Join Jeff Kelly, Pivotal’s Big Data Strategist and Chris Roche, Aridhia’s CEO, to learn how Big Data and data science are being applied to clinical research. Learn…
• Why research-oriented healthcare delivery organizations and academic medical centers need an ACRIS
• How improving collaboration and productivity accelerates the discovery of insights and increases competitiveness
• Why robust data security is critical to modernizing engagement between academia, industry and healthcare
• How to reduce research costs while improving commercialization opportunities
• Why enabling transparent analysis and reproducibility of research are key to scientific progress
• Best practices to get started on your digital transformation and Big Data journey
Data technology experts from Pivotal give the latest perspective on how big data analytics and applications are transforming organizations across industries.
This event provides an opportunity to learn about new developments in the rapidly-changing world of big data and understand best practices in creating Internet of Things (IoT) applications.
Learn more about the Pivotal Big Data Roadshow: http://pivotal.io/big-data/data-roadshow
Driving Real Insights Through Data ScienceVMware Tanzu
Major changes in industries have been brought about by the emergence of data-driven discoveries and applications. Many organizations are bringing together their data, and looking to drive change. But the ability to generate new insights in real time from a massive sets of data is still far from commonplace.
At this event, data technology experts and data scientists from Pivotal provided the latest business perspective on how data science and engineering can be used to accelerate the generation of new insights.
For information about upcoming Pivotal events, please visit: http://pivotal.io/news-events/#events
Customer Spotlight: How WellCare Accelerated Big Data Delivery to Improve Ana...VMware Tanzu
WellCare uses Attunity Replicate to offload data quickly and easily from its SQL Server and Oracle systems into Pivotal Greenplum Database. With the help of Attunity and Pivotal, WellCare has successfully enabled real-time reporting and analytics to gain a competitive edge.
Additional information:
https://pivotal.io/big-data/webinar/healthcare-success-story-wellcare
Webinar recording:
https://youtu.be/ZYiwRUxlY2s
How Data Science is Preventing College Dropouts and Advancing Student SuccessVMware Tanzu
Educational institutions have a wealth of information, which can be brought together in an institutional data lake to predict and influence student behavior. In this webinar, one of Pivotal's principal data scientists discusses a recent collaborative project with a top university, in which many data sources were used to build a 360-degree profile of student activity on campus and help predict student success. Learn about the data science pipelines that Pivotal developed and how they are now being used to predict student metrics (such as GPA, course grade and time to graduate), and even as intervention tools to help prevent students from dropping out.
Webinar recording: https://youtu.be/SxXZBmAs1aE
Pivotal Digital Transformation Forum: Becoming a Data Driven EnterpriseVMware Tanzu
Next Steps in Your Digital Transformation
This session brings together all the lessons learnt throughout the day and shares with you practical advice on how to get started with, or accelerate, your journey to become a digital business.
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Data technology experts from Pivotal give the latest perspective on how big data analytics and applications are transforming organizations across industries.
This event provides an opportunity to learn about new developments in the rapidly-changing world of big data and understand best practices in creating Internet of Things (IoT) applications.
Learn more about the Pivotal Big Data Roadshow: http://pivotal.io/big-data/data-roadshow
Driving Real Insights Through Data ScienceVMware Tanzu
Major changes in industries have been brought about by the emergence of data-driven discoveries and applications. Many organizations are bringing together their data, and looking to drive change. But the ability to generate new insights in real time from a massive sets of data is still far from commonplace.
At this event, data technology experts and data scientists from Pivotal provided the latest business perspective on how data science and engineering can be used to accelerate the generation of new insights.
For information about upcoming Pivotal events, please visit: http://pivotal.io/news-events/#events
Customer Spotlight: How WellCare Accelerated Big Data Delivery to Improve Ana...VMware Tanzu
WellCare uses Attunity Replicate to offload data quickly and easily from its SQL Server and Oracle systems into Pivotal Greenplum Database. With the help of Attunity and Pivotal, WellCare has successfully enabled real-time reporting and analytics to gain a competitive edge.
Additional information:
https://pivotal.io/big-data/webinar/healthcare-success-story-wellcare
Webinar recording:
https://youtu.be/ZYiwRUxlY2s
How Data Science is Preventing College Dropouts and Advancing Student SuccessVMware Tanzu
Educational institutions have a wealth of information, which can be brought together in an institutional data lake to predict and influence student behavior. In this webinar, one of Pivotal's principal data scientists discusses a recent collaborative project with a top university, in which many data sources were used to build a 360-degree profile of student activity on campus and help predict student success. Learn about the data science pipelines that Pivotal developed and how they are now being used to predict student metrics (such as GPA, course grade and time to graduate), and even as intervention tools to help prevent students from dropping out.
