowledge representation, reasoning, and planning can be used for advanced tasks. It then discusses how cognitive computing leverages a combination of these techniques and machine learning over deep domain models to make data-driven predictions and evidence-based explanations. The document provides examples of how IBM is applying these approaches through technologies like IBM Watson to transform industries like healthcare, retail, manufacturing and more by improving decision making, customer service, and other outcomes.
This group paper, written as a graduate student at CMU, attempts to define and summarize the huge challenge ahead of North American healthcare providers by illuminating current and future trends of healthcare business intelligence (BI); ramifications of EMR; the pros and cons of BI and analytics; the myriad ethical and privacy issues of big data’s role (normally associated with market share and profits); and lastly provide an industry overview of BI and analytics solutions specific to healthcare.
To view the 30+ page paper for which this presentation summarizes, please contact James Young via LinkedIn: https://www.linkedin.com/in/jamesyoung007
This document provides an overview of predictive analytics. It discusses what predictive analytics is and how it is used by organizations to make smarter decisions about customers. Predictive analytics uses historical data and statistical techniques to predict future outcomes and automate decisions. Examples are given of how predictive analytics has helped industries like financial services, insurance, telecommunications, retail, and healthcare improve customer decisions and outcomes.
The document discusses business analytics and how it was used by the Cincinnati Zoo and Botanical Garden to increase revenue and attendance. Specifically, it allowed the zoo to optimize food outlet operations, eliminate underperforming products, and use visitor data to target marketing to increase attendance by 4.2%. In general, business analytics involves using data, analytics, and technology to help managers make better fact-based decisions to improve various business operations and outcomes.
This document provides information about the "Big Data & Analytics for Pharma Summit" event taking place on November 3-4, 2016 in Philadelphia. The event will focus on challenges in pharmaceutical R&D, drug development, and safety monitoring, and how analytics can help address these challenges in an evolving market focused on patient-centricity. Key themes include real-world data usage, marketing, business models, decision making, and drug research. The agenda includes keynote speakers from major pharmaceutical companies discussing various analytics applications and case studies.
W.UP Sales.UP digital sales and engagement tool for banksW.UP
This document discusses the challenges facing banks from increasing competition and shifting customer expectations. It notes that origination and sales generate most banking profits but are now at risk. The document then introduces SALES.UP as a solution that uses customer data and AI to generate personalized insights and timely campaigns to boost digital sales and engagement. It provides examples of how SALES.UP can improve conversion rates and revenues. Finally, it includes a case study of a bank that implemented SALES.UP to better target customers.
François Protopapa gave a presentation on how data is changing consumer experiences. He discussed how the amount of data being created is growing exponentially and how businesses can collect consumer data as their most valuable asset. However, he emphasized that data must be properly analyzed and used to make good decisions in order to improve customer experiences and business performance. Protopapa proposed that companies implement a customer intelligence hub and platform to better integrate data across silos, generate insights, and provide an omnichannel customer experience.
Re:Imagine Pharma Marketing - Agenda at a Glancebarberenar
There have been many COVID driven impacts on customer engagement and marketing processes, tools, and tactics. However, even with the advancement of digital marketing and commercial transformation, in-person engagement still remains the cornerstone of the pharma marketing business.
While we should celebrate the small wins and pivots that have been made as a result of COVID forced change, it is vital to understand which of these changes are transitory and which are true, long lasting transformations and innovation to be built on, and embedded in future processes and planning.
What will be our indicators and measurements of value moving forward?
What are the content consumption habits/behaviors of HCPs now?
How can I de-risk from supply chain to product development to commercial activity?
How can I diversify our clinical trial recruitment and innovation?
Does reimbursement need to be integrated with innovation?
How can I effectively virtualize customer engagement, branding and product launches?
What is the right promotional mix, even if/when sales force can return?
To what extent are the different stakeholder activities changing/overlapping as business needs evolve?
These are just a fraction of the issues currently creating bottlenecks that require proactive future planning and careful roadmap development.
