Real time stock processing with apache nifi, apache flink and apache kafka

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Real time stock processing with apache nifi, apache flink and apache kafka with Kafka Connect apps, SMM, NiFi Registry, Scheam Registry, Kafka topics, Flink SQL, NiFi

Technologie

Real-Time Stock Processing
With Apache NiFi, Apache Flink and Apache Kafka
Timothy Spann, Principal DataFlow Field Engineer @
Pierre Villard, Senior Product Manager @

Who?
Tim Spann
@PaasDev // Blog: www.datainmotion.dev
Principal DataFlow Field Engineer. Princeton Future of Data Meetup.
https://github.com/tspannhw/EverythingApacheNiFi
https://community.cloudera.com/t5/Community-Articles/Real-Time-Stock-Processing-With-A
pache-NiFi-and-Apache-Kafka/ta-p/249221
Pierre Villard
Twitter & Github - @pvillard31 // Blog: www.pierrevillard.com
Committer and PMC member for Apache NiFi (in the community since 2015)
Senior Product Manager at Cloudera for products around Apache NiFi, NiFi Registry and MiNiFi
Previously at Google & Hortonworks

What?
This talk is about ingesting real-time data from many sources and build a dashboard on top it to track in
real time what our stocks are.
This use case is a good example to show the combination of some of the best Apache solutions for
streaming applications.

NiFi, Kafka and Flink in a few numbers
- Apache NiFi (version 1.12.x) - created and open sourced by the NSA - initial release in 2006
350+ contributors, 1200+ people in Slack, 3.1M+ docker pulls
Many sub-projects: NiFi, MiNiFi Java, MiNiFi C++, NiFi Registry, etc
- Apache Kafka (version 2.6.x) - created and open sourced by LinkedIn - initial release in 2011
700+ contributors
- Apache Flink (version 1.11.x) - initial release in 2011
750+ contributors, 2nd top repository by number of commits, top active project on mailing lists

Analyze
Streaming OLAP
Analytics & Time Series
Store Powered by
Druid & Kudu
Buffer
Apache Kafka
Topics
Ingest Gateway
Powered by Kafka
Distribute
Apache NiFi
Data Flow Apps
Powered by NiFi
Buffer
Apache Kafka
Syndicate
topics
Syndicate Services
Powered by Kafka
Collect
Syndicate
topics
Syndicate Services
Powered by Kafka
Replication /
Data Deployment
Analyze
Streaming Analytics Apps
Stream Processing
Powered by Flink
Streaming Reference Architecture
Data Collection
at the Edge
Apache NiFi / MiNiFi
- sensors, IoT
- databases
- ﬁle systems
- app sidecar
- live streams
- MQ
- logs
- network
Anything… you
name it!

Where?
CDP services are optimized for the elastic
compute & ‘always-on’ storage services provided
by any cloud provider
Web service hosted and managed by Cloudera
Hosted in the your cloud environment, but
managed by the CDP Management Console
Shared Data Experience (SDX) technologies form
a secure and governed data lake backed by object
storage (S3, ADLS, GCS)
Flow Management Streams Messaging Streaming Analytics

How? This use case architecture
Stock Data
Logs
Errors
Aggregates
Other data
SQL
Analytics

Demonstration
Let’s see all of this in action…

Thanks! Questions?
Timothy Spann, Principal DataFlow Field Engineer @
Pierre Villard, Senior Product Manager @

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28March2024-Codeless-Generative-AI-Pipelines https://www.meetup.com/futureofdata-princeton/events/299440871/ https://www.meetup.com/real-time-analytics-meetup-ny/events/299290822/ ******Note***** The event is seat-limited, therefore please complete your registration here. Only people completing the form will be able to attend. ----------------------- We're excited to invite you to join us in-person, for a Real-Time Analytics exploration! Join us for an evening of insights, networking as we delve into the OSS technologies shaping the field! Agenda: 05:30-06:00: Pizza and friends 06:00- 06:40: Codeless GenAI Pipelines with Flink, Kafka, NiFi 06:40- 07:20 Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders 07:20-07:30 QNA Codeless GenAI Pipelines with Flink, Kafka, NiFi | Tim Spann, Cloudera Explore the power of real-time streaming with GenAI using Apache NiFi. Learn how NiFi simplifies data engineering workflows, allowing you to focus on creativity over technical complexities. I'll guide you through practical examples, showcasing NiFi's automation impact from ingestion to delivery. Whether you're a seasoned data engineer or new to GenAI, this talk offers valuable insights into optimizing workflows. Join us to unlock the potential of real-time streaming and witness how NiFi makes data engineering a breeze for GenAI applications! Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders | Viktor Gamov, StarTree Explore how industry leaders like LinkedIn, Uber Eats, and Stripe are mastering real-time data with Viktor as your guide. Discover how Apache Pinot transforms data into actionable insights instantly. Viktor will showcase Pinot's features, including the Star-Tree Index, and explain why it's a game-changer in data strategy. This session is for everyone, from data geeks to business gurus, eager to uncover the future of tech. Join us and be wowed by the power of real-time analytics with Apache Pinot! ------- 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.