Webinar recording: https://youtu.be/SxXZBmAs1aE
Pivotal Digital Transformation Forum: Becoming a Data Driven EnterpriseVMware Tanzu
Next Steps in Your Digital Transformation
This session brings together all the lessons learnt throughout the day and shares with you practical advice on how to get started with, or accelerate, your journey to become a digital business.
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
The Vortex of Change - Digital Transformation (Presented by Intel)Cloudera, Inc.
The vortex of change continues all around us – inside the company, with our customers and partners. A new norm is upon us. Business models are being turned upside down – the hunters now the hunted, global equalization – size is no longer a guarantee of success. The innovative survive and thrive…the nervous and slow go under...what does all this change means for you? Find out how does Intel’s strengths help our customers in this world of change.
Contexti / Oracle - Big Data : From Pilot to ProductionContexti
Big Data is moving from hype to reality for many organisations. The value proposition is clear and sponsorship is high, but how do organisations execute?
Join Oracle and Contexti to discuss the typical journey of a big data project from concept to pilot to production.
• Discuss our experience with a regional Telco
• Common Use Cases across key verticals
• Defining and prioritising use cases
• The challenge of moving from Pilot to Production
• Common Operating Models for Big Data
• Funding a Big Data Capability going forward
• Pilots - common mistakes; challenges; success criteria
Data Science Case Studies: The Internet of Things: Implications for the Enter...VMware Tanzu
The Internet of Things: Implications for the Enterprise
The Internet Of Things (IoT) is already a reality but getting value out of that is still in its infancy. This session analyzes the implications of IoT for the enterprise with examples from the work we have done.
Rashmi Raghu is a Principal Data Scientist at Pivotal with a focus on the Internet-of-Things and applications in the Energy sector. Her work has spanned diverse industry problems including uncovering patterns & anomalies in massive datasets to predictive maintenance. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral work focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand.
Optimizing Regulatory Compliance with Big DataCloudera, Inc.
3 Things to Learn:
-There are many challenges in the way financial firms deal with regulatory compliance today
-Some of these challenges are related to data management and can be solved by big data technologies
-Cloudera and its partners Trifacta and Qlik are offering a solution that can accelerate the time to obtain compliance reports by using automated workflows and fast analytics that work on top of Cloudera’s Enterprise Data Hub.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Strata Conference talk on how Data Science brings IoT to life through predictive modeling.
The Internet of Things (IoT) will forever change the way businesses interact with each other and their customers. In 2020, 25 billion connected “things” will be in use, reports Gartner. IDC predictions are even higher as analysts estimate IoT will grow from 15 billion devices in 2015 to 30 billion devices in 2020.
With the adoption of these devices, effective leveraging of the torrent of data will be critical to driving the transformation of industries. Central to the fundamental shift will be the ability to pool data, and build models that drive real and significant actions.
From smart sensors to connected hospitals, Sarah will use illustrative use cases to demonstrate the fundamental concepts required to drive true impact from these connected devices. She will cover which models are most appropriate for a variety of actions and outcomes, what considerations around data access and processing are critical, and which tools are available to accomplish your task at hand.
Beyond a Big Data Pilot: Building a Production Data Infrastructure - Stampede...StampedeCon
At StampedeCon 2014, Stephen O’Sullivan (Silicon Valley Data Science) presented "Beyond a Big Data Pilot: Building a Production Data Infrastructure."
Creating a data architecture involves many moving parts. By examining the data value chain, from ingestion through to analytics, we will explain how the various parts of the Hadoop and big data ecosystem fit together to support batch, interactive and realtime analytical workloads.
By tracing the flow of data from source to output, we’ll explore the options and considerations for components, including data acquisition, ingestion, storage, data services, analytics and data management. Most importantly, we’ll leave you with a framework for understanding these options and making choices.
Protecting health and life science organizations from breaches and ransomwareCloudera, Inc.
3 Things to Learn About:
* 1. Ransomware is a particular problem and currently the highest priority for healthcare organizations. Machine learning can use the structure of a malicious email to detect an attack even before the email is opened.
* 2. Big data architectures provide the machine-learning models with the volume and variety of data required to achieve complete visibility across the spectrum of IT activity—from packets to logs to alerts.
* 3. Intel and industry partners are currently running one-hour, complimentary, confidential benchmark engagements for HLS organizations that want to see how their security compares with the industry .
Sudhir Menon, Vice President of Enterprise Information Management on Hilton’s innovation/renovation journey to create data as an enterprise asset .The data framework using HortonWorks Hadoop as the platform is the single source and repository for any enterprise-class data for reporting, analytics and data science. To achieve this transformation and levarage data as a true enterprise asset, we focused on a roadmap with 3 major objectives:
• API based delivery of data enabling real-time use
• Decommissioning legacy tools/environments
• Managing the data architecture for all IT investments in a Big Data model with scalability over years
Platform and framework to accomplish this roadmap include:
• Repository of ‘master’ data
• Real-time processing of data for the enterprise
• Best-in-class BI tools to analyze and visualize data
• Data science tools to identify underlying trends in data
Our VISION
We enable travel & hospitality market disruption through data & analytics innovation
Our MISSION
We drive Hilton’s performance with actioned, integrated insights, through market-leading, differentiated expertise and continuous innovation.