Join our expert speaker faculty, the Thought Leadership Council and many of your industry peers to develop this roadmap together as a true community.
Data science is transforming the fields of finance and accounting by automating many routine tasks through algorithms while also creating jobs that require more technical skills. Data scientists are helping financial institutions gain valuable customer insights from analyzing transaction data to improve services, detect fraud, and increase regulatory compliance. By building comprehensive customer profiles, data science allows banks to better understand customer preferences and reduce costs through more efficient processes. The growing use of data science and artificial intelligence is fundamentally changing the banking industry.
The document discusses how big data is being adopted across various industries with healthcare and commerce having the highest potential for growth. It provides examples of how big data is being used in healthcare for clinical decision making, operations, preventative medicine, and customer service. Challenges to healthcare big data adoption include a lack of skills, high costs, data security, and different data formats. Banking examples show big data use for fraud prevention, compliance, risk management, and customer insights. Challenges for banking include legal and privacy issues, data quality, and skills shortages. Future trends will include more personalized care and monitoring through interconnected devices and data sources.
JetFerry: Background Info on Business IntelligenceTechFerry
Business intelligence (BI) aims to transform data into meaningful information to support business decisions and growth. BI evolved from manually assembled reports in the pre-1970s to performance management occurring twice a year in the 1990s to today's real-time analytics and predictive insights. BI blends tools, processes, and skills to analyze large volumes of data, allowing effective decisions through access to clean, high-quality data visualization and insights. The future of BI includes enhanced data-driven insights, identifying strategies through natural language queries, and more personalized and real-time intelligent decision automation.
Insurance Service Meeting 2016 - Andrea Eichhorn CNseg
Cognitive solutions are transforming the insurance industry by helping insurers shift their focus from cost cutting to improving customer engagement and experience. Insurers are leveraging cognitive technologies like IBM Watson to better understand customers, more accurately assess risk, improve processes across the insurance value chain, and develop new personalized products and services. Adopting a cognitive strategy allows insurers to achieve strategic priorities like reducing costs and risk while enhancing the customer experience through human-like interaction with data and analytics.
Indian banking players face several challenges with big data including legal and regulatory issues, privacy and security concerns, a lack of skilled professionals, and data quality problems. However, big data can help banks with fraud detection and prevention, enhanced compliance reporting, customer segmentation, and personalized product offerings. Healthcare enterprises are already using various types of data including human-generated data, web and social media data, biometric data, and machine-to-machine data. As data has evolved from structured to unstructured forms, modern big data solutions can improve clinical trials, decision making, preventative healthcare, and more. Effective use of data across the healthcare ecosystem requires collaboration between players such as providers, payers, pharmacies, and patients.
The banking world is competitive. According to the FDIC, as of June 30th, 2017, consumers have a choice between 5,787 banks in the United States. Needless to say, their pickings are not slim. So out of the 5,000+ banks, what separates the top dogs from the rest? Here is a list of five things that successful banks do differently when it comes to banking software.
http://bit.ly/SuccessfulBanks
To successfully onboard banking clients, you must have these five essential tools: mobile capabilities, e-signature, analytics, understanding, and cloud.
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This document discusses effective practice management. It describes Med e Mass, a leading practice management company in South Africa that provides software and services to 9500 doctors. Effective practice management involves implementing long-term strategic plans, protocols, and controls to improve organization, reduce reactivity, and allow doctors to make informed decisions for practice growth while managing risks like data security. A practice management system can deliver improved efficiency, productivity, financial information, correspondence capabilities, and mitigate cash flow risks through features like electronic billing, reporting, user-friendly interfaces, and innovation.
Frederieke Jacobs on GDPR & digital health @ Health 2.0 Amsterdam, June 2018 kasiarab
Frederieke Jacobs (journalist, SmartHealth), "Overview of recent developments re privacy & digital health" https://www.linkedin.com/in/frederieke-jacobs
This is a presentation from a Health 2.0 Amsterdam "GDPR & healthcare: towards harvesting health from our data" event that took place on the 18th of June 2018
https://www.meetup.com/Health-2-0-Amsterdam/events/250870609/
The document discusses data warehousing, knowledge discovery in databases (KDD), and data mining. It defines a data warehouse as a subject-oriented collection of integrated and non-volatile data used to support management decision making. Data mining is extracting knowledge from large amounts of data and has applications in business transactions, ecommerce, healthcare, and more. Specifically for banking, data mining can be used for marketing, risk management, and customer acquisition/retention by identifying patterns in large customer data sets.
