Presented by Mike Rhodin, Senior VP, Software Solutions Group, at IBM InterConnect 2013.
Session titled: Best Practices in Becoming a Smarter Enterprise.
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.
[WSO2Con Asia 2018] Unravelling Todays Disruptive Tech LandscapeWSO2
This document provides an overview and analysis of emerging technologies and their impact on the middleware landscape. It segments middleware into seven categories and estimates their market sizes and growth rates. Emerging technologies like blockchain, serverless computing, and AI are shaping the landscape and interactions between segments. The document analyzes these technologies using frameworks to understand their history, hype cycles, and potential impacts. It presents timelines for publishing reports on serverless and blockchain technologies and identifies other areas like chatbots and IoT that need analysis. The overall goal is to provide an understanding of current and future technology markets and opportunities for discussion.
Beyond analytics: Prescriptive analytics for the future of your business by Á...Big Data Spain
Analytics has undoubtedly changed the way businesses are operated. It has made clearer than ever that what cannot be measured cannot be managed. However, about 80% of Big Data projects still merely rely on descriptive analytics. While clever visualizations of the business data can be of great aid in the decision making process, there is much more value to be explored through deeper analytical processes. Whenever information about business rules and costs is available, prescriptive analytics can recommend efficient courses of action to optimize costs or revenues.
Session presented at Big Data Spain 2015 Conference
16th Oct 2015
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Abstract: http://www.bigdataspain.org/program/fri/slot-29.html#spch29.2
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
Business analytics is the practice of iterative statistical analysis of a company's data to support data-driven decision making. It has evolved from early uses of basic graphs and spreadsheets to track sales trends and predict outcomes, to modern applications that gain insights from large volumes of historical data using descriptive analytics and predict customer behavior using predictive analytics to inform real-time decisions. Common business analytics tools include SPSS for statistical analysis and Microsoft Excel for calculations, graphs, and pivot tables.
Today's Technology and Emerging Technology LandscapeSrinath Perera
We have seen the rise and fall of many technologies, some disappearing without a trace while others redefining the world. Collectively they have shaped our world beyond recognition. In this talk, Srinath will start with past technologies exploring their behavior. Then he will explore current middleware landscape, its composition, and relationships between different segments. He will discuss significant developments and discuss their future. Further, he will discuss emerging technologies, forces that shape them, and the promise of each technology, and finally, speculate about their evolution. You will walk away with knowledge on the evolution of middleware, the status quo, and discussion about how, at WSO2, we think those technologies will evolve.
This document describes an all-in-one AI-based cloud application for the insurance industry called PENTATION Analytics. It provides intelligence driven servicing through unique and actionable interventions. The application utilizes structured data, text data, new data assets and intervention models in AI powered predictive models. It aims to be a one stop shop solution accessible to CEOs, underwriters and agents through a cloud dashboard.
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.
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.
[WSO2Con Asia 2018] Unravelling Todays Disruptive Tech LandscapeWSO2
This document provides an overview and analysis of emerging technologies and their impact on the middleware landscape. It segments middleware into seven categories and estimates their market sizes and growth rates. Emerging technologies like blockchain, serverless computing, and AI are shaping the landscape and interactions between segments. The document analyzes these technologies using frameworks to understand their history, hype cycles, and potential impacts. It presents timelines for publishing reports on serverless and blockchain technologies and identifies other areas like chatbots and IoT that need analysis. The overall goal is to provide an understanding of current and future technology markets and opportunities for discussion.
Beyond analytics: Prescriptive analytics for the future of your business by Á...Big Data Spain
Analytics has undoubtedly changed the way businesses are operated. It has made clearer than ever that what cannot be measured cannot be managed. However, about 80% of Big Data projects still merely rely on descriptive analytics. While clever visualizations of the business data can be of great aid in the decision making process, there is much more value to be explored through deeper analytical processes. Whenever information about business rules and costs is available, prescriptive analytics can recommend efficient courses of action to optimize costs or revenues.
Session presented at Big Data Spain 2015 Conference
16th Oct 2015
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Abstract: http://www.bigdataspain.org/program/fri/slot-29.html#spch29.2
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
Business analytics is the practice of iterative statistical analysis of a company's data to support data-driven decision making. It has evolved from early uses of basic graphs and spreadsheets to track sales trends and predict outcomes, to modern applications that gain insights from large volumes of historical data using descriptive analytics and predict customer behavior using predictive analytics to inform real-time decisions. Common business analytics tools include SPSS for statistical analysis and Microsoft Excel for calculations, graphs, and pivot tables.
Today's Technology and Emerging Technology LandscapeSrinath Perera
We have seen the rise and fall of many technologies, some disappearing without a trace while others redefining the world. Collectively they have shaped our world beyond recognition. In this talk, Srinath will start with past technologies exploring their behavior. Then he will explore current middleware landscape, its composition, and relationships between different segments. He will discuss significant developments and discuss their future. Further, he will discuss emerging technologies, forces that shape them, and the promise of each technology, and finally, speculate about their evolution. You will walk away with knowledge on the evolution of middleware, the status quo, and discussion about how, at WSO2, we think those technologies will evolve.
This document describes an all-in-one AI-based cloud application for the insurance industry called PENTATION Analytics. It provides intelligence driven servicing through unique and actionable interventions. The application utilizes structured data, text data, new data assets and intervention models in AI powered predictive models. It aims to be a one stop shop solution accessible to CEOs, underwriters and agents through a cloud dashboard.
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.
This document discusses Alliander's use of big data analytics to support its smart grid. It outlines some of the challenges Alliander faces with an aging grid and energy transition. Alliander is using big data analytics to gain better insight into grid behavior at lower voltage levels and make more information-based and customer-focused investments. Examples shown include asset health analytics to identify risky joints and a sensor system to detect potential cable defects in real-time. The document also discusses Alliander's analytics ecosystem and portfolio approach to innovating, validating, and implementing analytics, as well as the new skills that will be required for continued development.