Our STRATEGy
1. Create an aspirational and unrivaled hospitality Data & Analytics team that attracts the best talent
2. Become a trusted strategic business partner, driving untapped incremental value.
3. Provide timely access to quality data and innovative solutions.
Delivering improved patient outcomes through advanced analytics 6.26.18Cloudera, Inc.
Rush University Medical Center, along with Cloudera and MetiStream, talk about adopting a comprehensive and interactive analytic platform for improved patient outcomes and better genomic analysis, highlighting examples in both genomics and clinical notes. John Spooner of 451 Research provides context to the discussion and shares market insights that complement the customer stories.
How to add security in dataops and devopsUlf Mattsson
The emerging DataOps is not Just DevOps for Data. According to Gartner, DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and consumers across an organization.
The goal of DataOps is to create predictable delivery and change management of data, data models and related artifacts. DataOps uses technology to automate data delivery with the appropriate levels of security, quality and metadata to improve the use and value of data in a dynamic environment.
This session will discuss how to add Security in DataOps and DevOps.
IoT – Present and Future
Sensor Data Processing on Pivotal Stack
Smoothing
State estimation
Edge detection
Use Case – Smart Meter Analytics
Use Case – Predictive Maintenance for Drilling
Deploying your IoT Apps on PCF
DATAOPS: THE NEXT BIG WAVE ON YOUR DATA JOURNEY - Big Data Expowebwinkelvakdag
Hitachi Vantara believes DataOps is the next big wave to hit the IT sector because it can unleash the FULL power and potential of your employees and/or customers and your data.
Imagine the number of potential transformations that didn’t come to fruition because 97.5% of your data never made it into the hands of your team. With DataOps these scenarios will be a thing of the past, because your employees and/or customers will be empowered with the right data at the right time.
This session is about DataOps, delivering the right data, to the right place at right time to the right person. DataOps achieves the promise of analytics, machine learning, and AI to transform operations and drive innovation.
The presentation will go into what DataOps is and how we as Hitachi Vantara solve the DataOps challenges.
The demonstration is targeted to the cooperation between data engineers, data scientists and business analysts to remove bottlenecks in training, tuning, testing and deploying predictive models at one side and monitoring, evaluating, comparing and rebuilding these models. Model accuracy degrades over time; monitoring and switching models is cumbersome. Hitachi Pentaho can help here.
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalHarvinder Atwal
Title
DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed.
Synopsis
● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure.
● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities.
● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product.
● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills.
● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products.
● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.
Cloudera + Syncsort: Fuel Business Insights, Analytics, and Next Generation T...Precisely
Effective AI and ML projects require a perfect blend of scalable, clean data funneled from a variety of sources across the business. The only problem? Uncleaned data often lives in hard-to-access legacy systems, and it costs time and money to build the right foundation to deliver that data to answer ever-changing questions from business users. Together, Cloudera and Syncsort enable you to build a scalable foundation of data connections to reinvent the data lifecycle of all your projects in the most efficient way possible.
View this webinar on-demand to learn how innovative solutions from Cloudera and Syncsort enable AI and ML success. You will learn:
• Best practices for transforming complex data into clear, actionable insights for AI and ML projects
• How to visually assess the quality of the sources in your data lake and their completeness, consistency, and accuracy
• The value of an Enterprise Data Cloud and the newly unveiled Cloudera Data Platform
• How Syncsort Connect integrates natively with the Cloudera Data Platform
A Modern Data Strategy for Precision MedicineCloudera, Inc.
Genomics is upon us, made possible by big data and the technologies designed to support it. Doctors, who historically used clinical data, and researchers, who historically used genomic data, are now increasingly focused on analyzing the same single data set: introducing the opportunity to share bodies of knowledge, fostering collaborative innovation, and driving toward higher standards of care.
However, this data is enormous – volumes of genomic data are expected to reach two to four exabytes per year by 2025, yet the cost of genetic sequencing has decreased 100-fold over the past 10 years.
Cloudera is helping solve the big data problem with its Apache Hadoop-based platform for large-scale data processing, discovery, and analytics; putting precision medicine within reach.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today.
The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact.
