Date: 14th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Perry Krug
Organisation: Couchbase
About: Who wants to see an ad today for the shoes they bought last week? Everyone knows that customer experience is driven by data: don't waste an opportunity to get them the right data at the right time. Real-time results are critical, but raw speed isn't everything: you need power and flexibility to react to changes on the fly. Come learn how market-leading enterprises are using Couchbase as their speed layer for ingestion, incremental view and presentation layers alongside Kafka, Spark and Hadoop to liberate their data lakes.
Big Data LDN 2018: DATABASE FOR THE INSTANT EXPERIENCEMatt Stubbs
Date: 14th November 2018
Location: Customer Experience Theatre
Time: 12:30 - 13:00
Speaker: David Maitland
Organisation: Redis Labs
About: This session will cover the technology underpinning at the software infrastructure level required to deliver the instant experience to the end user and enterprises alike. Use cases and value derived by major brands will be shared in this insightful session based the world's most loved database REDIS.
AWS is hosting the first FSI Cloud Symposium in Hong Kong, which will take place on Thursday, March 23, 2017 at Grand Hyatt Hotel. The event will bring together FSI customers, industry professional and AWS experts, to explore how to turn the dream of transformation, innovation and acceleration into reality by exploiting Cloud, Voice to Text and IoT technologies. The packed agenda includes expert sessions on a host of pressing issues, such as security and compliance, as well as customer experience sharing on how cloud computing is benefiting the industry.
Speaker: Lijia Xu, Big Data Practice Lead, Professional Services, AWS
AWS Financial Services Cloud Symposium | Hong Kong - KeynoteAmazon Web Services
AWS is hosting the first FSI Cloud Symposium in Hong Kong, which will take place on Thursday, March 23, 2017 at Grand Hyatt Hotel. The event will bring together FSI customers, industry professional and AWS experts, to explore how to turn the dream of transformation, innovation and acceleration into reality by exploiting Cloud, Voice to Text and IoT technologies. The packed agenda includes expert sessions on a host of pressing issues, such as security and compliance, as well as customer experience sharing on how cloud computing is benefiting the industry.
Speaker: Frank Fallon, Vice President, Global Financial Services, AWS
Customer Event Hub – a modern Customer 360° view with DataStax Enterprise (DSE) Guido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented using DataStax Enterprise as the backend.
TripleLift: Preparing for a New Programmatic Ad-Tech WorldVoltDB
Michael Harroun, Director of Backend Architecture at TripleLift explores the benefits of leveraging real-time databases to power their programmatic native advertisement exchange.
Fast Data for Competitive Advantage: 4 Steps to Expand your Window of Opportu...VoltDB
In this webinar, you’ll hear VoltDB CEO, Bruce Reading, outline 4 steps to expand your window of opportunity while avoiding risky options that can destroy your business. Technology innovator and CEO of Emagine International, David Peters, will also share key lessons learned from establishing his company’s ability to use fast data to crush competitors and execute on Emagine’s ability to open new markets. To view the webinar in its entirety, click here: http://learn.voltdb.com/WRExecSeries1.html
Lessons Learned: The Impact of Fast Data for PersonalizationVoltDB
deltaDNA is leader in personalization, having honed their knowledge and skills in one of the most competitive and demanding markets: online gaming. In this Webinar, Chris Wright, deltaDNA’s CTO, joins VoltDB CMO, Peter Vescuso to explain how capturing and understanding data “in the moment” has enabled Chris to reduce margins, increase monetization, and understand his customers as well as provide the ability to react to them in real time.
Big Data LDN 2018: DATABASE FOR THE INSTANT EXPERIENCEMatt Stubbs
Date: 14th November 2018
Location: Customer Experience Theatre
Time: 12:30 - 13:00
Speaker: David Maitland
Organisation: Redis Labs
About: This session will cover the technology underpinning at the software infrastructure level required to deliver the instant experience to the end user and enterprises alike. Use cases and value derived by major brands will be shared in this insightful session based the world's most loved database REDIS.
AWS is hosting the first FSI Cloud Symposium in Hong Kong, which will take place on Thursday, March 23, 2017 at Grand Hyatt Hotel. The event will bring together FSI customers, industry professional and AWS experts, to explore how to turn the dream of transformation, innovation and acceleration into reality by exploiting Cloud, Voice to Text and IoT technologies. The packed agenda includes expert sessions on a host of pressing issues, such as security and compliance, as well as customer experience sharing on how cloud computing is benefiting the industry.
