Info Architecture 2020 (c) 2011, JR McGrawJ.R. McGraw
This document provides an overview of enterprise information management and related technologies. It outlines key areas such as data integration, business intelligence, analytics, enterprise performance management, metadata management, identity and access management, transaction processing, content management, information services, master data management, and infrastructure. The document also discusses emerging technologies like real-time analytics, social data, mobile, cloud, big data, and new approaches for data storage, caching, and services.
This document discusses graphs and graph databases. It provides examples of how organizations like eBay, NASA, and pharmaceutical companies use graph databases to connect disparate data sources and gain insights. Graph databases are becoming increasingly popular due to growth in connected data and can be used for applications like fraud prevention, product recommendations, and knowledge discovery. The document promotes Neo4j as the leading graph database and mentions its adoption by many large enterprises and upcoming cloud services.
MicroStrategy Indianapolis - Speed to ValueAdam Drought
Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Data Innovation Summit 2017 - Eric Rodriguez
Sharing the early lessons of building lex.be in a challenging LegalTech ecosystem at DISummit
Visit https://lex.be
Data Marketplace: Speed to Value with MicroStrategy & Flexible ArchitecturesSteve Grover, CBIP,CSM
Description: Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Info Architecture 2020 (c) 2011, JR McGrawJ.R. McGraw
This document provides an overview of enterprise information management and related technologies. It outlines key areas such as data integration, business intelligence, analytics, enterprise performance management, metadata management, identity and access management, transaction processing, content management, information services, master data management, and infrastructure. The document also discusses emerging technologies like real-time analytics, social data, mobile, cloud, big data, and new approaches for data storage, caching, and services.
This document discusses graphs and graph databases. It provides examples of how organizations like eBay, NASA, and pharmaceutical companies use graph databases to connect disparate data sources and gain insights. Graph databases are becoming increasingly popular due to growth in connected data and can be used for applications like fraud prevention, product recommendations, and knowledge discovery. The document promotes Neo4j as the leading graph database and mentions its adoption by many large enterprises and upcoming cloud services.
MicroStrategy Indianapolis - Speed to ValueAdam Drought
Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Data Innovation Summit 2017 - Eric Rodriguez
Sharing the early lessons of building lex.be in a challenging LegalTech ecosystem at DISummit
Visit https://lex.be
Data Marketplace: Speed to Value with MicroStrategy & Flexible ArchitecturesSteve Grover, CBIP,CSM
Description: Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
The document is a draft data science capability framework created by Craig C. Milroy, Chief Data Architect. The framework outlines various data science capabilities across several areas including lab management, languages, applications, visualization, data management, data processing, and analytics. Specific techniques mentioned include R, Python, Scala, Java, notebooks, dashboards, data services, data preparation, machine learning, deep learning, and natural language processing among others.
This document discusses strategies for effective data monetization. It outlines challenges in data monetization like the increasing volume of data and the need for AI. It presents a data monetization maturity model and describes the top 5 best practices for successful data monetization as: getting the foundation right by infusing AI/data science; focusing on people like data engineers and scientists; constructing a robust business model; and ensuring trust and ethics. The document recommends using case generation and prioritization and provides industry examples. It promotes IBM Cloud Private for Data as an integrated analytics platform to overcome challenges and realize the benefits of data monetization.
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
This document provides information about ERGO Comps, LLC and the data-as-a-service industry. It discusses how the market for outsourced data management has grown beyond verification to include real-time alerts and analytics. Common pricing models include recurring retainers plus transactions, pay-for-performance, and subscription retainers. The document also lists several acquisition deals that have taken place in the data-as-a-service industry from 2017 to 2018.
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
Chief Data Officer: Customer Analytics InnovationCraig Milroy
The document discusses a chief data officer's roadmap for using customer analytics and data to understand the "customer network". It mentions using big data, business intelligence, data architecture, data governance, data integration, data quality, data strategy, data visualization and other techniques to gain insights into customers, customer relationships, and customer behavior to improve customer centricity and relationships. The CDO's roadmap would help organizations transform their business using next generation data platforms and an open, customer-focused approach.