The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories:
Data Lifecycle Connection
Data for Enterprise AI
Cloud Innovation
Security & Governance Leadership
People First
Data for Good
Industry Transformation
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Big Data Roundtable. Why, how, where, which, and when to start doing Big DataRaul Goycoolea Seoane
Big Data Roundtable. Why, how, where, which, and when to start doing Big Data. Why Big Data is not just a new keyword, can be a competitive advantage if it's doing right and on time, and most important, before you competition.
Supporting a Collaborative R&D Organization with a Dynamic Big Data SolutionSaama
Nikhil Gopinath presents regarding big data solutions at the Big Data and Analytics for Healthcare and Life Sciences Summit on October 18, 2017 in San Francisco, CA.
Bridging Health Care and Clinical Trial Data through TechnologySaama
Karim Damji, SVP of Product and Marketing, presented at the Bridging Clinical Research and Clinical Health Care conference held at the Gaylord in National Harbor on April 4-5, 2018.
The Vortex of Change - Digital Transformation (Presented by Intel)Cloudera, Inc.
The vortex of change continues all around us – inside the company, with our customers and partners. A new norm is upon us. Business models are being turned upside down – the hunters now the hunted, global equalization – size is no longer a guarantee of success. The innovative survive and thrive…the nervous and slow go under...what does all this change means for you? Find out how does Intel’s strengths help our customers in this world of change.
Contexti / Oracle - Big Data : From Pilot to ProductionContexti
Big Data is moving from hype to reality for many organisations. The value proposition is clear and sponsorship is high, but how do organisations execute?
Join Oracle and Contexti to discuss the typical journey of a big data project from concept to pilot to production.
• Discuss our experience with a regional Telco
• Common Use Cases across key verticals
• Defining and prioritising use cases
• The challenge of moving from Pilot to Production
• Common Operating Models for Big Data
• Funding a Big Data Capability going forward
• Pilots - common mistakes; challenges; success criteria
Data Science Case Studies: The Internet of Things: Implications for the Enter...VMware Tanzu
The Internet of Things: Implications for the Enterprise
The Internet Of Things (IoT) is already a reality but getting value out of that is still in its infancy. This session analyzes the implications of IoT for the enterprise with examples from the work we have done.
Rashmi Raghu is a Principal Data Scientist at Pivotal with a focus on the Internet-of-Things and applications in the Energy sector. Her work has spanned diverse industry problems including uncovering patterns & anomalies in massive datasets to predictive maintenance. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral work focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand.
Optimizing Regulatory Compliance with Big DataCloudera, Inc.
3 Things to Learn:
-There are many challenges in the way financial firms deal with regulatory compliance today
-Some of these challenges are related to data management and can be solved by big data technologies
-Cloudera and its partners Trifacta and Qlik are offering a solution that can accelerate the time to obtain compliance reports by using automated workflows and fast analytics that work on top of Cloudera’s Enterprise Data Hub.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Strata Conference talk on how Data Science brings IoT to life through predictive modeling.
The Internet of Things (IoT) will forever change the way businesses interact with each other and their customers. In 2020, 25 billion connected “things” will be in use, reports Gartner. IDC predictions are even higher as analysts estimate IoT will grow from 15 billion devices in 2015 to 30 billion devices in 2020.
With the adoption of these devices, effective leveraging of the torrent of data will be critical to driving the transformation of industries. Central to the fundamental shift will be the ability to pool data, and build models that drive real and significant actions.
From smart sensors to connected hospitals, Sarah will use illustrative use cases to demonstrate the fundamental concepts required to drive true impact from these connected devices. She will cover which models are most appropriate for a variety of actions and outcomes, what considerations around data access and processing are critical, and which tools are available to accomplish your task at hand.
Beyond a Big Data Pilot: Building a Production Data Infrastructure - Stampede...StampedeCon
At StampedeCon 2014, Stephen O’Sullivan (Silicon Valley Data Science) presented "Beyond a Big Data Pilot: Building a Production Data Infrastructure."
Creating a data architecture involves many moving parts. By examining the data value chain, from ingestion through to analytics, we will explain how the various parts of the Hadoop and big data ecosystem fit together to support batch, interactive and realtime analytical workloads.
By tracing the flow of data from source to output, we’ll explore the options and considerations for components, including data acquisition, ingestion, storage, data services, analytics and data management. Most importantly, we’ll leave you with a framework for understanding these options and making choices.
Protecting health and life science organizations from breaches and ransomwareCloudera, Inc.
3 Things to Learn About:
* 1. Ransomware is a particular problem and currently the highest priority for healthcare organizations. Machine learning can use the structure of a malicious email to detect an attack even before the email is opened.
* 2. Big data architectures provide the machine-learning models with the volume and variety of data required to achieve complete visibility across the spectrum of IT activity—from packets to logs to alerts.
* 3. Intel and industry partners are currently running one-hour, complimentary, confidential benchmark engagements for HLS organizations that want to see how their security compares with the industry .