Operationalizing Data Science: The Right Architecture and ToolsVMware Tanzu
In part one of this two-part series, you learned some of the common reasons enterprises struggle to turn insights into actions as well as a strategy for overcoming these challenges to successfully operationalize data science. In part two, it’s time to fill in the architectural and technological details of that strategy.
Pivotal Data Scientist Megha Agarwal will share the key ingredients to successfully put data science models in production and use them to drive actions in real-time. In this webinar, you will learn:
- Adopting extreme programming practices for data science
- Importance of working in a balanced team
- How to put and maintain machine learning models in production
- End-to-end pipeline design
Presenter: Megha Agarwal, Data Scientist
Blockchain is a revolutionary technology for some industries and applications, however it is commonly misunderstand and confused with the cryptocurrency Bitcoin. Blockchain is the underlying technology that makes Bitcoin and other cryptocurrencies possible, but it can be used for much more than cryptocurrencies alone. This presentation explains what Blockchain is, how it works and expounds on the uses of blockchain technology outside of cryptocurrencies in order to equip IT auditors with the knowledge they need to advise their companies on blockchain implementations. Blockchain has several very real uses cases, such as in logistics and financial payments clearing, however there is a lot of misleading or false information out there. The basics between what a public and private blockchain is, how the chain operates, what are miners, what security considerations exist, etc. will be discussed, along with an overview of how to audit this technology.
Understand what Blockchain is
Describe the differences between public and private blockchains
Understand where blockchain can be useful to companies, and where it is unnecessary
What security considerations exist
Be able to perform a basic Blockchain audit
Big data machine learning and predictive analytics have become an integral part of the retail industry. Enterpises across the world have now begun making informed decisions backed by data.
How advanced analytics is impacting the banking sectorMichael Haddad
The document discusses how advanced analytics is impacting the banking sector. It covers topics like regulatory changes forcing banks to invest in compliance; new digital technologies changing how customers interact with banks; and data analytics helping banks reduce risk, deliver personalized services, and retain skills. It also discusses Hitachi Data Systems' acquisition of Pentaho and how their combined platform can provide unified data integration and business analytics across structured, unstructured, and streaming data sources.
Seminar & Talkshow : How Big Data & IoT Create Smart Environment and Business...Tunjung Utomo
- Big data is a large collection of datasets that were once difficult to process due to their size and complexity but can now be managed through tools and expertise.
- Big data changes business by allowing companies to use data as an asset to create new products/services, gain better customer insights, improve efficiency, and enable near real-time analysis for decision making.
- Examples of big data use cases include using location data to analyze visitor patterns at an F1 race, using predictive analytics for better sales and pricing recommendations, conducting root cause analysis to reduce costs, enabling real-time equipment monitoring for efficiency, and monitoring business performance metrics.
The document discusses how IT operations are facing big data challenges due to the large volume, variety, and velocity of IT information. It argues that applying big data analytics to IT operations data can help address these challenges and extract value. Specifically, IT operations analytics tools can collect all types of IT data, provide insights into potential problems, and help IT operations teams detect issues early before they impact customers. These tools analyze patterns and relationships to spot problems faster and reduce false alerts.
Data has become a key focus for corporate leaders today. Chartered Global Management Accountant (CGMA) designation holders are well placed to help translate data into commercial insights and value.
Data Science: The Art of Foul Play by Serhiy ShelpukSoftServe
Serhiy Shelpuk, Lead Data Scientist, Competence Manager at SoftServe, Inc., delivered an insightful presentation on Data Science and SoftServe`s Data Science Group Knowledge Model at the 2013 IT Weekend Ukraine conference that took place on September 14, 2013, in Kyiv, Ukraine. Here`s his presentation.
With so much noise and buzzwords floating around regarding data analytics, it can be rather difficult to decipher between the signal (what is worthwhile) and what is only talk. Sometimes the rhetoric even starts within your organization, confounding the issue further. During Andrew’s session, he will provide attendees with the knowledge they need to tune out the bogus information while gleaning valuable insights for developing and deploying their audit analytics program. The presentation will conclude with tangible examples of a successful Manufacturing Audit Analytics program, and recommendations for how to get yours up and running. After attending, participants will be able to articulate how steps for setting up an analytics program within their departments, as well be armed with knowledge for educating senior leadership on the fundamental changes in technology that are occurring, and what is just marketing.
Five Pitfalls when Operationalizing Data Science and a Strategy for SuccessVMware Tanzu
Enterprise executives and IT teams alike know that data science is not optional, but struggle to benefit from it because the process takes too long and operationalizing models in applications can be hairy.
Join guest speaker, Forrester Research’s Mike Gualtieri and Pivotal’s Jeff Kelly and Dormain Drewitz for an interactive discussion about operationalizing data science in your business. In this webinar, the first of a two-part series, you will learn:
- The essential value of data science and the concept of perishable insights.
- Five common pitfalls of data science teams.
- How to dramatically increase the productivity of data scientists.
- The smooth hand-off steps required to operationalize data science models in enterprise applications.
Presenter : Guest Speakers Mike Gualtieri, Forrester, Dormain Drewitz and Jeff Kelly, Pivotal
[Ai in finance] AI in regulatory compliance, risk management, and auditingNatalino Busa
AI to Improve Regulatory Compliance, Governance & Auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests.
Machine Learning, Internet of Things and Unlocking Your Earning PotentialSmith Hanley Associates
The Analytical Recruiters at Smith Hanley Associates share with you the hottest trend in the data science job market for 2017, machine learning, the hottest trend for the future, IoT, and where your compensation should be in this competitive marketplace.