Lower Total Cost of Care and Gain Valuable Patient Insights through Predictiv...Perficient, Inc.
Learn how predictive analytics for healthcare can enable your organization to make proactive decisions that can have a profound impact for both patients and care providers. We discuss current and emerging healthcare trends and the positive impact that predictive analytics can have on your organization by:
Optimizing Resource Utilization: Better allocate nurses, clinicians, diagnostic machinery and other resources by predicting future admission volumes
Enhancing Patient Care: Proactively treat patients by more accurately predicting the chance of a chronic condition or the response to medications and therapies
Improving Clinical Outcomes: Analyze treatment success rates to improve treatment plans, minimizing complications and readmissions
Increasing Income and Revenue: Prevent fraudulent behavior and identify opportunities to collect missing income
This document discusses data warehousing, knowledge discovery in databases (KDD), and data mining. It defines a data warehouse as a subject-oriented collection of integrated and non-volatile data used to support management decision making. Data mining is extracting knowledge from large amounts of data and has two main uses: making sense of too much data with too little information and extracting useful information from data to interpret it. The document also discusses applications of data mining in areas like banking, marketing, risk management, and customer acquisition/retention.
The document discusses the digital health agenda and strategy for collecting, aggregating, and analyzing patient data across the NHS. It makes the following key points:
1) The NHS interacts with over 1 million patients every 36 hours, and the goal is to capture data from each interaction, convert it to digital format, and aggregate it.
2) This aggregated data can be analyzed to generate knowledge that improves patient outcomes, addresses sustainability challenges, and enhances the healthcare system.
3) A digital maturity program called "Paperless 2020" provides the strategy, which includes standards for data sharing, security, analytics and other domains to realize this vision.
Penser Consulting answers the key questions:
- What is big data, and why does it matter?
- How can big data drive business decisions?
- How can you build data analytics capabilities in your organisation?
Augmented intelligence pietro_leo_sole24_ore_schoolPietro Leo
This document discusses using artificial intelligence and cognitive computing to make precise decisions. It begins by explaining how AI techniques like natural language processing, knowledge representation, reasoning, and planning can be used for advanced tasks. It then discusses how cognitive computing leverages a combination of these techniques and machine learning over deep domain models to make data-driven predictions and evidence-based explanations. The document provides examples of how IBM is applying these approaches through technologies like IBM Watson to transform industries like healthcare, retail, manufacturing and more by improving decision making, customer service, and other outcomes.
This group paper, written as a graduate student at CMU, attempts to define and summarize the huge challenge ahead of North American healthcare providers by illuminating current and future trends of healthcare business intelligence (BI); ramifications of EMR; the pros and cons of BI and analytics; the myriad ethical and privacy issues of big data’s role (normally associated with market share and profits); and lastly provide an industry overview of BI and analytics solutions specific to healthcare.
To view the 30+ page paper for which this presentation summarizes, please contact James Young via LinkedIn: https://www.linkedin.com/in/jamesyoung007
This document provides an overview of predictive analytics. It discusses what predictive analytics is and how it is used by organizations to make smarter decisions about customers. Predictive analytics uses historical data and statistical techniques to predict future outcomes and automate decisions. Examples are given of how predictive analytics has helped industries like financial services, insurance, telecommunications, retail, and healthcare improve customer decisions and outcomes.
The document discusses business analytics and how it was used by the Cincinnati Zoo and Botanical Garden to increase revenue and attendance. Specifically, it allowed the zoo to optimize food outlet operations, eliminate underperforming products, and use visitor data to target marketing to increase attendance by 4.2%. In general, business analytics involves using data, analytics, and technology to help managers make better fact-based decisions to improve various business operations and outcomes.