Speaker: Lijia Xu, Big Data Practice Lead, Professional Services, AWS
AWS Financial Services Cloud Symposium | Hong Kong - KeynoteAmazon Web Services
AWS is hosting the first FSI Cloud Symposium in Hong Kong, which will take place on Thursday, March 23, 2017 at Grand Hyatt Hotel. The event will bring together FSI customers, industry professional and AWS experts, to explore how to turn the dream of transformation, innovation and acceleration into reality by exploiting Cloud, Voice to Text and IoT technologies. The packed agenda includes expert sessions on a host of pressing issues, such as security and compliance, as well as customer experience sharing on how cloud computing is benefiting the industry.
Speaker: Frank Fallon, Vice President, Global Financial Services, AWS
Customer Event Hub – a modern Customer 360° view with DataStax Enterprise (DSE) Guido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented using DataStax Enterprise as the backend.
TripleLift: Preparing for a New Programmatic Ad-Tech WorldVoltDB
Michael Harroun, Director of Backend Architecture at TripleLift explores the benefits of leveraging real-time databases to power their programmatic native advertisement exchange.
Fast Data for Competitive Advantage: 4 Steps to Expand your Window of Opportu...VoltDB
In this webinar, you’ll hear VoltDB CEO, Bruce Reading, outline 4 steps to expand your window of opportunity while avoiding risky options that can destroy your business. Technology innovator and CEO of Emagine International, David Peters, will also share key lessons learned from establishing his company’s ability to use fast data to crush competitors and execute on Emagine’s ability to open new markets. To view the webinar in its entirety, click here: http://learn.voltdb.com/WRExecSeries1.html
Lessons Learned: The Impact of Fast Data for PersonalizationVoltDB
deltaDNA is leader in personalization, having honed their knowledge and skills in one of the most competitive and demanding markets: online gaming. In this Webinar, Chris Wright, deltaDNA’s CTO, joins VoltDB CMO, Peter Vescuso to explain how capturing and understanding data “in the moment” has enabled Chris to reduce margins, increase monetization, and understand his customers as well as provide the ability to react to them in real time.
Transforming Your Business with Fast Data – Five Use Case ExamplesVoltDB
Dheeraj Remella, Director of Solutions Architecture, VoltDB discusses how five customers transformed their business with VoltDB. Industries covered include ad tech data counting and tracking, content analytics for a global CDN, financial market data latency reduction and regulatory compliance, online game sessionization, player profiling and monetization and mobile network subscriber personalization, and ad delivery.
New Trend - Big Data Analytics as a service
The combination of ‘data analysis’ and 'big data-open source-cloud computing' opens up a new universe of opportunities at many levels and in many places.
Business breakout during Confluent’s streaming event in Munich, presented by Falko Schwarz, VP CEMEA at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Real-time Microservices and In-Memory Data GridsAli Hodroj
How in-memory data grids enable a real-time microservices architecture while diminishing the accidental complexity of persistence, orchestration, and fragmentation of scale.
Customer Event Hub – a modern Customer 360° view with DataStax Enterprise (DSE)Guido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented.
How Market Intelligence From Hadoop on Azure Shows Trucking Companies a Clear...DataWorks Summit
TMW Systems (a Trimble Company) has been in the business of long-haul trucking, logistics operations and fleet management for more than thirty years, but we wanted more data, so we turned to our customer community. Now, we turn that data into market intelligence, which we then provide back to our customers. To do this, we invested heavily in Hortonworks Data Platform running on Microsoft Azure in the cloud. In our talk, we’ll share our strategy for capturing operational, maintenance, financial and mobile communications information and how we provide that back to our customer base. Our approach enables advanced analytics by leveraging Big Data technologies to find new relationships in data that may have been previously overlooked. Survey responses capture business performance metrics, strategy and emerging trends from 150 businesses, representing more than 31 billion dollars in freight movement. Learn how we combine that survey data with other sources like machine and sensor data to help guide our customers to profitability.
Scylla Summit 2022: Scalable and Sustainable Supply Chains with DLT and ScyllaDBScyllaDB
Explore how IOTA addressed supply chain digitization challenges, including the role of data serialization formats (EPCIS 2.0), Distributed Ledgers (IOTA), and scalable, resilient databases (ScyllaDB) across specific use cases.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Streaming Data in the Cloud with Confluent and MongoDB Atlas | Robert Walters...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
Towards Real-Time banking API's: Introducing Coral, a web api for realtime st...Natalino Busa
Banks are innovating. The purpose of this innovation is to transform bank services into meaningful and frictionless customer experiences. A key element in order to achieve that ambitious goal is by providing well tailored and reactive APIs and provide them as the building blocks for greater and smoother customer journeys and experiences. For these API’s to work, internal processes have to evolve as well from batch processing to real time event processing.