Big Data LDN 2018: INTELLIGENCE EVERYWHERE – POWER TO THE PEOPLEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics Theatre
Time: 11:50 - 12:20
Speaker: Matt Pepper
Organisation: MIcroStretegy
About: In this session, Matt Pepper will demonstrate how MicroStrategy enables an Enterprise to provide:
• Governed Data Discovery at scale
• Freedom for departments to build applications whilst remaining compliant
• The capability to link disparate data into a cohesive platform
• The right information to the right person, in the right format, at the right time
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
The document discusses how combining data across organizations within a sector can create "Sector Advantage". It proposes that a neutral third party like Digital Catapult could host combined data through its Data Catalyser initiative, allowing smaller companies to explore the data and extract value, while maintaining security and competitive advantages for data providers. The Data Catalyser uses technical and legal frameworks to allow innovative data exploration across organizations in a controlled way to enable new opportunities for sector advantage.
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCSTata Consultancy Services
In this opening key note, Ananth shared insights on technologies and trends that are changing the way we view atoms, people, materials, things and data, and how we can prepare ourselves to exploit these new opportunities.
How to identify the Return on Investment of Big Data / CIO (Infographic)suparupaa
The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information
Nathalie Morris, CEO of Qrious, discusses the importance of data foundations for artificial intelligence (AI) in marketing. She explains that for AI to succeed, it needs high-quality data that is complete, centrally located, and collected with clear consent. It also needs varied data that reflects human diversity. Only then can AI deliver real value for customers, rather than just using AI for its own sake. The key is for companies to improve their data foundations in preparation for increasingly using AI.
John Avery discusses opportunities in big data and graph analytics for financial services. Big data involves storing, processing, and analyzing large amounts of structured and unstructured data across distributed systems. It can help financial firms reduce the effort to analyze more data and enable new types of analyses. Graph analytics uses relationships in data to power applications in areas like risk management, trading, and regulatory compliance. Firms should explore applying these technologies to problems like counterparty risk analysis, market surveillance, and systemic risk oversight.
Using Big Data in Finance by Jonah EnglerJonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
As the year comes to an end, it is time to look ahead to see what the next year will bring us. Now for the 7th year in a row, I offer you my two cents on the most important technology trends for 2019 to help you, and your business, prepare for the next year. As we approach the end of the second decade of this new millennium, technology is evolving faster than ever before. These exponential times will have a profound effect on what it means to be human and how we manage organisations and societies. 2019 will be a year in which technology will improve its grip on society and where competition among countries over AI and quantum supremacy will increase. That is why I would like to call 2019 the Year of Truth. Let’s have a look at the seven technology trends that will dominate 2019.
致詞歡迎:Big Data 無所不在,Data Technology 無 C 不歡Etu Solution
This document contains the opening remarks from Lin Longfen, the general manager of Jingcheng Group. It discusses how Gartner dropped "Big Data" from its hype cycle of emerging technologies in 2015 because it is now considered a mainstream part of many industries. Big data is still essential for major trends like the Internet of Things, Industry 4.0, and smart everything. The document emphasizes that understanding customers ("C") is key to a company's ("B") competitive advantage in the digital economy, and that leveraging industry data is a common development strategy across Jingcheng Group's business units.
The document summarizes a meetup about data visualization hosted by Platfora Company. It discusses Platfora software that transforms raw data in Hadoop into interactive business intelligence without needing ETL or a data warehouse. It provides an overview of Platfora Company, which was founded in 2011 and has raised $27.2M from investors. The meetup featured a demonstration of Platfora's data visualization and analysis capabilities.
The future of FinTech product using pervasive Machine Learning automation - A...Shift Conference
Machine learning and automated decisions are reshaping businesses by automating processes, optimizing customer interactions, and efficiently measuring risk. The future of fintech relies on pervasive use of machine learning, but scaling ML applications is challenging due to the scarcity of data scientists and the complex ML process. Automated machine learning can address these issues by simplifying and accelerating the ML lifecycle, enabling a wider range of users to develop and deploy models at scale across all business functions.
The document is a draft data science capability framework created by Craig C. Milroy, Chief Data Architect. The framework outlines various data science capabilities across several areas including lab management, languages, applications, visualization, data management, data processing, and analytics. Specific techniques mentioned include R, Python, Scala, Java, notebooks, dashboards, data services, data preparation, machine learning, deep learning, and natural language processing among others.
This document discusses strategies for effective data monetization. It outlines challenges in data monetization like the increasing volume of data and the need for AI. It presents a data monetization maturity model and describes the top 5 best practices for successful data monetization as: getting the foundation right by infusing AI/data science; focusing on people like data engineers and scientists; constructing a robust business model; and ensuring trust and ethics. The document recommends using case generation and prioritization and provides industry examples. It promotes IBM Cloud Private for Data as an integrated analytics platform to overcome challenges and realize the benefits of data monetization.