Big Data & Business Analytics: Understanding the MarketspaceBala Iyer
This document provides an overview of big data and business analytics. It discusses the growth of data and importance of analytics to businesses. The key topics covered include defining big data and data science, analyzing the analytics ecosystem and key players, examining use cases of analytics at companies like Target and Whirlpool, and providing recommendations for building an analytics capability and working with analytics vendors. The presentation emphasizes how data-driven decisions can improve business performance but also notes challenges to overcome like skills shortages and changing organizational culture.
Modak Analytics provides predictive modeling solutions to help companies analyze customer data and make reliable decisions. Predictive modeling involves [1] analyzing piled up customer data to derive useful insights, [2] designing a predictive model using various techniques like clustering, decision trees, regression, and scorecards, and [3] implementing the model to better understand customers and make profitable decisions. Predictive analysis allows companies to segment markets, rank products, predict customer responses, and reduce fraud. Modak Analytics' customized solutions leverage different modeling techniques to create ensemble models that extract the strengths of each technique.
The document discusses the need for "Smart Data" over "Big Data". It argues that while Big Data has potential, the technology is constantly evolving and data scientists with the needed skills are scarce and expensive. It advocates for providing business users with self-service analytics capabilities to answer over 90% of their questions quickly without IT assistance. Examples are provided of how self-service analytics helped Coca-Cola and JD Group gain insights from their data more efficiently.
NUS-ISS Learning Day 2018- Start with Data GovernanceNUS-ISS
The document discusses starting data governance from where an organization currently is. It highlights common questions around data that indicate a need for governance. The document then discusses using data to improve operations, customer experience, and more. It also outlines how data is changing different industries. The rest of the document discusses data governance in more detail, including defining it, ensuring data quality, and addressing compliance and security challenges. It provides examples of legislation and offers a framework for establishing an effective data governance program.
This document summarizes the services of a company that provides data analysis and machine learning solutions. They have an interdisciplinary team with over 15 years of experience in areas like machine learning, artificial intelligence, big data, and data engineering. Their expertise includes developing data models, analysis products, and systems to help companies with forecasting, decision making, and improving data operations efficiency. They can help clients across various industries like telecom, finance, retail, and more.
Credit Card Fraud Detection Using ML In DatabricksDatabricks
In the Credit Card Companies, illegitimate credit card usage is a serious problem which results in a need to accurately detect fraudulent transactions vs non-fraudulent transactions. All organizations can be hugely impacted by fraud and fraudulent activities, especially those in financial services. The threat can originate from internal or external, but the effects can be devastating – including loss of consumer confidence, incarceration for those involved, even up to downfall of a corporation. Despite regular fraud prevention measures, these are constantly being put to the test in an attempt to beat the system.
Fraud detection is a task of predicting whether a card has been used by the cardholder. One of the methods to recognize fraud card usage is to leverage Machine Learning (ML) models. In order to more dynamically detect fraudulent transactions, one can train ML models on a set of dataset including credit card transaction information as well as card and demographic information of the owner of the account. This will be our goal of the project while leveraging Databricks.
Decision Point AI, plan around what will happen instead of what has happened?Karl Smith
Presentation pack for Decision Point AI, Europe and USA. Focus, will the government approve a merger? and
will the combined M&A firms deliver good value?
IBM InterConnect 2015 - What is New in IBM Connections 2015Luis Benitez
This document provides a summary of new features and updates for IBM Connections and IBM Connections Mobile. It discusses enhancements delivered via cloud updates in 2014 and plans for 2015, including increased storage limits, file syncing for Mac, improved search and profiles, and additional mobile updates. The presentation emphasizes IBM's cloud-first development approach and focus on continuous delivery of updates. It highlights both current capabilities and planned future innovations.
IBM Connections Cloud & IBM Docs: Working securely and quickly with contentLuis Benitez
Are you struggling to manage your unstructured social content? Imagine combining the power of social and real-time document collaboration with ECM-grade native repositories and document management to help. This session will explore the benefits of online editors like IBM Docs that help to improve productivity and reduce the review and rework cycles associated with team-based business documents. Discover how to extend your content management strategy to include social documents and files by complementing it with a rich enterprise social network provided by IBM Connections Cloud.
This document discusses Alliander's use of big data analytics to support its smart grid. It outlines some of the challenges Alliander faces with an aging grid and energy transition. Alliander is using big data analytics to gain better insight into grid behavior at lower voltage levels and make more information-based and customer-focused investments. Examples shown include asset health analytics to identify risky joints and a sensor system to detect potential cable defects in real-time. The document also discusses Alliander's analytics ecosystem and portfolio approach to innovating, validating, and implementing analytics, as well as the new skills that will be required for continued development.
Operationalizing Data Science: The Right Architecture and ToolsVMware Tanzu
In part one of this two-part series, you learned some of the common reasons enterprises struggle to turn insights into actions as well as a strategy for overcoming these challenges to successfully operationalize data science. In part two, it’s time to fill in the architectural and technological details of that strategy.
Pivotal Data Scientist Megha Agarwal will share the key ingredients to successfully put data science models in production and use them to drive actions in real-time. In this webinar, you will learn:
- Adopting extreme programming practices for data science
- Importance of working in a balanced team
- How to put and maintain machine learning models in production
- End-to-end pipeline design
Presenter: Megha Agarwal, Data Scientist
Blockchain is a revolutionary technology for some industries and applications, however it is commonly misunderstand and confused with the cryptocurrency Bitcoin. Blockchain is the underlying technology that makes Bitcoin and other cryptocurrencies possible, but it can be used for much more than cryptocurrencies alone. This presentation explains what Blockchain is, how it works and expounds on the uses of blockchain technology outside of cryptocurrencies in order to equip IT auditors with the knowledge they need to advise their companies on blockchain implementations. Blockchain has several very real uses cases, such as in logistics and financial payments clearing, however there is a lot of misleading or false information out there. The basics between what a public and private blockchain is, how the chain operates, what are miners, what security considerations exist, etc. will be discussed, along with an overview of how to audit this technology.