In this talk, after providing a brief introduction of the streaming computing landscape, we describe a RESTful API called “Coral” meant to design and deploy customized and flexible data flows. The user can compose data flow for a number of data streaming goals such as on-the-fly data clustering and classifiers, streaming analytics, per-event predictive analysis , real time recommenders. Once the events are processed, Coral passes the resulting analysis as auctionable events for alerting, messaging or further processing to other systems. Coral is a flexible and generic event processing platform to transform streaming data into actionable events via a RESTful API. Those data flows are defined via the Web API by connecting together basic streaming processing elements named “coral actors”. The Coral framework manages those coral actors on a distributed and scalable architecture.
Streaming and real time data processing and analytics are the key elements to an improved customer experience. In this way, you can get the most targeted processing for your domain (marketing customization, personalized recommenders, fraud detection, real time security alerting, etc.). This streaming “data flow” model implies processing customers’ events as soon as they enter via web APIs. This approach borrows a lot from distributed “data flow” concepts developed for processor architectures back in the 80’s. The “Coral” streaming processing engine is generic and built on top of world class libraries such as Akka and Spark, and fully exposed via a RESTful web API.
Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020HostedbyConfluent
This session will describe and demonstrate the longstanding integration between Couchbase Server and Apache Kafka and will include descriptions of both the mechanics of the integration and practical situations when combining these products is appropriate.
Couchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQLDATAVERSITY
Thousands of companies, from Uber and Netflix to Goldman Sachs and Cisco, use Apache Kafka to transform and reshape their data architectures. Kafka is frequently used as the bridge between legacy RDBMS and new NoSQL database systems, effectively transforming SQL table data into JSON documents and vice versa. Many companies also use Kafka for business-critical applications that drive real-time stream processing and analytics, intersystem messaging, high-volume data ingestion, and operational metrics collection.
Couchbase and Kafka can be used together to address high throughput, distributed data management, and transformation challenges.
In this webinar we’ll explore:
Where Kafka fits into the big data ecosystem
How companies are using Kafka for both real-time processing and as a bus for data exchange
An example of how Kafka can bridge legacy RDBMS and new NoSQL database systems
Several real-world use case architectures
Transforming Your Business with Fast Data – Five Use Case ExamplesVoltDB
Dheeraj Remella, Director of Solutions Architecture, VoltDB discusses how five customers transformed their business with VoltDB. Industries covered include ad tech data counting and tracking, content analytics for a global CDN, financial market data latency reduction and regulatory compliance, online game sessionization, player profiling and monetization and mobile network subscriber personalization, and ad delivery.
New Trend - Big Data Analytics as a service
The combination of ‘data analysis’ and 'big data-open source-cloud computing' opens up a new universe of opportunities at many levels and in many places.
Business breakout during Confluent’s streaming event in Munich, presented by Falko Schwarz, VP CEMEA at Confluent. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Real-time Microservices and In-Memory Data GridsAli Hodroj
How in-memory data grids enable a real-time microservices architecture while diminishing the accidental complexity of persistence, orchestration, and fragmentation of scale.
Customer Event Hub – a modern Customer 360° view with DataStax Enterprise (DSE)Guido Schmutz
Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme.
To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation.
In this presentation the value of such a platform is shown and how it can be implemented.
How Market Intelligence From Hadoop on Azure Shows Trucking Companies a Clear...DataWorks Summit
TMW Systems (a Trimble Company) has been in the business of long-haul trucking, logistics operations and fleet management for more than thirty years, but we wanted more data, so we turned to our customer community. Now, we turn that data into market intelligence, which we then provide back to our customers. To do this, we invested heavily in Hortonworks Data Platform running on Microsoft Azure in the cloud. In our talk, we’ll share our strategy for capturing operational, maintenance, financial and mobile communications information and how we provide that back to our customer base. Our approach enables advanced analytics by leveraging Big Data technologies to find new relationships in data that may have been previously overlooked. Survey responses capture business performance metrics, strategy and emerging trends from 150 businesses, representing more than 31 billion dollars in freight movement. Learn how we combine that survey data with other sources like machine and sensor data to help guide our customers to profitability.