This document provides information about the "Big Data & Analytics for Pharma Summit" event taking place on November 3-4, 2016 in Philadelphia. The event will focus on challenges in pharmaceutical R&D, drug development, and safety monitoring, and how analytics can help address these challenges in an evolving market focused on patient-centricity. Key themes include real-world data usage, marketing, business models, decision making, and drug research. The agenda includes keynote speakers from major pharmaceutical companies discussing various analytics applications and case studies.
W.UP Sales.UP digital sales and engagement tool for banksW.UP
This document discusses the challenges facing banks from increasing competition and shifting customer expectations. It notes that origination and sales generate most banking profits but are now at risk. The document then introduces SALES.UP as a solution that uses customer data and AI to generate personalized insights and timely campaigns to boost digital sales and engagement. It provides examples of how SALES.UP can improve conversion rates and revenues. Finally, it includes a case study of a bank that implemented SALES.UP to better target customers.
François Protopapa gave a presentation on how data is changing consumer experiences. He discussed how the amount of data being created is growing exponentially and how businesses can collect consumer data as their most valuable asset. However, he emphasized that data must be properly analyzed and used to make good decisions in order to improve customer experiences and business performance. Protopapa proposed that companies implement a customer intelligence hub and platform to better integrate data across silos, generate insights, and provide an omnichannel customer experience.
Re:Imagine Pharma Marketing - Agenda at a Glancebarberenar
There have been many COVID driven impacts on customer engagement and marketing processes, tools, and tactics. However, even with the advancement of digital marketing and commercial transformation, in-person engagement still remains the cornerstone of the pharma marketing business.
While we should celebrate the small wins and pivots that have been made as a result of COVID forced change, it is vital to understand which of these changes are transitory and which are true, long lasting transformations and innovation to be built on, and embedded in future processes and planning.
What will be our indicators and measurements of value moving forward?
What are the content consumption habits/behaviors of HCPs now?
How can I de-risk from supply chain to product development to commercial activity?
How can I diversify our clinical trial recruitment and innovation?
Does reimbursement need to be integrated with innovation?
How can I effectively virtualize customer engagement, branding and product launches?
What is the right promotional mix, even if/when sales force can return?
To what extent are the different stakeholder activities changing/overlapping as business needs evolve?
These are just a fraction of the issues currently creating bottlenecks that require proactive future planning and careful roadmap development.
Join our expert speaker faculty, the Thought Leadership Council and many of your industry peers to develop this roadmap together as a true community.
Data science is transforming the fields of finance and accounting by automating many routine tasks through algorithms while also creating jobs that require more technical skills. Data scientists are helping financial institutions gain valuable customer insights from analyzing transaction data to improve services, detect fraud, and increase regulatory compliance. By building comprehensive customer profiles, data science allows banks to better understand customer preferences and reduce costs through more efficient processes. The growing use of data science and artificial intelligence is fundamentally changing the banking industry.
The document discusses how big data is being adopted across various industries with healthcare and commerce having the highest potential for growth. It provides examples of how big data is being used in healthcare for clinical decision making, operations, preventative medicine, and customer service. Challenges to healthcare big data adoption include a lack of skills, high costs, data security, and different data formats. Banking examples show big data use for fraud prevention, compliance, risk management, and customer insights. Challenges for banking include legal and privacy issues, data quality, and skills shortages. Future trends will include more personalized care and monitoring through interconnected devices and data sources.
JetFerry: Background Info on Business IntelligenceTechFerry
Business intelligence (BI) aims to transform data into meaningful information to support business decisions and growth. BI evolved from manually assembled reports in the pre-1970s to performance management occurring twice a year in the 1990s to today's real-time analytics and predictive insights. BI blends tools, processes, and skills to analyze large volumes of data, allowing effective decisions through access to clean, high-quality data visualization and insights. The future of BI includes enhanced data-driven insights, identifying strategies through natural language queries, and more personalized and real-time intelligent decision automation.