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
This document provides information about ERGO Comps, LLC and the data-as-a-service industry. It discusses how the market for outsourced data management has grown beyond verification to include real-time alerts and analytics. Common pricing models include recurring retainers plus transactions, pay-for-performance, and subscription retainers. The document also lists several acquisition deals that have taken place in the data-as-a-service industry from 2017 to 2018.
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
Chief Data Officer: Customer Analytics InnovationCraig Milroy
The document discusses a chief data officer's roadmap for using customer analytics and data to understand the "customer network". It mentions using big data, business intelligence, data architecture, data governance, data integration, data quality, data strategy, data visualization and other techniques to gain insights into customers, customer relationships, and customer behavior to improve customer centricity and relationships. The CDO's roadmap would help organizations transform their business using next generation data platforms and an open, customer-focused approach.
Big Data LDN 2018: INTELLIGENCE EVERYWHERE – POWER TO THE PEOPLEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics Theatre
Time: 11:50 - 12:20
Speaker: Matt Pepper
Organisation: MIcroStretegy
About: In this session, Matt Pepper will demonstrate how MicroStrategy enables an Enterprise to provide:
• Governed Data Discovery at scale
• Freedom for departments to build applications whilst remaining compliant
• The capability to link disparate data into a cohesive platform
• The right information to the right person, in the right format, at the right time
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
The document discusses how combining data across organizations within a sector can create "Sector Advantage". It proposes that a neutral third party like Digital Catapult could host combined data through its Data Catalyser initiative, allowing smaller companies to explore the data and extract value, while maintaining security and competitive advantages for data providers. The Data Catalyser uses technical and legal frameworks to allow innovative data exploration across organizations in a controlled way to enable new opportunities for sector advantage.
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCSTata Consultancy Services
In this opening key note, Ananth shared insights on technologies and trends that are changing the way we view atoms, people, materials, things and data, and how we can prepare ourselves to exploit these new opportunities.
How to identify the Return on Investment of Big Data / CIO (Infographic)suparupaa
The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information
Nathalie Morris, CEO of Qrious, discusses the importance of data foundations for artificial intelligence (AI) in marketing. She explains that for AI to succeed, it needs high-quality data that is complete, centrally located, and collected with clear consent. It also needs varied data that reflects human diversity. Only then can AI deliver real value for customers, rather than just using AI for its own sake. The key is for companies to improve their data foundations in preparation for increasingly using AI.
John Avery discusses opportunities in big data and graph analytics for financial services. Big data involves storing, processing, and analyzing large amounts of structured and unstructured data across distributed systems. It can help financial firms reduce the effort to analyze more data and enable new types of analyses. Graph analytics uses relationships in data to power applications in areas like risk management, trading, and regulatory compliance. Firms should explore applying these technologies to problems like counterparty risk analysis, market surveillance, and systemic risk oversight.
Using Big Data in Finance by Jonah EnglerJonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
As the year comes to an end, it is time to look ahead to see what the next year will bring us. Now for the 7th year in a row, I offer you my two cents on the most important technology trends for 2019 to help you, and your business, prepare for the next year. As we approach the end of the second decade of this new millennium, technology is evolving faster than ever before. These exponential times will have a profound effect on what it means to be human and how we manage organisations and societies. 2019 will be a year in which technology will improve its grip on society and where competition among countries over AI and quantum supremacy will increase. That is why I would like to call 2019 the Year of Truth. Let’s have a look at the seven technology trends that will dominate 2019.
致詞歡迎:Big Data 無所不在,Data Technology 無 C 不歡Etu Solution
This document contains the opening remarks from Lin Longfen, the general manager of Jingcheng Group. It discusses how Gartner dropped "Big Data" from its hype cycle of emerging technologies in 2015 because it is now considered a mainstream part of many industries. Big data is still essential for major trends like the Internet of Things, Industry 4.0, and smart everything. The document emphasizes that understanding customers ("C") is key to a company's ("B") competitive advantage in the digital economy, and that leveraging industry data is a common development strategy across Jingcheng Group's business units.