Scylla Summit 2022: Scalable and Sustainable Supply Chains with DLT and ScyllaDBScyllaDB
Explore how IOTA addressed supply chain digitization challenges, including the role of data serialization formats (EPCIS 2.0), Distributed Ledgers (IOTA), and scalable, resilient databases (ScyllaDB) across specific use cases.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Streaming Data in the Cloud with Confluent and MongoDB Atlas | Robert Walters...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
Towards Real-Time banking API's: Introducing Coral, a web api for realtime st...Natalino Busa
Banks are innovating. The purpose of this innovation is to transform bank services into meaningful and frictionless customer experiences. A key element in order to achieve that ambitious goal is by providing well tailored and reactive APIs and provide them as the building blocks for greater and smoother customer journeys and experiences. For these API’s to work, internal processes have to evolve as well from batch processing to real time event processing.
In this talk, after providing a brief introduction of the streaming computing landscape, we describe a RESTful API called “Coral” meant to design and deploy customized and flexible data flows. The user can compose data flow for a number of data streaming goals such as on-the-fly data clustering and classifiers, streaming analytics, per-event predictive analysis , real time recommenders. Once the events are processed, Coral passes the resulting analysis as auctionable events for alerting, messaging or further processing to other systems. Coral is a flexible and generic event processing platform to transform streaming data into actionable events via a RESTful API. Those data flows are defined via the Web API by connecting together basic streaming processing elements named “coral actors”. The Coral framework manages those coral actors on a distributed and scalable architecture.
Streaming and real time data processing and analytics are the key elements to an improved customer experience. In this way, you can get the most targeted processing for your domain (marketing customization, personalized recommenders, fraud detection, real time security alerting, etc.). This streaming “data flow” model implies processing customers’ events as soon as they enter via web APIs. This approach borrows a lot from distributed “data flow” concepts developed for processor architectures back in the 80’s. The “Coral” streaming processing engine is generic and built on top of world class libraries such as Akka and Spark, and fully exposed via a RESTful web API.
Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020HostedbyConfluent
This session will describe and demonstrate the longstanding integration between Couchbase Server and Apache Kafka and will include descriptions of both the mechanics of the integration and practical situations when combining these products is appropriate.
Couchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQLDATAVERSITY
Thousands of companies, from Uber and Netflix to Goldman Sachs and Cisco, use Apache Kafka to transform and reshape their data architectures. Kafka is frequently used as the bridge between legacy RDBMS and new NoSQL database systems, effectively transforming SQL table data into JSON documents and vice versa. Many companies also use Kafka for business-critical applications that drive real-time stream processing and analytics, intersystem messaging, high-volume data ingestion, and operational metrics collection.
Couchbase and Kafka can be used together to address high throughput, distributed data management, and transformation challenges.
In this webinar we’ll explore:
Where Kafka fits into the big data ecosystem
How companies are using Kafka for both real-time processing and as a bus for data exchange
An example of how Kafka can bridge legacy RDBMS and new NoSQL database systems
Several real-world use case architectures
Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement ...confluent
(Bruno Simic, Solutions Engineer, Couchbase)
Breakout during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Why microservices architectures drive exceptional customer experiencesDenis Wilson Souza Rosa
An introduction to why microservices is a mandatory architecture for flexible and highly scalable applications and which are some of the most common problems.
View the recording:
http://hortonworks.com/webinar/accelerating-real-time-data-ingest-hadoop/
Hadoop didn’t disrupt the data center. The exploding amounts of data did. But, let’s face it, if you can’t move your data to Hadoop, then you can’t use it in Hadoop. The experts from Hortonworks, the #1 leader in Hadoop development, and Attunity, a leading data management software provider, cover:
- How to ingest your most valuable data into Hadoop using Attunity Replicate
- About how customers are using Hortonworks DataFlow (HDF) powered by Apache NiFi
- How to combine the real-time change data capture (CDC) technology with connected data platforms from Hortonworks
We discuss how Attunity Replicate and Hortonworks Data Flow (HDF) work together to move data into Hadoop.
Operational Analytics Using Spark and NoSQL Data StoresDATAVERSITY
NoSQL data stores have emerged for scalable capture and real-time analysis of data. Apache Spark and Hadoop provide additional scalable analytics processing. This session looks at these technologies and how they can be used to support operational analytics to improve operational effectiveness. It also looks at an example of how operational analytics can be implemented in NoSQL environments using the Basho Data Platform with Apache Spark:
•The emergence of NoSQL, Hadoop and Apache Spark
•NoSQL Use Cases
•The need for operational analytics
•Types of operational analysis
•Key requirements for operational analytics
•Operational analytics using the Basho Data Platform with Apache Spark.
apidays LIVE Singapore 2022_Redesigning Data Architecture.pdfapidays
apidays LIVE Singapore 2022: Digitising at scale with APIs
April 20 & 21, 2022
Redesign Your Data Architecture to Deliver Modern, Personalized Applications
Jeff Morris, VP Product & Solutions Marketing at Couchbase
------------
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This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...Timothy Spann
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipelines
https://www.meetup.com/futureofdata-newyork/events/298660453/
Unlocking Financial Data with Real-Time Pipelines
(Flink Analytics on Stocks with SQL )
By Timothy Spann
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data. I will be utilizing NiFi 2.0 with Python and Vector Databases.