Sudhir Menon, Vice President of Enterprise Information Management on Hilton’s innovation/renovation journey to create data as an enterprise asset .The data framework using HortonWorks Hadoop as the platform is the single source and repository for any enterprise-class data for reporting, analytics and data science. To achieve this transformation and levarage data as a true enterprise asset, we focused on a roadmap with 3 major objectives:
• API based delivery of data enabling real-time use
• Decommissioning legacy tools/environments
• Managing the data architecture for all IT investments in a Big Data model with scalability over years
Platform and framework to accomplish this roadmap include:
• Repository of ‘master’ data
• Real-time processing of data for the enterprise
• Best-in-class BI tools to analyze and visualize data
• Data science tools to identify underlying trends in data
Our VISION
We enable travel & hospitality market disruption through data & analytics innovation
Our MISSION
We drive Hilton’s performance with actioned, integrated insights, through market-leading, differentiated expertise and continuous innovation.
Our STRATEGy
1. Create an aspirational and unrivaled hospitality Data & Analytics team that attracts the best talent
2. Become a trusted strategic business partner, driving untapped incremental value.
3. Provide timely access to quality data and innovative solutions.
Delivering improved patient outcomes through advanced analytics 6.26.18Cloudera, Inc.
Rush University Medical Center, along with Cloudera and MetiStream, talk about adopting a comprehensive and interactive analytic platform for improved patient outcomes and better genomic analysis, highlighting examples in both genomics and clinical notes. John Spooner of 451 Research provides context to the discussion and shares market insights that complement the customer stories.
How to add security in dataops and devopsUlf Mattsson
The emerging DataOps is not Just DevOps for Data. According to Gartner, DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and consumers across an organization.
The goal of DataOps is to create predictable delivery and change management of data, data models and related artifacts. DataOps uses technology to automate data delivery with the appropriate levels of security, quality and metadata to improve the use and value of data in a dynamic environment.
This session will discuss how to add Security in DataOps and DevOps.
IoT – Present and Future
Sensor Data Processing on Pivotal Stack
Smoothing
State estimation
Edge detection
Use Case – Smart Meter Analytics
Use Case – Predictive Maintenance for Drilling
Deploying your IoT Apps on PCF
DATAOPS: THE NEXT BIG WAVE ON YOUR DATA JOURNEY - Big Data Expowebwinkelvakdag
Hitachi Vantara believes DataOps is the next big wave to hit the IT sector because it can unleash the FULL power and potential of your employees and/or customers and your data.
Imagine the number of potential transformations that didn’t come to fruition because 97.5% of your data never made it into the hands of your team. With DataOps these scenarios will be a thing of the past, because your employees and/or customers will be empowered with the right data at the right time.
This session is about DataOps, delivering the right data, to the right place at right time to the right person. DataOps achieves the promise of analytics, machine learning, and AI to transform operations and drive innovation.
The presentation will go into what DataOps is and how we as Hitachi Vantara solve the DataOps challenges.
The demonstration is targeted to the cooperation between data engineers, data scientists and business analysts to remove bottlenecks in training, tuning, testing and deploying predictive models at one side and monitoring, evaluating, comparing and rebuilding these models. Model accuracy degrades over time; monitoring and switching models is cumbersome. Hitachi Pentaho can help here.
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalHarvinder Atwal
Title
DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed.
Synopsis
● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure.
● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities.
● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product.
● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills.
● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products.
● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.
Cloudera + Syncsort: Fuel Business Insights, Analytics, and Next Generation T...Precisely
Effective AI and ML projects require a perfect blend of scalable, clean data funneled from a variety of sources across the business. The only problem? Uncleaned data often lives in hard-to-access legacy systems, and it costs time and money to build the right foundation to deliver that data to answer ever-changing questions from business users. Together, Cloudera and Syncsort enable you to build a scalable foundation of data connections to reinvent the data lifecycle of all your projects in the most efficient way possible.
View this webinar on-demand to learn how innovative solutions from Cloudera and Syncsort enable AI and ML success. You will learn:
• Best practices for transforming complex data into clear, actionable insights for AI and ML projects
• How to visually assess the quality of the sources in your data lake and their completeness, consistency, and accuracy
• The value of an Enterprise Data Cloud and the newly unveiled Cloudera Data Platform
• How Syncsort Connect integrates natively with the Cloudera Data Platform
A Modern Data Strategy for Precision MedicineCloudera, Inc.
Genomics is upon us, made possible by big data and the technologies designed to support it. Doctors, who historically used clinical data, and researchers, who historically used genomic data, are now increasingly focused on analyzing the same single data set: introducing the opportunity to share bodies of knowledge, fostering collaborative innovation, and driving toward higher standards of care.
However, this data is enormous – volumes of genomic data are expected to reach two to four exabytes per year by 2025, yet the cost of genetic sequencing has decreased 100-fold over the past 10 years.