Understand what Blockchain is
Describe the differences between public and private blockchains
Understand where blockchain can be useful to companies, and where it is unnecessary
What security considerations exist
Be able to perform a basic Blockchain audit
Big data machine learning and predictive analytics have become an integral part of the retail industry. Enterpises across the world have now begun making informed decisions backed by data.
How advanced analytics is impacting the banking sectorMichael Haddad
The document discusses how advanced analytics is impacting the banking sector. It covers topics like regulatory changes forcing banks to invest in compliance; new digital technologies changing how customers interact with banks; and data analytics helping banks reduce risk, deliver personalized services, and retain skills. It also discusses Hitachi Data Systems' acquisition of Pentaho and how their combined platform can provide unified data integration and business analytics across structured, unstructured, and streaming data sources.
Seminar & Talkshow : How Big Data & IoT Create Smart Environment and Business...Tunjung Utomo
- Big data is a large collection of datasets that were once difficult to process due to their size and complexity but can now be managed through tools and expertise.
- Big data changes business by allowing companies to use data as an asset to create new products/services, gain better customer insights, improve efficiency, and enable near real-time analysis for decision making.
- Examples of big data use cases include using location data to analyze visitor patterns at an F1 race, using predictive analytics for better sales and pricing recommendations, conducting root cause analysis to reduce costs, enabling real-time equipment monitoring for efficiency, and monitoring business performance metrics.
The document discusses how IT operations are facing big data challenges due to the large volume, variety, and velocity of IT information. It argues that applying big data analytics to IT operations data can help address these challenges and extract value. Specifically, IT operations analytics tools can collect all types of IT data, provide insights into potential problems, and help IT operations teams detect issues early before they impact customers. These tools analyze patterns and relationships to spot problems faster and reduce false alerts.
Data has become a key focus for corporate leaders today. Chartered Global Management Accountant (CGMA) designation holders are well placed to help translate data into commercial insights and value.
Data Science: The Art of Foul Play by Serhiy ShelpukSoftServe
Serhiy Shelpuk, Lead Data Scientist, Competence Manager at SoftServe, Inc., delivered an insightful presentation on Data Science and SoftServe`s Data Science Group Knowledge Model at the 2013 IT Weekend Ukraine conference that took place on September 14, 2013, in Kyiv, Ukraine. Here`s his presentation.
With so much noise and buzzwords floating around regarding data analytics, it can be rather difficult to decipher between the signal (what is worthwhile) and what is only talk. Sometimes the rhetoric even starts within your organization, confounding the issue further. During Andrew’s session, he will provide attendees with the knowledge they need to tune out the bogus information while gleaning valuable insights for developing and deploying their audit analytics program. The presentation will conclude with tangible examples of a successful Manufacturing Audit Analytics program, and recommendations for how to get yours up and running. After attending, participants will be able to articulate how steps for setting up an analytics program within their departments, as well be armed with knowledge for educating senior leadership on the fundamental changes in technology that are occurring, and what is just marketing.
Five Pitfalls when Operationalizing Data Science and a Strategy for SuccessVMware Tanzu
Enterprise executives and IT teams alike know that data science is not optional, but struggle to benefit from it because the process takes too long and operationalizing models in applications can be hairy.
Join guest speaker, Forrester Research’s Mike Gualtieri and Pivotal’s Jeff Kelly and Dormain Drewitz for an interactive discussion about operationalizing data science in your business. In this webinar, the first of a two-part series, you will learn:
- The essential value of data science and the concept of perishable insights.
- Five common pitfalls of data science teams.
- How to dramatically increase the productivity of data scientists.
- The smooth hand-off steps required to operationalize data science models in enterprise applications.
Presenter : Guest Speakers Mike Gualtieri, Forrester, Dormain Drewitz and Jeff Kelly, Pivotal
[Ai in finance] AI in regulatory compliance, risk management, and auditingNatalino Busa
AI to Improve Regulatory Compliance, Governance & Auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests.
Machine Learning, Internet of Things and Unlocking Your Earning PotentialSmith Hanley Associates
The Analytical Recruiters at Smith Hanley Associates share with you the hottest trend in the data science job market for 2017, machine learning, the hottest trend for the future, IoT, and where your compensation should be in this competitive marketplace.
Big Data & Business Analytics: Understanding the MarketspaceBala Iyer
This document provides an overview of big data and business analytics. It discusses the growth of data and importance of analytics to businesses. The key topics covered include defining big data and data science, analyzing the analytics ecosystem and key players, examining use cases of analytics at companies like Target and Whirlpool, and providing recommendations for building an analytics capability and working with analytics vendors. The presentation emphasizes how data-driven decisions can improve business performance but also notes challenges to overcome like skills shortages and changing organizational culture.
Modak Analytics provides predictive modeling solutions to help companies analyze customer data and make reliable decisions. Predictive modeling involves [1] analyzing piled up customer data to derive useful insights, [2] designing a predictive model using various techniques like clustering, decision trees, regression, and scorecards, and [3] implementing the model to better understand customers and make profitable decisions. Predictive analysis allows companies to segment markets, rank products, predict customer responses, and reduce fraud. Modak Analytics' customized solutions leverage different modeling techniques to create ensemble models that extract the strengths of each technique.