The document summarizes a meetup about data visualization hosted by Platfora Company. It discusses Platfora software that transforms raw data in Hadoop into interactive business intelligence without needing ETL or a data warehouse. It provides an overview of Platfora Company, which was founded in 2011 and has raised $27.2M from investors. The meetup featured a demonstration of Platfora's data visualization and analysis capabilities.
The future of FinTech product using pervasive Machine Learning automation - A...Shift Conference
Machine learning and automated decisions are reshaping businesses by automating processes, optimizing customer interactions, and efficiently measuring risk. The future of fintech relies on pervasive use of machine learning, but scaling ML applications is challenging due to the scarcity of data scientists and the complex ML process. Automated machine learning can address these issues by simplifying and accelerating the ML lifecycle, enabling a wider range of users to develop and deploy models at scale across all business functions.
Meeting Business Data Needs The AI and ML Frontier in Data Capture ServicesAndrew Leo
In today's data-driven landscape, businesses are faced with the challenge of efficiently managing vast volumes of data. Traditional methods often fall short, but there's a solution: AI and ML-powered data capture services.
Our latest presentation dives into how these technologies are revolutionizing data capture, enhancing accuracy, efficiency, and scalability across industries. From automated data extraction to real-time analysis, the possibilities are endless!
Join the conversation and learn how your business can benefit from intelligent data capture solutions.
Check out the full presentation here:
Ready to elevate your data capture game? Contact us to explore tailored solutions for your business.
Enabling digital business with governed data lakeKaran Sachdeva
Digital business is enabled by Artificial intelligence, Machine learning, and data science. Artificial intelligence and machine learning are dependent on right Information architecture and data foundation. Governed data lake infused with governance and data science platform gives you the power to take the organization in the digital transformation and AI journey.
Accelerate Your Move to the Cloud with Data Catalogs and GovernanceDATAVERSITY
As more data is migrating to the cloud, whether to increase efficiencies or take advantage of new capabilities like AI and machine learning tools, organizations are challenged on how to do so in a consumable, trusted fashion. Join us for this webcast and hear how enterprises are using data catalogs to unify approaches across their cloud and on-premises worlds, and prioritize which data assets should be moved to cloud, resulting in a more consumable and trusted data lake and ecosystem.
Graph technology has truly burst onto the scene with diverse new products and services, proving that graph is relevant and that not all graph use cases are equal. Previously relegated to niche implementations and science projects, graph now finds itself deployed as the foundational technology for enterprise analytics solutions and enterprise Data Fabric strategies. It is no surprise that many are calling 2018 “The Year of the Graph”.
The document discusses the role of data scientists and trends in data science. It describes how data scientists identify business needs, prepare and analyze data, interpret results, and communicate findings. However, emerging tools are automating some of these tasks using techniques like machine learning and natural language processing. This could change the role of data scientists and enable more self-service data analysis. The document also lists some vendors developing tools to support self-service data science through augmented intelligence.
Better Business From Exploring Ideas - AWS Summit Sydney 2018Amazon Web Services
Better Business from Exploring Ideas - Modern Data Architectures on AWS
In this session you will learn how organisations are able to drive better business outcomes from products and deliver more personalised and real-time experiences to customers. We will walk through a common customer journey that shows how to quickly test ideas and get insights, built on top of data lakes, data pipelines, and sandboxes using the same platform advantages of Modern Data Architectures on AWS as some of our most prominent customers. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning.
Craig Stires, APAC Head of Analytics, Big Data, and AI, Amazon Web Services
Designing the Next Generation Data LakeRobert Chong
This document contains a presentation by George Trujillo on designing the next generation data lake. It discusses how analytic platforms need to change to keep up with business demands. New technologies like cloud, object storage, and self-driving databases are allowing for more flexible and scalable data architectures. This is shifting analytics platforms from tightly coupled storage and compute to independent, elastic models. These changes will impact how organizations build projects, careers, and skills in the future by focusing more on innovation and delivering results faster.
A modern day data management platform driven by the evolved thought process and focus,
- From Data to Metadata engineering and Ontologies
- From Data Swamps to Data Products
- From Data for AI to AI for Data
- From Tech Debts to Data Monetization
Réinventez le Data Management avec la Data Virtualization de DenodoDenodo
Regardez la version complète du webinar à la demande ici: https://goo.gl/ZxRqmX
"D'ici à 2020, 50% des entreprises mettront en œuvre une forme de virtualisation des données comme une option pour l'intégration de données", selon le cabinet d’analystes Gartner. La virtualisation des données ou data virtualization est devenue une force motrice pour les entreprises pour la mise en œuvre d’une architecture de données d'entreprise agile, temps réel et flexible.