Timothy Spann
Principal Developer Advocate, Cloudera
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
https://twitter.com/PaaSDev
https://www.linkedin.com/in/timothyspann/
https://medium.com/@tspann
https://github.com/tspannhw/FLiPStackWeekly/
No sql data-storage for-your-ios-apps-using-couchbase-mobilePriya Rajagopal
This talk will introduce you to Couchbase Mobile - an open source, JSON Document Data store for your mobile platforms. If you have ever built or are thinking of building an iOS app with offline data storage capabilities, you have probably looked at Core Data or SQLite and you have probably realized that it’s a daunting task. There are many challenges and this talk will begin by examining some of the main requirements of an offline storage solution. This talk includes a discussion of NoSQL technologies focussing on the JSON Document Style. You will get an overview of the Couchbase Mobile architecture and examples that demonstrate the CRUD and Query API for managing your data store.
Today, data lakes are widely used and have become extremely affordable as data volumes have grown. However, they are only meant for storage and by themselves provide no direct value. With up to 80% of data stored in the data lake today, how do you unlock the value of the data lake? The value lies in the compute engine that runs on top of a data lake.
Join us for this webinar where Ahana co-founder and Chief Product Officer Dipti Borkar will discuss how to unlock the value of your data lake with the emerging Open Data Lake analytics architecture.
Dipti will cover:
-Open Data Lake analytics - what it is and what use cases it supports
-Why companies are moving to an open data lake analytics approach
-Why the open source data lake query engine Presto is critical to this approach
Data-Centric Infrastructure for Agile DevelopmentDATAVERSITY
Most data centers are filled with rigid data servers that are tightly linked to specific applications, leading to data duplication, lengthy development cycles, and unnecessary costs. Learn how you can use an Enterprise NoSQL database platform to help create a flexible, agile data fabric that will allow you to iterate your application development, optimize your data, and reduce costs.
When your enterprise infrastructure is data-centric instead of application-centric, you make it easy for anyone to pull crucial data without spending unnecessary time and money on plumbing...freeing resources for building better applications. Learn how other companies have built –and benefited from– a data-centric infrastructure for agile development.
Ingest and manage all your data, documents, and semantic triples in a flexible, schema-agnostic platform – without sacrificing the ACID transactions, granular security, database management tools and other features you’ve come to expect in a mature database platform
Quickly build complex, interactive search applications
Deliver robust, real-time search and alerting within your applications
Use – and optimize – modern infrastructure including Hadoop and cloud to attain operational agility
Simplify implementation of data governance requirements around security, privacy, provenance, retention, continuity, and compliance – while reducing risk, cost, and time
GSJUG: Mastering Data Streaming Pipelines 09May2023Timothy Spann
GSJUG: Mastering Data Streaming Pipelines 09May2023
https://www.meetup.com/futureofdata-princeton/events/293233881/
This is a repost from the Garden State Java Users Group Event.
Join me at
https://www.meetup.com/garden-state-java-user-group/events/293229660/
See: https://www.eventbrite.com/e/mastering-data-streaming-pipelines-tickets-627677218457?_ga=2.253257801.1787151623.1682868226-741104479.1678110925
Please note that registration via EventBrite is required to attend either in-person or online.
We are happy to announce that Tim Spann will be our special guest for the May 9, 2023 meeting!
Abstract:
In this session, Tim will show you some best practices that he has discovered over the last seven years in building data streaming applications including IoT, CDC, Logs, and more.
In his modern approach, we utilize several Apache frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Kafka. From there we build streaming ETL with Apache Flink, enhance events with NiFi enrichment. We build continuous queries against our topics with Flink SQL.
We will show where Java fits in as sources, enrichments, NiFi processors and sinks.
We hope to see you on May 9!
Speaker
Timothy Spann
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Pulsar, Apache Kafka, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming.
Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
In this session, Tim will show you some best practices that he has discovered over the last seven years in building data streaming applications, including IoT, CDC, Logs, and more.
In his modern approach, we utilize several Apache frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Kafka. From there, we build streaming ETL with Apache Flink, enhance events with NiFi enrichment. We build continuous queries against our topics with Flink SQL.