The document discusses the need for "Smart Data" over "Big Data". It argues that while Big Data has potential, the technology is constantly evolving and data scientists with the needed skills are scarce and expensive. It advocates for providing business users with self-service analytics capabilities to answer over 90% of their questions quickly without IT assistance. Examples are provided of how self-service analytics helped Coca-Cola and JD Group gain insights from their data more efficiently.
NUS-ISS Learning Day 2018- Start with Data GovernanceNUS-ISS
The document discusses starting data governance from where an organization currently is. It highlights common questions around data that indicate a need for governance. The document then discusses using data to improve operations, customer experience, and more. It also outlines how data is changing different industries. The rest of the document discusses data governance in more detail, including defining it, ensuring data quality, and addressing compliance and security challenges. It provides examples of legislation and offers a framework for establishing an effective data governance program.
This document summarizes the services of a company that provides data analysis and machine learning solutions. They have an interdisciplinary team with over 15 years of experience in areas like machine learning, artificial intelligence, big data, and data engineering. Their expertise includes developing data models, analysis products, and systems to help companies with forecasting, decision making, and improving data operations efficiency. They can help clients across various industries like telecom, finance, retail, and more.
Credit Card Fraud Detection Using ML In DatabricksDatabricks
In the Credit Card Companies, illegitimate credit card usage is a serious problem which results in a need to accurately detect fraudulent transactions vs non-fraudulent transactions. All organizations can be hugely impacted by fraud and fraudulent activities, especially those in financial services. The threat can originate from internal or external, but the effects can be devastating – including loss of consumer confidence, incarceration for those involved, even up to downfall of a corporation. Despite regular fraud prevention measures, these are constantly being put to the test in an attempt to beat the system.
Fraud detection is a task of predicting whether a card has been used by the cardholder. One of the methods to recognize fraud card usage is to leverage Machine Learning (ML) models. In order to more dynamically detect fraudulent transactions, one can train ML models on a set of dataset including credit card transaction information as well as card and demographic information of the owner of the account. This will be our goal of the project while leveraging Databricks.
Decision Point AI, plan around what will happen instead of what has happened?Karl Smith
Presentation pack for Decision Point AI, Europe and USA. Focus, will the government approve a merger? and
will the combined M&A firms deliver good value?
IBM InterConnect 2015 - What is New in IBM Connections 2015Luis Benitez
This document provides a summary of new features and updates for IBM Connections and IBM Connections Mobile. It discusses enhancements delivered via cloud updates in 2014 and plans for 2015, including increased storage limits, file syncing for Mac, improved search and profiles, and additional mobile updates. The presentation emphasizes IBM's cloud-first development approach and focus on continuous delivery of updates. It highlights both current capabilities and planned future innovations.
IBM Connections Cloud & IBM Docs: Working securely and quickly with contentLuis Benitez
Are you struggling to manage your unstructured social content? Imagine combining the power of social and real-time document collaboration with ECM-grade native repositories and document management to help. This session will explore the benefits of online editors like IBM Docs that help to improve productivity and reduce the review and rework cycles associated with team-based business documents. Discover how to extend your content management strategy to include social documents and files by complementing it with a rich enterprise social network provided by IBM Connections Cloud.
What's New in IBM Connections Social Cloud - Q2 2016Luis Benitez
This deck summarizes the new features in IBM Connections Social Cloud that were delivered in the Q2 2016 release. For more information, check out http://ibmcloud.com/social
Follow me:
http://twitter.com/lbenitez
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What is new in IBM Connections 5.5 and IBM Docs 2.0Luis Benitez
This deck covers the highlights of the new capabilities introduced in the IBM Docs 2.0 and IBM Connections 5.5 released on December 2015.
To learn more, go to http://ibm.com/social
Follow me:
Twitter: http://twitter.com/lbenitez
LinkedIn: http://pr.linkedin.com/in/luisbenitez
My Blog: http://www.lbenitez.com
Manzanillo is a beach city in Mexico that is a 1 hour drive from Colima and 8 hours from Salamanca. It has over 6 beautiful beaches that are popular destinations during Holy Week for their traditional Carnival celebrations and fishing. The weather is warm and sunny. There are several exclusive hotels such as Caracoles, Zar, Barcelo, Hadas, City Express, and Marbella. Popular attractions include exclusive bars, famous restaurants, surfing beaches like Miramar, the Carnival, and beach tours. The author plans to visit beaches, restaurants, and go on an exclusive beach tour for 5 days to get to know more of the city's famous places.
This document discusses key performance indicators (KPIs) for food and beverage executive positions. It provides examples of KPIs, lists the key result areas and tasks, and describes the steps to create KPIs for this role. Mistakes to avoid when developing KPIs, such as having too many, are also outlined. The document recommends that KPIs should be clearly linked to strategy and empower employees. Various types of KPIs are defined.
The document spans an unspecified period of time, mentioning that 3 months had passed and then a week later news was received about Dane's deployment to Afghanistan. The document also references love and Christmas without providing additional context.
This document provides a corporate profile and details of services for HSS. It contains confidential information about HSS's service portfolio, methodology, accounting model, support packages and credentials. Any disclosure of the confidential information to outside parties could damage HSS as the ownership of the information remains with the company.
This document provides an introduction to computer software, including definitions of software and hardware. It describes different types of software such as system software, application software, open source software, and proprietary software. Examples are given for each type, including operating systems, compilers, word processors, spreadsheets, and databases. Key aspects of software like compilers, loaders, linkers, and interpreters are also explained.
Charleston360 Real Estate connects buyers and sellers in the Charleston, SC area and promotes the Lowcountry lifestyle, including its history, scenic views, parks, recreation, local art, music, farms, fishermen, and mild climate. Led by Principal Rachel Barkley, the real estate firm helps clients find their dream home in areas like downtown Charleston, waterfront properties, and suburbs.