Au sommaire de ce webinar:
Denodo et son positionnement sur le marché de la Data Virtualization
Les principales fonctionnalités
Démo/vidéo
Les principaux cas d’usage. Présentation d'un cas client : comment Intel a repensé l’architecture de ses données avec la Data Virtualization
Les ressources
Questions/Réponses
The document discusses how data has become a central business asset and strategic advantage. It notes that the growth of data from sources like the Internet of Things means that variety, not just volume or velocity, will be important. New business processes will revolve around data, which will become more valuable over the next decade. It also provides examples of how companies like eBay and Groupon have used data for competitive advantages like identifying top sellers.
Better Business from Exploring Ideas - Modern Data Architectures on AWSAmazon Web Services
In this session you will learn how organisations are able to drive better business outcomes from products and deliver more personalised and real-time experiences to customers. We will walk through a common customer journey that shows how to quickly test ideas and get insights, built on top of data lakes, data pipelines, and sandboxes using the same platform advantages of Modern Data Architectures on AWS as some of our most prominent customers. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning.
Accelerate Your Move to the Cloud with Data Catalogs and GovernanceDATAVERSITY
As more data is migrating to the cloud, whether to increase efficiencies or take advantage of new capabilities like AI and machine learning tools, organizations are challenged on how to do so in a consumable, trusted fashion. Join us for this webcast and hear how enterprises are using data catalogs to unify approaches across their cloud and on-premises worlds, and prioritize which data assets should be moved to cloud, resulting in a more consumable and trusted data lake and ecosystem.
This presentation was made on June 16, 2020.
A recording of the presentation can be viewed here: https://youtu.be/khjW1t0gtSA
AI is unlocking new potential for every enterprise. Organizations are using AI and machine learning technology to inform business decisions, predict potential issues, and provide more efficient, customized customer experiences. The results can enable a competitive edge for the business.
H2O.ai is a visionary leader in AI and machine learning and is on a mission to democratize AI for everyone. We believe that every company can become an AI company, not just the AI Superpowers. We are empowering companies with our leading AI and Machine Learning platforms, our expertise, experience and training to embark on their own AI journey to become AI companies themselves. All companies in all industries can participate in this AI Transformation.
Tune into this virtual meetup to learn how companies are transforming their business with the power of AI and where to start.
About Parul Pandey:
Parul is a Data Science Evangelist here at H2O.ai. She combines Data Science , evangelism and community in her work. Her emphasis is to spread the information about H2O and Driverless AI to as many people as possible, She is also an active writer and has contributed towards various national and international publications.
Big Data Security Analytics (BDSA) with Randy FranklinSridhar Karnam
The document discusses big data security analytics and how HP addresses related challenges. It notes that big data analytics for security requires real-time analysis of high-volume, diverse data streams. While many big data solutions focus on batch analytics, security demands real-time correlation and detection of threats. The document outlines how HP's ArcSight platform collects, correlates, and analyzes security data from many sources in real-time. It also explains how HP uses Hadoop for long-term storage and analytics, and Autonomy for semantic analysis of unstructured data to enable predictive security.
Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - ...Amazon Web Services
You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
How to Quickly Get Insights from IoT Data on AWS (ANT337-S) - AWS re:Invent 2018Amazon Web Services
The Internet of Things (IoT) is creating massive amounts of data, but users can’t easily access that data and quickly make decisions from it. Data projects are too often funded and delivered without enough consideration for how users will access and consume that data. Domo connects the people, data, and systems to give users the data they need to do their jobs, anytime and from anywhere. In this session, learn how LifeConEx, DHL’s temperature management specialist, uses Domo to get insights from their IoT data to its users, and see the impressive results they have achieved. This session is brought to you by AWS partner, Domo.
[Webinar Slides] Data Explosion in Your Organization? Harness It with a Compr...AIIM International
Check out these webinar slides to learn the latest ways Office 365 is providing the tools to develop and implement a modern records management strategy to take charge of the data explosion.
Want to follow along with the webinar replay? Download it here for FREE: https://info.aiim.org/data-explosion-in-your-organization-harness-it-with-a-comprehensive-records-management-strategy
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.