We will show where Java fits in as sources, enrichments, NiFi processors, and sinks.
https://www.eventbrite.com/e/mastering-data-streaming-pipelines-tickets-627677218457?_ga=2.253257801.178
OSACon 2023_ Unlocking Financial Data with Real-Time PipelinesTimothy Spann
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
Unlocking Financial Data with Real-Time Pipelines
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data.
Key Points to be Covered:
Introduction to Real-Time Data Pipelines: a. The limitations of traditional batch processing in the financial domain. b. Understanding the need for real-time data processing.
Apache Flink: Powering Real-Time Stream Processing: a. Overview of Apache Flink and its role in real-time stream processing. b. Use cases for Apache Flink in the financial industry. c. How Flink enables fast, scalable, and fault-tolerant processing of streaming financial data.
Apache Kafka: Building Resilient Event Streaming Platforms: a. Introduction to Apache Kafka and its role as a distributed streaming platform. b. Kafka's capabilities in handling high-throughput, fault-tolerant, and real-time data streaming. c. Integration of Kafka with financial data sources and consumers.
Apache NiFi: Data Ingestion and Flow Management: a. Overview of Apache NiFi and its role in data ingestion and flow management. b. Data integration and transformation capabilities of NiFi for financial data. c. Utilizing NiFi to collect and process financial data from diverse sources.
Iceberg: Efficient Data Lake Management: a. Understanding Iceberg and its role in managing large-scale data lakes. b. Iceberg's schema evolution and table-level metadata capabilities. c. How Iceberg simplifies data lake management in financial institutions.
Real-World Use Cases: a. Real-time fraud detection using Flink, Kafka, and NiFi. b. Portfolio risk analysis with Iceberg and Flink. c. Streamlined regulatory reporting leveraging all four technologies.
Best Practices and Considerations: a. Architectural considerations when building real-time financial data pipelines. b. Ensuring data integrity, security, and compliance in real-time pipelines. c. Scalability an
Similar to Big Data LDN 2018: BIG DATA TOO SLOW? SPRINKLE IN SOME NOSQL (20)
Blueprint Series: Banking In The Cloud – Ultra-high Reliability ArchitecturesMatt Stubbs
Data architecture for a challenger bank.Speaker: Jason Maude, Head of Technology Advocacy, Starling BankSpeaker Bio: Jason Maude is a coder, coach, and public speaker. He has over a decade of experience working in the financial sector, primarily in creating and delivering software. He is passionate about explaining complex technical concepts to those who are convinced that they won't be able to understand them. He currently works at Starling Bank as their Head of Technology Advocacy and host of the Starling podcast.Filmed at Skills Matter/Code Node London on 9th May 2019 as part of the Big Data LDN Meetup Blueprint Series.Meetup sponsored by DataStax.
Speed Up Your Apache Cassandra™ Applications: A Practical Guide to Reactive P...Matt Stubbs
Speaker: Cedrick Lunven, Developer Advocate, DataStax
Speaker Bio: Cedrick is a Developer Advocate at DataStax where he finds opportunities to share his passions by speaking about developing distributed architectures and implementing reference applications for developers. In 2013, he created FF4j, an open source framework for Feature Toggle which he still actively maintains. He is now contributor in JHipster team.
Talk Synopsis: We have all introduced more or less functional programming and asynchronous operations into our applications in order to speed up and distribute treatments (e.g., multi-threading, future, completableFuture, etc.). To build truly non-blocking components, optimize resource usage, and avoid "callback hell" you have to think reactive—everything is an event.
From the frontend UI to database communications, it’s now possible to develop Java applications as fully reactive with frameworks like Spring WebFlux and Reactor. With high throughput and tunable consistency, applications built on top of Apache Cassandra™ fit perfectly within this pattern.
DataStax has been developing Apache Cassandra drivers for years, and in the latest version of the enterprise driver we introduced reactive programming.
During this session we will migrate, step by step, a vanilla CRUD Java service (SpringBoot / SpringMVC) into reactive with both code review and live coding. Bring home a working project!
Filmed at Skills Matter/Code Node London on 9th May 2019 as part of the Big Data LDN Meetup Blueprint Series.
Meetup sponsored by DataStax.
Blueprint Series: Expedia Partner Solutions, Data PlatformMatt Stubbs
Join Anselmo for an engaging overview of the new end-to-end data architecture at Expedia Group, taking a journey through cloud and on-prem data lakes, real-time and batch processes and streamlined access for data producers and consumers. Find out how the new architecture unifies a complex mix of data sources and feeds the data science development cycle. Expedia might appear to be a market-leading travel company – in reality, it’s a highly successful technology and data science company.