Este documento presenta un juego educativo sobre las frutas con varios niveles. El objetivo es reconocer las distintas clases de frutas por su color, tamaño y textura, y aprender sobre los colores y tamaños de las frutas. El juego incluye instrucciones, un menú principal con tres niveles de dificultad creciente, y preguntas en cada nivel sobre las características de las frutas.
A computer is an electronic device that processes data to provide valuable information. It has a high processing speed, 100% accuracy, huge data storage capacity, reduces paperwork and manpower, and can operate continuously without tiring. However, it requires electricity and has no mind or emotions of its own. Proper cleaning and ventilation are also needed. Common computer components include the central processing unit, arithmetic logical unit, control unit, and uninterrupted power supply. Keyboards, mice, joysticks, touchpads, light pens, scanners, digital cameras, optical mark readers, and microphones are examples of input devices used to enter data into a computer.
This document provides tips for salespeople, including speaking in the future tense, validating problems, listening to customers, removing hurdles, and creating an easy "yes" for customers. It suggests getting referrals, being a thought leader, staying positive, and following up on connections through emails, meetings, and social media to sell more by solving customer problems.
IT and business leaders must increase their efforts to evolve from traditional BI tools, that focus on descriptive analysis (what happened), to advanced analytical technologies, that can answer questions like “why did it happen”, “what will happen” and “what should I do”.
"While the basic analytical technologies provide a general summary of the data, advanced analytical technologies deliver deeper knowledge of information data and granular data.” - Alexander Linden, Gartner Research Director
The reward of a smarter decision making process, based on Data Intelligence, is a powerful driver to improve overall business performance.
Wiseminer is the only and most efficient end-to-end Data Intelligence software to help you make smarter decisions and drive business results.
Contact us: info@wiseminer.com
Presented at SplunkLive! Paris 2018: Get More From Your Machine Data With Splunk AI
- Why AI & Machine Learning?
- What is Machine Learning?
- Splunk's Machine Learning Tour
- Use Cases & Customer Stories
This document discusses business intelligence (BI), including its definition as IT-enabled business decision making based on data analysis, why BI is important for making informed decisions and gaining competitive advantages, the advantages it provides organizations, key technologies that support BI like data warehousing and analytics tools, the common components of BI systems, how BI can be applied in management, stakeholders in BI systems, and an overview of data mining and the tools used.
SplunkLive! Munich 2018: Get More From Your Machine Data Splunk & AISplunk
Presented at SplunkLive! Munich 2018:
- Why AI & Machine Learning?
- What is Machine Learning?
- Splunk's Machine Learning Tour
- Use Cases & Customer Stories
The world we live in right now is getting more and more digital. All possible things we were reading in sci-fi books or watching in fantasy movies are becoming a reality. Internet of things, drones, e-world, mobility, applications, cloud, digital prototyping, e-voting, quantum computing, 3D printing like in Terminator movies and much more is a reality. On average auditory of this room can agree that it is ok to say that we live in the future. As what has happened to technology for personal use and business in last 25 years is impressive. And we can experience that. We are unique generation and live in unique times.
The digital world gives huge opportunities to any business entering it. There are soon close to 4 billion of potential customers out there in 2015 that are. Digital world introduces new products every day and technology creators are extremely working on to get new products to market as soon as possible.
But like in every book, movie, story, historical reality when there are good forces also there are bad forces. Cyber crime is growing and various things are happening everywhere. New technologies also introduce new risks and those risks are with different configuration. Countries attack countries and we call that a cyber wars, citizens are attacking countries and we call that hacktivism, professionals are attacking everyone for financial gains and we call that organized digital crime. And the methods are getting more and more sophisticated so in the end doesn’t matter how great are technologies of defense every day we have new articles of new indicents, data breeches, companies who have huge financial loses and damages of reputation, lost marketplace, stock market positions, customers, employees or even lives. I won’t touch each different method of attacks but I will simply try to share how we as a system integrator of complex cyber security protection technology solutions look at things and protect our customers.
The document summarizes services offered by a company for big data analytics. It describes services such as big data analytics, data integration, predictive analytics, data storage and management, and real-time analytics. It also outlines benefits like enabling data-driven decision making, identifying new opportunities, optimizing operations, enhancing customer experience, and mitigating risks. Technologies used include Hadoop, Apache Spark, Apache Kafka, Apache Hive, Python, R, and data visualization tools.
SplunkLive! Zurich 2018: Get More From Your Machine Data with Splunk & AISplunk
This presentation discusses how Splunk and machine learning can help organizations get more value from their machine data. It describes how machine learning can improve decision making, uncover hidden trends, alert on deviations, and forecast incidents. The presentation provides an overview of Splunk's machine learning capabilities, including search, packaged solutions, and the machine learning toolkit. It also showcases several customer use cases that have benefited from Splunk's machine learning offerings, such as network incident detection, security/fraud prevention, and optimizing operations.
This document discusses using AI and data modeling to improve insurance operations. It provides examples of using structured text, customer data, and other sources to build models for risk assessment, fraud detection, and other tasks. The document emphasizes the importance of data quality and having a holistic data strategy. It also stresses an iterative approach to AI development and increasing skills. An example use case describes using natural language processing models to assist underwriters by providing relevant risk expertise and intelligence from various data sources.