Insurance Service Meeting 2016 - Andrea Eichhorn CNseg
Cognitive solutions are transforming the insurance industry by helping insurers shift their focus from cost cutting to improving customer engagement and experience. Insurers are leveraging cognitive technologies like IBM Watson to better understand customers, more accurately assess risk, improve processes across the insurance value chain, and develop new personalized products and services. Adopting a cognitive strategy allows insurers to achieve strategic priorities like reducing costs and risk while enhancing the customer experience through human-like interaction with data and analytics.
Indian banking players face several challenges with big data including legal and regulatory issues, privacy and security concerns, a lack of skilled professionals, and data quality problems. However, big data can help banks with fraud detection and prevention, enhanced compliance reporting, customer segmentation, and personalized product offerings. Healthcare enterprises are already using various types of data including human-generated data, web and social media data, biometric data, and machine-to-machine data. As data has evolved from structured to unstructured forms, modern big data solutions can improve clinical trials, decision making, preventative healthcare, and more. Effective use of data across the healthcare ecosystem requires collaboration between players such as providers, payers, pharmacies, and patients.
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The banking world is competitive. According to the FDIC, as of June 30th, 2017, consumers have a choice between 5,787 banks in the United States. Needless to say, their pickings are not slim. So out of the 5,000+ banks, what separates the top dogs from the rest? Here is a list of five things that successful banks do differently when it comes to banking software.
http://bit.ly/SuccessfulBanks
To successfully onboard banking clients, you must have these five essential tools: mobile capabilities, e-signature, analytics, understanding, and cloud.
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Reusable solutions reduce costs and time to market. This is a presentation from IBM Insight 2014 about how to leverage IBM Case Manager as an enterprise-wide reusable solution.
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Synopsis
In this synthetic case study, Pyramid Solutions demonstrates how we help insurance providers over the years by combining our ECM best practices and technology.
The Guidewire suite of products are great point solutions. But what happens when people outside of a Guidewire user group (like people in the legal department) need access to documents located in PolicyCenter? The answer is simple: they can’t. Learn how to bridge department silos so your organization always has enterprise-wide visibility and accessibility of documents.
When businesses do not uphold service level agreements (SLAs) customer satisfaction drops, operational costs rise, and management oversight complicates. Discover how Pyramid Solutions uses IBM Bluemix, SPSS and IBM Case Manager to help businesses monitor and manage SLAs in the onboarding process.
Congratulations! You captured information to classify and organize your documents. But now how do you leverage that information? Instead of putting it on the wayside, have all your employees utilize it. See show how businesses combine cognitive capture and case management technologies to gain insight and acumen.
Union Bank slashed onboarding times with analytics, mobile, and e-signatures. They completed Phase 1 of their project with IBM in 22 weeks, automating processes and forms. Phase 2 added tactical analytics for pipeline reporting, a mobile case app for real-time updates, and e-signatures to take documents directly from IBM Case Manager. This improved the mobile workforce's access to information and ability to interact with cases on the go.
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Onboarding processes that are fragmented and lengthy leave room for missed opportunities and high abandonment rates. Ultimately reflecting poorly on a bank’s reputation and the bottom line. Today’s clients expect convenient, timely and accurate service – on their terms.
Watch to learn how you can modernize your client onboarding process delivering a superior customer experience with client capture, personalization, e-signature, analytics and cloud.
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Disparate enterprise content management (ECM) solutions for underwriting, claims, and supporting groups, such as accounting, and risk and compliance, made it cumbersome to gather a holistic-view of policy holder content throughout the life of a policy and make it readily available to all authorized employees and third parties. By introducing an advanced case management solution, the property and casualty division is streamlining content and processes to help teams work together faster and more productively.
Complete Solutions in ECM using IBM, Internal and Third Party, Custom ComponentsPyramid Solutions, Inc.