Blueprint Series: Architecture Patterns for Implementing Serverless Microserv...Matt Stubbs
Richard Freeman talks about how the data science team at JustGiving built KOALA, a fully serverless stack for real-time web analytics capture, stream processing, metrics API, and storage service, supporting live data at scale from over 26M users. He discusses recent advances in serverless computing, and how you can implement traditionally container-based microservice patterns using serverless-based architectures instead. Deploying Serverless in your organisation can dramatically increase the delivery speed, productivity and flexibility of the development team, while reducing the overall running, DevOps and maintenance costs.
Big Data LDN 2018: ENABLING DATA-DRIVEN DECISIONS WITH AUTOMATED INSIGHTSMatt Stubbs
Date: 13th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Charlotte Emms
Organisation: seenit
About: How do you get your colleagues interested in the power of data? Taking you through Seenit’s journey using Couchbase's NoSQL database to create a regular, fully automated update in an easily digestible format.
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
Date: 13th November 2018
Location: Governance and MDM Theatre
Time: 12:30 - 13:00
Organisation: Immuta
About: Artificial intelligence is rising in importance, but it’s also increasingly at loggerheads with data protection regimes like the GDPR—or so it seems. In this talk, Sophie will explain where and how AI and GDPR conflict with one another, and how to resolve these tensions.
Big Data LDN 2018: REALISING THE PROMISE OF SELF-SERVICE ANALYTICS WITH DATA ...Matt Stubbs
Date: 13th November 2018
Location: Governance and MDM Theatre
Time: 11:50 - 12:20
Speaker: Mark Pritchard
Organisation: Denodo
About: Self-service analytics promises to liberate business users to perform analytics without the assistance of IT, and this in turn promises to free IT to focus on enhancing the infrastructure.
Join us to learn how data virtualization will allow you to gain real-time access to enterprise-wide data and deliver self-service analytics. We will explore how you can seamlessly unify fragmented data, replace your high-maintenance and high cost data integrations with a single, low-maintenance data virtualization layer; and how you can preserve your data integrity and ensure data lineage is fully traceable.
Big Data LDN 2018: TURNING MULTIPLE DATA LAKES INTO A UNIFIED ANALYTIC DATA L...Matt Stubbs
Date: 13th November 2018
Location: Governance and MDM Theatre
Time: 11:10 - 11:40
Organisation: TIBCO
About: The big data phenomenon continues to accelerate, resulting in multiple data lakes at most organisations. However, according to Gartner, “Through 2019, 90% of the information assets from big data analytic efforts will be siloed and unusable across multiple business processes.”
Are you ready to unleash this data from these silos and deliver the insights your organisation needs to drive compelling customer experiences, innovative new products and optimized operations? In this session you will learn how to apply data virtualisation to: - Access, transform and deliver data from across your lakes, clouds and other data sources - Empower a range of analytic users and tools with all the data they need - Move rapidly to a modern and flexible data architecture for the long run In addition, you will see a demonstration of data virtualisation in action.
Big Data LDN 2018: CONSISTENT SECURITY, GOVERNANCE AND FLEXIBILITY FOR ALL WO...Matt Stubbs
Date: 14th November 2018
Location: Data-Driven Ldn Theatre
Time: 12:30 - 13:00
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About: The growth of public cloud is reinforcing the need to think more carefully about taking a consistent approach to data governance as technology teams build out a flexible and agile infrastructure to meet the demands of the business.
Join this session to learn more about Cloudera's recommended approach for enterprise-grade security and governance and how to ensure a consistent framework across private, public and on-premises environments.
Big Data LDN 2018: MICROLISE: USING BIG DATA AND AI IN TRANSPORT AND LOGISTICSMatt Stubbs
Date: 14th November 2018
Location: Data-Driven Ldn Theatre
Time: 11:10 - 11:40
Organisation: Microlise
About: Microlise are a leading provider of technology solutions to the transport and logistics industry worldwide. Discover how, with over 400,000 connected assets generating billions of messages a day, Microlise is evolving its platform to bring real-time analytics to its customers to improve safety, security and efficiency outcomes.
Big Data LDN 2018: EXPERIAN: MAXIMISE EVERY OPPORTUNITY IN THE BIG DATA UNIVERSEMatt Stubbs
Date: 14th November 2018
Location: Data-Driven Ldn Theatre
Time: 10:30 - 11:00
Speaker: Anna Matty
Organisation: Experian
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Data and innovation offer huge potential to revolutionise all markets. There is an opportunity to be one step ahead of the need, to redesign journeys and enhance enterprise strategies. To do this you need access to the most advanced analytics but also the best quality, including variations and types of data, and then the technology that can act on this insight. Data science can present a unique opportunity for uncovered growth and accelerate your business through strategic innovation – fast. In this session you will hear more about how today's analytics can move from a single task, to an ongoing strategic opportunity. An opportunity that helps you move at the speed of the market and helps you maximise every opportunity.