Practical session reviewing the next evolution of robotic process automation (RPA) and the expanded value it can deliver supported by artificial intelligence (AI)
Review business interest in advancing RPA with AI
Explore the complementary strengths and weaknesses of RPA & AI
Present the future of RPA in the form of Intelligent Automation powered by AI
Discuss how your business can implement such capabilities
Part 5 of a 9 Part Research Series named "What matters in AI" published on https://www.andremuscat.com
Delivering business value from operational insights at ING BankSplunk
The document discusses how ING Bank uses Splunk to extract business value from operational data. It describes several IT use cases like customer pre-scoring, portfolio management, fraud detection and reducing downtime. It also discusses expanding the use of Splunk beyond IT to business cases like customer journey mapping. The document shares details of ING Bank's Splunk implementation, how it migrated systems to Splunk, and future plans to integrate Hadoop and machine learning.
Although the recent Equifax breach that reportedly compromised 143 million accounts has sent consumers scrambling to protect their assets, financial institutions and corporations are likely to feel the impending effects of this attack as well.
It is predicted there will be a surge in social engineering and BEC scams, as the hackers now have a wealth of information needed to impersonate individuals and corporate entities in a variety of contexts. However, the right strategic approach and technology solutions can effectively mitigate the fraud risk.
In this webinar, guest speaker Andras Cser, VP, Principal Analyst in Security & Risk from Forrester Research, will provide an expert industry perspective and discuss what financial institutions and corporations can do to protect themselves. You will gain insight into how organizations are raising their defenses, understand the best practices to minimize fraud loss, and learn how advanced analytics solutions can help minimize the risk.
Big data and analytics ibm digital game plan short v2 nonconfFriedel Jonker
This document provides an agenda and overview for a presentation on activating the individual enterprise through customer centricity and big data and analytics strategies. The presentation discusses developing a 360 degree view of customers, moving from traditional analytics 1.0 to more advanced analytics 3.0, and focusing on cognitive solutions from IBM Watson such as Watson Explorer. It emphasizes building a customer centric model and activating the individual enterprise to better understand and serve customers.
Big data and marketing is becoming an important tool for companies. The document discusses how big data can be used for personalization, listening to customers, and responding to better serve their needs. It outlines the key steps in the process from data collection and analysis to insights and actions. Various big data tools and techniques are mentioned to understand customer behavior and trends in order to tailor marketing and customer experiences. The challenges of translating data into insights and actions are also addressed.
#MarketingShake - Edward Chenard - Descubrí el poder del Big Data para Transf...amdia
Big data and marketing is becoming an important tool for companies. The document discusses how big data can be used for personalization, listening to customers, and responding to better serve their needs. It outlines the key steps in the process from data collection and analysis to insights and actions. Various big data tools and techniques are mentioned to understand customer behavior and trends in order to tailor marketing and customer experiences. The importance of data visualization to tell the story of patterns and create useful insights for businesses is also highlighted.
The document discusses how modern software architectures can help tame big data. It introduces the speakers and provides an overview of WidasConcepts. The agenda includes a discussion of how big data can help businesses, an example of big data applied in the CarbookPlus platform, and new software architectures for big data. Real-time systems and architectures like lambda architecture are presented as ways to process big data at high velocity and volume. The conclusion emphasizes that big data improves business efficiency but requires tailored implementations and new skills.
Data Science - Part I - Sustaining Predictive Analytics CapabilitiesDerek Kane
This is the first lecture in a series of data analytics topics and geared to individuals and business professionals who have no understand of building modern analytics approaches. This lecture provides an overview of the models and techniques we will address throughout the lecture series, we will discuss Business Intelligence topics, predictive analytics, and big data technologies. Finally, we will walk through a simple yet effective example which showcases the potential of predictive analytics in a business context.
1) While data has become more abundant, organizations must ensure they extract useful information from data to drive better decisions.
2) The rise of instrumented, interconnected and intelligent systems allows organizations to gain real-time insights from vast amounts of structured and unstructured data.
3) Leveraging predictive analytics and content analytics can help organizations move from reactive to predictive decision-making to optimize performance.
FUTURE OF DATA SCIENCE IN INDIA
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
Similar to IBM InterConnect 2013: Big Data and Analytics Presented by Mike Rhodin (20)
IBM InterConnect 2013 Smarter Commerce Keynote: SingTelIBM Events
SingTel is a leading telecommunications company in Asia and Africa with 477 million mobile customers. In the quarter ending June 30, 2013, SingTel had operating revenue of $4.3 billion, EBITDA of $1.3 billion, underlying net profit of $897 million, and free cash flow of $893 million. SingTel has leading market positions for mobile in markets like India, Thailand, the Philippines, Indonesia, and Singapore. It also provides business solutions to enterprises. Marketing and IT roles have become more complex due to factors like increased data sources and types of customer connections. Analytical marketing requires balancing data, infrastructure, people and processes to deliver the right offers to customers.
This document discusses challenges facing Chief Information Security Officers (CISOs) and how IBM security solutions address those challenges through intelligence, integration, and expertise. It summarizes IBM's security framework which uses analytics, visibility, and integration across network protection, fraud protection, endpoint management, and other capabilities to provide advanced threat protection, risk management, compliance, and resource optimization. The document also provides examples of how IBM security solutions have helped clients enhance user and asset security, transaction security, and gain security intelligence.
IBM InterConnect 2013 Mobile Keynote: Marie WieckIBM Events
The document discusses the growing importance and impact of mobile devices. It notes that mobile adoption continues to explode, with mobile changing interactions across industries like banking, travel, government, and more. It also discusses how mobile is changing how individuals get things done. The document then summarizes some business and IT challenges that these trends bring, like app integration, infrastructure complexity, privacy/security, and the need for new processes and designs. It outlines findings from a study that show how "mobile leaders" are addressing these challenges differently than others. Finally, it discusses how IBM can help organizations build a mobile enterprise agenda with offerings like MobileFirst.