Pyramid Solutions showcased how real-world customers have used IBM Content Navigator and IBM Case Manager to develop solutions that can be applied to the entire enterprise. Using the extendibility of Content Navigator has allowed customers to use custom components that were developed in-house in conjunction with third-party and OOTB components to develop complete solutions to meet the users’ needs. This session examines how custom components can be built and combined with third-party and IBM products. It also examines the flexibility of component design that enables flexible interfaces that can be used across content and case management solutions without the need to develop separate components.
In this whitepaper, you'll learn how you can use barcodes to error-proof your production line.
Your customers are anticipating quality and on time shipments at the lowest cost possible. Barcode technology has allowed for advanced capabilities to not only ensure the right parts are in the right place at the right time, or accurate inventory but gives manufactures the piece of mind that they are producing quality parts.
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
In our second session, we shall learn all about the main features and fundamentals of UiPath Studio that enable us to use the building blocks for any automation project.
📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...AlexanderRichford
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
Discover the Unseen: Tailored Recommendation of Unwatched ContentScyllaDB
The session shares how JioCinema approaches ""watch discounting."" This capability ensures that if a user watched a certain amount of a show/movie, the platform no longer recommends that particular content to the user. Flawless operation of this feature promotes the discover of new content, improving the overall user experience.
JioCinema is an Indian over-the-top media streaming service owned by Viacom18.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Getting the Most Out of ScyllaDB Monitoring: ShareChat's TipsScyllaDB
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
3. DISRUPTORS ABOUND
MILLENNIALS
Demand interactive and instantaneous buying
experience
NON-TRADITIONAL PRODUCTS
Focus mostly on health benefits and less on
mortality risk
NEW EXTERNAL PLAYERS
Abundance of capital and knowledge of
consumer buying habits
Millennials
Non-
traditional
products
External
players
4. CARRIER PAINS
MAXIMIZING FAST TRACK
Better, more informed decisions
STREAMLINING THE PROCESS
Special authorizations, APS processing
MORE WITH LESS
Avoid medical records and paramed exams
ACCURATE RATING
Greater insight to rate more precisely
Carrier
Reinsurer
Decision
5. INTELLIGENT ASSESSMENT
What is the level of risk?
Risk Score
Content Æ Data Æ Information Æ Decision
MIB
Cognitive
Engine
Fast Track
Underwriting
PolicyTHE
UNDERWRITING
PROCESS
6. EXTRACTING KEY MEDICAL DATA
Establish a chronology of declared and reported information
Diagnoses
Prescriptions
Procedures
Chronology
Handwriting
Redundant text
MIB
Medical
Extractor
Key Info Bookmarked
7. 2011 2012 2013 2014 2015 2016
Colon polyps / benign Angina
Diabetes Type II
DIAGNOSES / TREATMENTS
PRESCRIPTIONS / DOSAGE
Propranolol
Metformin
GOAL: ASSIMILATE DIAGNOSTIC AND RX INFO
AND LAB RESULTS INTO APPLICANT TIMELINE
8. Content Navigator
A unified user experience for capture, content and case
SOURCE
MFP
Tablet
FaxArchive
Scanner
E-mail
Smartphone
Network
Scanner
Datacap
Web, Desktop, Mobile
TRANSFORM
Look-Up
Verify Rules
ClassifyExtract
OMR BarcodeOCR ICR
DELIVER
Web Portal
LOB
Solutions
BPM
ECM On-
Premise
ECM
Cloud
Case
Mgmt.
IBM DOCUMENT CAPTURE CAPABILITIES
At a glance
17. PRESENT CONDITIONS
Provide high level view of applicant conditions
HIGHER RISK
2010 2011 2012 2013 2014 2015 2016
AnginaColon Polyps Benign
Diabetes Type II
High Cholesterol
Propanolol
Lipitor
Metformin
DIAGNOSES / TREATMENTS
PRESCRIPTIONS / DOSAGE
Propanolol
18. CONTINUOUS ASSESSMENT
What’s next
Risk Score
Train
Content Æ Data Æ Information Æ Decision Æ Feedback
MIB
Predictive Model
Cognitive
Engine
Underwriter
Fast Track?
APS Requests
Rating Support