Big Data LDN 2018: A LOOK INSIDE APPLIED MACHINE LEARNINGMatt Stubbs
Date: 13th November 2018
Location: Data-Driven Ldn Theatre
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Organisation: Cloudera
About: The field of machine learning (ML) ranges from the very practical and pragmatic to the highly theoretical and abstract. This talk describes several of the challenges facing organisations that want to leverage more of their data through ML, including some examples of the applied algorithms that are already delivering value in business contexts.
Big Data LDN 2018: DEUTSCHE BANK: THE PATH TO AUTOMATION IN A HIGHLY REGULATE...Matt Stubbs
Date: 13th November 2018
Location: Data-Driven Ldn Theatre
Time: 12:30 - 13:00
Speaker: Paul Wilkinson, Naveen Gupta
Organisation: Cloudera
About: Investment banks are faced with some of the toughest regulatory requirements in the world. In a market where data is increasing and changing at extraordinary rates the journey with data governance never ends.
In this session, Deutsche Bank will share their journey with big data and explain some of the processes and techniques they have employed to prepare the bank for today’s challenges and tomorrow’s opportunities.
Brought to you by Naveen Gupta, VP Software Engineering, Deutsche Bank and Paul Wilkinson, Principal Solutions Architect, Cloudera.
Big Data LDN 2018: FROM PROLIFERATION TO PRODUCTIVITY: MACHINE LEARNING DATA ...Matt Stubbs
Date: 14th November 2018
Location: Self-Service Analytics Theatre
Time: 13:50 - 14:20
Speaker: Stephanie McReynolds
Organisation: Alation
About: Raw data is proliferating at an enormous rate. But so are our derived data assets - hundreds of dashboards, thousands of reports, millions of transformed data sets. Self-service analytics have ensured that this noise is making it increasingly hard to understand and trust data for decision-making. This trust gap is holding your organisation back from business outcomes.
European analytics leaders have found a way to close the gap between data and decision-making. From MunichRe to Pfizer and Daimler, analytics teams are adopting data catalogues for thousands of self-service analytics users.
Join us in this session to hear how data catalogues that activate data by incorporating machine learning can:
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Big Data LDN 2018: DATA APIS DON’T DISCRIMINATEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics Theatre
Time: 15:50 - 16:20
Speaker: Nishanth Kadiyala
Organisation: Progress
About: The exploding API economy, combined with an advanced analytics market projected to reach $30 billion by 2019, is forcing IT to expose more and more data through APIs. Business analysts, data engineers, and data scientists are still not happy because their needs never really made it into the existing API strategies. This is because most APIs are designed for application integration, but not for the data workers who are looking for APIs that facilitate direct data access to run complex analytics. Data APIs are specifically designed to provide that frictionless data access experience to support analytics across standard interoperable interfaces such as OData (REST) or ODBC/JDBC (SQL). Consider expanding your API strategy to service the developers with open analytics in this $30 billion market.
Big Data LDN 2018: A TALE OF TWO BI STANDARDS: DATA WAREHOUSES AND DATA LAKESMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics Theatre
Time: 14:30 - 15:00
Speaker: Zaf Khan
Organisation: Arcadia Data
About: The use of data lakes continue to grow, and a recent survey by Eckerson Group shows that organizations are getting real value from their deployments. However, there’s still a lot of room for improvement when it comes to giving business users access to the wealth of potential insights in the data lake.
While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, organizations often struggle with data lakes because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives?
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Big Data LDN 2018: FIGHTING DATA CHAOS: CONNECTING USERS TO DATA AT SCALEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics
Theatre Time: 12:30 - 13:00
Speaker: Joel McKelvey
Organisation: Looker
About: Companies that use data well are more efficient, effective, and profitable. Unfortunately, most organizations struggle to keep up with the changing supply of data — and the growing business demands for that data. The key is to connect data supply to data users in a way that scales, supports existing workflows, and serves as a foundation for the future.
This session will explore how to bring data to users where and when they need it without sacrificing data governance or unified metrics. This session will also present proven ways to build a data foundation for your organisation that can support future changes in both data supply and data demand.
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• How to provide users access to data in a way that naturally fits in their existing workflows and allows users to take immediate action.
• How companies like Deliveroo and King extract critical business insights from growing data and deliver those insights to their business users.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
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3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