Cloudera is helping solve the big data problem with its Apache Hadoop-based platform for large-scale data processing, discovery, and analytics; putting precision medicine within reach.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today.
The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact.
The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories:
Data Lifecycle Connection
Data for Enterprise AI
Cloud Innovation
Security & Governance Leadership
People First
Data for Good
Industry Transformation
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Big Data Roundtable. Why, how, where, which, and when to start doing Big DataRaul Goycoolea Seoane
Big Data Roundtable. Why, how, where, which, and when to start doing Big Data. Why Big Data is not just a new keyword, can be a competitive advantage if it's doing right and on time, and most important, before you competition.
Supporting a Collaborative R&D Organization with a Dynamic Big Data SolutionSaama
Nikhil Gopinath presents regarding big data solutions at the Big Data and Analytics for Healthcare and Life Sciences Summit on October 18, 2017 in San Francisco, CA.
Bridging Health Care and Clinical Trial Data through TechnologySaama
Karim Damji, SVP of Product and Marketing, presented at the Bridging Clinical Research and Clinical Health Care conference held at the Gaylord in National Harbor on April 4-5, 2018.
Enterprise Analytics: Serving Big Data Projects for HealthcareDATA360US
Andrew Rosenberg's Presentation on "Enterprise Analytics: Serving Big Data Projects for Healthcare" at DATA 360 Healthcare Informatics Conference - March 5th, 2015
Transform to Cognitive Healthcare with IBM Software Defined Infrastructure an...Paula Koziol
Medical data is exploding. The internet of things is changing how we work and live. The healthcare industry is responding and transforming. In this cognitive and cloud era, IBM is positioned to help healthcare organizations of all sizes transform, thrive and deliver better outcomes. Learn about IBM's cognitive healthcare platform for infrastructure and how it delivers a scalable, secure hybrid cloud for GE Healthcare applications and cloud ecosystems. Review of case studies demonstrate the resiliency, flexibility and cost savings achieved while managing the velocity of enterprise imaging and healthcare data.
White paper explores Intel’s latest SSD technology, new Carestream solutions, the impact for PACS, and a look at the future of medical imaging data, access, storage and analysis.
Building an Intelligent Biobank to Power Research Decision-MakingDenodo
This presentation belongs to the workshop: "Building an Intelligent Biobank to Power Research Decision-Making", from ISBER 2015 Annual Meeting by Lori A. Ball (Chief Operating Officer, President of Integrated Client Solutions at BioStorage Technologies, Inc), Brian Brunner (Senior Manager, Clinical Practice at LabAnswer) and Suresh Chandrasekaran (Senior Vice President at Denodo).
The workshop cover three different topic areas:
- Research sample intelligence: the growing need for Global Data Integration (Biobank Sample and Data Stakeholders).
- Building a research data integration plan and cloud sourcing strategy (data integration).
- How data virtualization works and the value it delivers (a data virtualization introduction, solution portfolio and current customers in Life Sciences industry).
The biomedical R&D environment is increasingly dependent on data meta-analysis and bioinformatics to support research advancements. The integration of biorepository sample inventory data with biomarker and clinical research information has become a priority to R&D organizations. Therefore, a flexible IT system for managing sample collections, integrating sample data with clinical data and providing a data virtualization platform will enable the advancement of research studies. This workshop provides an overview of how sample data integration, virtualization and analytics can lead to more streamlined and unified sample intelligence to support global biobanking for future research.
Microsoft: A Waking Giant in Healthcare Analytics and Big DataDale Sanders
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
Open Insights Harvard DBMI - Personal Health Train - Kees van Bochove - The HyveKees van Bochove
In this talk, the Personal Health Train concept will be introduced, which enables running personalized medicine workflows as trains visiting data stations (e.g. hospital records, primary care records, clinical studies and registries, patient-held data from e.g. wearable sensors etc.) The Personal Health Train is a very powerful concept, which is however dependent on source medical data to be coded with appropriate metadata on consent, license, scope etc. of the data, and the data itself to be encoded using biomedical data standards, which is an ever growing field in biomedical informatics. In order to realize the Personal Health Train biomedical data will need to be FAIR, i.e. adopt the FAIR Guiding Principles. This talk will cover the emerging GO-FAIR international movement, and provide examples of how several European health data networks currently are adopting open standards based stacks, to enable routine health care data to be come accessible for research.