IBM InterConnect 2013 Mobile Keynote: Kristen LauriaIBM Events
The document discusses how organizations can take advantage of mobile technologies and the mobile phenomena. It provides examples of how IBM helped different organizations integrate mobile solutions. Rohde & Schwarz reduced mobile development costs by 60% using the IBM Worklight platform. Kochi Medical School Hospital improved care quality and reduced costs using IBM's Mobile Enterprise Services. NS Shopping selected IBM's technologies to transform its customer experience and gain insights about consumer preferences from mobile apps.
IBM InterConnect 2013 Expert Integrated Systems Keynote: Sotiropoulos & WieckIBM Events
This document discusses how IBM's PureSystems family of expert integrated systems can simplify and accelerate cloud deployments and big data analytics. PureSystems appliances integrate hardware and software to automate tasks and reduce the time and effort spent on IT projects. They allow clients to improve IT efficiency by simplifying the lifecycle, accelerate applications and analytics, and simplify cloud platforms. The document provides examples of clients cutting time to provision environments by 30% and reducing management time across the lifecycle by up to 75% when using PureSystems.
IBM InterConnect 2013 Expert Integrated Systems Keynote: SpindoIBM Events
PT. Steel Pipe Industry of Indonesia Tbk (SPINDO) is the largest steel pipe producer in Indonesia and ASEAN, established in 1971. It was using aging SAP servers since 2005 that caused availability and performance issues. To address this, in December 2012 it implemented an IBM PureFlex system with Power servers that provided 7 times faster processing, 3.7 times faster backups, 36% reduced database size, 40% lower energy usage, and over 50% less space. The new system has capacity for 3 years of usage and is expandable for over 7 years, with a 7 year maintenance agreement.
This document contains a summary of a presentation on adopting DevOps practices for faster and more efficient software delivery. It discusses how software delivery is critical but challenging for most organizations. DevOps takes a holistic approach to optimize the entire delivery process through practices like continuous integration, deployment, testing, and monitoring. The document outlines different adoption paths organizations can take, such as starting with continuous planning and measurement or collaborative development. It emphasizes starting small on high-value projects and measuring outcomes to steer further improvements. Adopting DevOps requires both technical and cultural changes but can significantly improve time to market, quality, and competitiveness.
InterConnect 2013 Cloud General Session: Douglas WhiteIBM Events
The document discusses a peer-to-peer conversation between Douglas White, CTO and Senior Vice President of Cloud Infrastructure Services at IBM, and other attendees. Douglas White's role at IBM involves overseeing cloud infrastructure and services. The conversation took place at an IBM conference in 2013.
IBM InterConnect 2013 Cloud General Session: Tom RosamiliaIBM Events
Presentation by Tom Rosamilia, Senior VP, Systems & Technology Group and IBM Integrated Supply Chain, at IBM InterConnect 2013
http://ibm.com/interconnect
IBM InterConnect 2013 Cloud General Session: George KaridisIBM Events
SoftLayer is a global hosting provider that offers public, private, and hybrid cloud solutions through its standardized modular infrastructure platform. It has data centers in 13 locations around the world and a robust API that allows customers to automate provisioning and management of servers, storage, networking and other resources on its unified platform. SoftLayer serves over 21,000 customers across industries with a focus on providing flexible, on-demand computing infrastructure and services.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
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.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
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.
2. #IBMINTERCONNECT
Analyze
Data
(Integrate & Interconnect)
Apply
Insight
(Intelligent Outcomes)
Capture
Data
(Instrument)
Identify
Patterns
(Unlock Insight)
All Information
Transaction data
Application data
Machine data
Social data
Enterprise content
All Perspectives
Past (historical, aggregated)
Present (real-time)
Future (predictive, prescriptive)
Learning (cognitive)
All People
All departments
Experts and non-experts
Executives and employees
Partners and customers
All Decisions
Strategic and tactical
Major and minor
Routine and exceptions
Manual and automated
Key Tenets of Big Data & Analytics
Analyze
Data
(Integrate & Interconnect)
Apply
Insight
(Intelligent Outcomes)
Capture
Data
(Instrument)
Identify
Patterns
(Unlock Insight)
3. #IBMINTERCONNECT
Adding Value at Every Point of Impact
….Each Decision, Interaction & Process
Big Data
& Analytics
Systems of Record
Infrastructure
Security Intelligence
Enterprise Applications
Systems of Engagement
Mobile Commerce
Call Center
Social Business
Infuse, Extend & Integrate
4. #IBMINTERCONNECT
Infuse Big Data & Analytics Everywhere
…what we have learned
Attract, grow,
retain customers
Create new
business models
Transform financial
processes
Manage
risk
Optimize operations
and reduce fraud
Improve IT
economics
Big Data
& Analytics
5. #IBMINTERCONNECT
Information Governance, Security and Business Continuity
All Data
Sources
New Era Solutions
Smarter
Analytics
Social
Business
Smarter
Commerce
Smarter
Cities
Watson
Solutions
Information
Ingestion
and
Integration Data
Landing
Archive
Real-time Analytics
Data
Exploration
Enterprise
Warehouse
Data Marts
New Architecture is Required
6. #IBMINTERCONNECT
How can everyone
be more right …
… more often?
Descriptive
Prescriptive
Predictive
Cognitive
What has happened?
What could happen?
How can we achieve the best outcome?
Tell me the best course of action?
Business
Value
Big Data
and
Analytics
IBM’s Analytics Enables Better Decisions
9. #IBMINTERCONNECT
How to Start with IBM
Imagine it.
Build a culture that
infuses analytics
everywhere.
Realize it.
Invest in a
big data & analytics
platform.
Trust it.
Be proactive about
privacy, security
and governance.
Big Data & Analytics
IBM’s end-to-end Big Data & Analytics Portfolio
Take an outcome-driven
approach to outperform
Start small, and
scale at your pace
Confidently manage
data at scale - efficiently