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons ...David Peyruc
tranSMART Community Meeting 5-7 Nov 13 - Session 5: Recent tranSMART Lessons Learned in Academic and Life Science Settings
Dan Housman, Recombinant by Deloitte
The Recombinant by Deloitte team has worked with organizations such as Kimmel Cancer Center as a model to adapt existing mature i2b2 implementations to meet business and scientific needs. Other organizations are increasingly focused on how to use cloud and high performance computing models to achieve different performance levels. Advanced initiatives are progressing to link commercial tools such as Qlikview to explore tranSMART data and to solve for key gaps in scientific pipelines. Dan will present recent lessons learned, new capabilities, and some of the impact on the path forwards for future tranSMART updates.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
The clinical development data deluge is reaching critical mass for pharmaceuticals. Use of varied data for targeted outcomes remains difficult, despite studies that generate evidence of the risk-benefit profile of investigational products. New technologies are federating the ability to leverage analytic-ready data for innovations in clinical operations and clinical science. With the application of clinical data-as-a-service and meta-data core, centralized clinical data lakes have the power to improve data quality, evidence generation, and time-to-insights.
Karim Damji and Benzi Mathews presented this deck at the Clinical Trial Innovation Summit held in Boston on April 24-26.
Speaker Presentation from U.S. News Healthcare of Tomorrow leadership summit, November 2-4, 2016 in Washington, DC. Find out more about this forum at www.usnewshot.com.
Hitting the Sweet Spot with Predictive Analytics (Michael Draugelis)Ashleigh Kades
Speaker Presentation from U.S. News Healthcare of Tomorrow leadership summit, November 2-4, 2016 in Washington, DC. Find out more about this forum at www.usnewshot.com.
Baptist Health: Solving Healthcare Problems with Big DataMapR Technologies
Editor’s Note: Download the complimentary MapR Guide to Big Data in Healthcare for more information: https://mapr.com/mapr-guide-big-data-healthcare/
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics.
Join this webinar to hear how Baptist Health is using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer—through their consumer- centric approach.
MapR Technologies will cover broader big data healthcare trends and production use cases that demonstrate how to converge data and compute power to deliver data-driven healthcare applications.
The Tanzu Developer Connect is a hands-on workshop that dives deep into TAP. Attendees receive a hands on experience. This is a great program to leverage accounts with current TAP opportunities.
The Tanzu Developer Connect is a hands-on workshop that dives deep into TAP. Attendees receive a hands on experience. This is a great program to leverage accounts with current TAP opportunities.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
2. Chris Roche, CEO, Aridhia
Today’s speaker
Chris joined Aridhia in 2014 to provide strategic commercial leadership
as Aridhia embraced new 3rd generation technologies to support their
new cloud based business model and collaborative data science
platform. Chris combines a background in computing, specialising in
artificial intelligence and business transformation. He spent 14 years at
EMC, where he held a number of senior director positions including
serving as Country Manager for EMC in Ireland, Regional Director for
Greenplum, EMC’s Big Data business and as EMEA CTO. He holds a
1st Class Degree in Computing and Information Technology (BScHons),
is a member of the British Computer Society (MBCS) and is qualified as
a Chartered Engineer (CEng) and Chartered Information Technology
Practitioner (CITP).
3. Data Challenges in Clinical Research
Today’s agenda
o Introduction to Clinical Research & Data
o Market Challenges and the Aridhia Business Model
o Data in Clinical Research Use Cases
o Aridhia Business Transformation Journey
o Data, Technology and Roadmap
o Q&A
6. Increasing productivity in the collaborative research workflow
Data
discovery
Data capture
Data load
Data quality
Analysis
Visualisation
Data analyst / Data owner /
Biostatistician / Researcher
Data owner
Data analyst /
Biostatistician / CRO
Data steward and analyst
/ Biostatistician / Pharma
End user
(clinician, manager, MDT,
patient, etc.)
Statistician / Data analyst /
Biostatistician and domain
expert etc.
Distribute output
7. Integrating precision medicine into the workflow
Data
discovery
Data capture
Data load
Data quality
Analysis
Visualisation
Data analyst / Data owner /
Biostatistician / Researcher
Data owner
Data analyst /
Biostatistician / CRO
Data steward and analyst
/ Biostatistician / Pharma
End user
(clinician, manager, MDT,
patient, etc.)
Statistician / Data analyst /
Biostatistician and domain
expert etc.
Distribute output
13. Change the way research and PM interacts with their data
14. ACRIS – Advanced Clinical Research Information Systems
ACRIS:
• a complex constellation of capabilities
that can rapidly assemble data assets
for clinical research questions
Provides:
• data mining and research process
support to meet the needs of clinical
and translational research
• related biostatistics and biocomputation
Includes:
• electronic health record (EHR) access
• open-source components
• an approach for big data needs
18. • Traumatic Brain Injury (TBI) is a leading worldwide problem; the annual incidence of
hospitalisation following TBI ranges from 108-332 new cases per 100,000 inhabitants
• 72 million time points of data per patient stay (mean stay 2 days)
• 1.6Gb of data per patient per day, approximately 1.5Mb of data per minute per patient
• Near real-time integration of high-frequency ICU data, research & implement physiological
models & delivery of results back to the bedside
19. • Developing tools that can predict disease activity over a 12-month horizon for adults
recently diagnosed with relapsing-onset multiple sclerosis (MS)
• Patient reported outcomes, clinical, genomic analysis and quantitative neuroimaging data
will be evaluated to determine the optimum predictive tool, enabling NHS clinicians to
map a personalised trajectory of disease and predict those patients with a high likelihood
of transitioning to secondary progressive MS
• Will enable early intervention and result in focused delivery of the finite disease modifying
treatment drug budget to patients with the most compelling basis to receive treatment
• Data capture to deliver real-time NHS data integration across 4 NHS boards
20.
21. “Radboud university medical center is a leading academic center for patient care, education and
research, with the mission ‘to have a significant impact on healthcare’.
Our activities help to improve healthcare and consequently the health of individuals and of society.
We believe we can achieve that by providing excellent quality, participatory and personalized
healthcare, operational excellence and by working together in sustainable networks.”
22. ‘From bricks to clicks’
Education
Digital Learning
Environment (DLE)
Care
Electronic Medical
Record (EMR)
Research
Digital Research
Environment (DRE)
24. Secure FTP
Flat files, XML,
unstructured Virtual DesktopWeb Access
Security and Identity Management
App User / Member Data Scientist Administrator
CollaborativeWorkspaceUserInterface
Secure Messaging
HL, FHIR, other
payload
Active
Database agent
Direct EHR
connection
Active Web
service agent
FHIR, Web Services
HealthcareLandingZone
Services
Apps
Collaborative Services
Audit
Analytical Tools
Data and Compute Fabric
Admin
N3
Connection
Repository
e.g. Genomic store
Hadoop
Workspace DB
Health Analytics
Schema (option)
Workspace DB
MGRID HL7 RIM
Schema
(roadmap)
Workspace DB
Schema-agnostic
data lake
Web Access
SQL, R, R Shiny,
MADLIB
Virtual Desktop
Bring your
own tools
Collaboration
Tagging,
messaging,
notification,
alerts
Audit
Access, usage,
authentication,
provisioning,
upload
Apps
User-built analytical apps and output
or Aridhia-populated apps
e.g. LaTEX publishing, Health Analytic
Schema, data quality…
De-identification Service
Table Mapping
Dataset Library
Health Analytics Schema
Ontology Service
Direct to File Store
Data Quality Reports Data Linkage Reports Data Selection API
Data Staging Network Security App Hosting
Healthcare Landing Zone
Precision Medicine PaaS
Multi-site LIMS
Sample
Management
CTM
System
DICOM
End-Point
BIX Workflow
Data Asset
Repository
Federated Analysis API
Life-Cycle
Container
Secure file share
Large unstructured
25. Precision Medicine
Workspace
Small Clinical Trials
Workspace
Healthcare Landing Zone Workspaces
Key Management
Database
De-identification
Service
Data Preparation
Airlock
CDR
Workspace
Data Export
Participant Privacy
Management
Core Services
Client-specific Services
Available for Subsequent Research Use
Dynamic Consent
Dataset Library
Service
Ontology Service
Health Analytics
Schema
App Hosting Area
(Analytics application/
local applications)
Data Modelling and
Compliance
Financial
& Admin
Research &
Non-clinical
Data
Research
External
Database
Care Domain
(Client)
PACS
(if
required)
EPRS &
Clinical
EPRS Direct
PACS Direct
Custom Reports
Shared Care
Portal
Archiving
Healthcare Landing Zone
26. (* = roadmap 2016)
Benefits - impact on common research tasks
Research task Tools provided Time to Value
Sourcing data Connectivity with NHS sites Weeks
Castor GCP-level EDC (partner service) Days
De-identification De-identification Service <24h
Upload SFTP, tabular data mapping Minutes
Data Quality Data quality report, Ontology Service, Dataset Library Service <3h
Linkage Consistent study IDs, data model support, omics templates* Hours
Visualisation Quick visualisation tools On demand
Exploratory Analytics R, SQL + MADLIB On demand
Feature extraction Bioinformatics, image analysis toolkits On demand
Training models MADLIB, Python, Spark*, parallel computing Hours
Common analysis R packages (e.g. Survival), 3rd party tools Hours
Publication Publication quality PDF, PowerPoint <6h
App prototyping Shiny mini-apps 1-2 days
27. Roadmap – integrated vision for clinical informatics
Collaboration
Participant
Privacy &
Consent
Precision
Medicine
Workflows
Federated
Analysis
AnalyticsHealthcare
Landing
Zone
Hospital Integrations Transactions per patientResearch & Innovation Projects
Ontology
Service
Specialty
Apps
Data
Catalogue
Electronic
Data
Capture