28March2024-Codeless-Generative-AI-Pipelines

Timothy Spann

https://princetonacm.acm.org/tcfpro/ 18th Annual IEEE IT Professional Conference (ITPC) Armstrong Hall at The College of New Jersey Friday, March 15th, 2024 | 10:00 AM to 5:00 PM IT Professional Conference at Trenton Computer Festival IEEE Information Technology Professional Conference on Friday, March 15th, 2024 TCFPro24 Building Real-Time Generative AI Pipelines Building Real-Time Generative AI Pipelines In this talk, Tim will delve into the exciting realm of building real-time generative AI pipelines with streaming capabilities. The discussion will revolve around the integration of cutting-edge technologies to create dynamic and responsive systems that harness the power of generative algorithms. From leveraging streaming data sources to implementing advanced machine learning models, the presentation will explore the key components necessary for constructing a robust real-time generative AI pipeline. Practical insights, use cases, and best practices will be shared, offering a comprehensive guide for developers and data scientists aspiring to design and implement dynamic AI systems in a streaming environment. Tim will show a live demo showing we can use Apache NiFi to provide a live chat between a person in Slack and several LLM models all orchestrated with Apache NiFi, Apache Kafka and Python. We will use RAG against Chroma and Pinecone vector data stores, Hugging Face and WatsonX.AI LLM, and add additional context with NiFi lookups of stocks, weather and other data streams in real-time. 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.

TCFPro24 Building Real-Time Generative AI Pipelines

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2024 Build Generative AI for Non-Profits

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/

2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...

Timothy Spann

Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg with Stock Data and LLM Abstract In this talk, we’ll discuss how to use Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg to process and analyze stock data. We demonstrated the ingestion, processing, and analysis of stock data. Additionally, we illustrated how to use an LLM to generate predictions from the analyzed data. Karin Wolok Developer Relations, Dev Marketing, and Community Programming @ Project Elevate Karin Wolok's LinkedIn account Karin Wolok's twitter account Tim Spann Principal Developer Advocate @ Cloudera Tim Spann's LinkedIn account Tim Spann's twitter account https://www.conf42.com/Python_2024_Karin_Wolok_Tim_Spann_nifi__kafka_risingwave_iceberg_llm

Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg...

Timothy Spann

2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines https://www.aicamp.ai/event/eventdetails/W2024022214 apache nifi llm generative ai gen ai ml dl machine learning apache kafka apache flink postgresql python AI Meetup (NYC): GenAI, LLMs, ML and Data Feb 22, 05:30 PM EST Welcome to the monthly in-person AI meetup in New York City, in collaboration with Microsoft. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers Agenda: * 5:30pm~6:00pm: Checkin, Food/drink and networking * 6:00pm~6:10pm: Welcome/community update * 6:10pm~8:30pm: Tech talks * 8:30pm: Q&A, Open discussion Tech Talk: Searching and Reasoning Over Multimedia Data with Vector Databases and LMMs Speaker: Zain Hasan (Weaviate LinkedIn) Abstract: In this talk, Zain Hasan will discuss how we can use open-source multimodal embedding models in conjunction with large generative multimodal models that can that can see, hear, read, and feel data(!), to perform cross-modal search(searching audio with images, videos with text etc.) and multimodal retrieval augmented generation (MM-RAG) at the billion-object scale with the help of open source vector databases. I will also demonstrate, with live code demos, how being able to perform this cross-modal retrieval in real-time can enables users to use LLMs that can reason over their enterprise multimodal data. This talk will revolve around how we can scale the usage of multimodal embedding and generative models in production. Tech Talk: Codeless Generative AI Pipelines Speaker: Timothy Spann (Cloudera LinkedIn) Abstract: Join us for an insightful talk on leveraging the power of real-time streaming tools, specifically Apache NiFi, to revolutionize GenAI data engineering. In this session, we’ll explore how the integration of Apache NiFi can automate the entire process of prompt building, making it a seamless and efficient task. Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 20,000+ local or 300K+ developers worldwide. Venue: Microsoft NYC - Times Square, 11 Times Square, New York, NY 10036 Room Name: Central Park West 6501 Community on Slack/Discord - Event chat: chat and connect with speakers and attendees - Sharing blogs, events, job openings, projects collaborations Join Slack (search and join the #newyork channel) | Join Discord

2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines

Timothy Spann

DBA Fundamentals Group: Continuous SQL with Kafka and Flink 20-Feb-2024 In this talk, I will walk through how someone can set up and run continuous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas, and publishing data. We will then cover consuming Kafka data, joining Kafka topics, and inserting new events into Kafka topics as they arrive. This basic overview will show hands-on techniques, tips, and examples of how to do this. Tim Spann Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.

DBA Fundamentals Group: Continuous SQL with Kafka and Flink

Timothy Spann

NY Open Source Data Meetup Feb 8 2024 Building Real-time Pipelines with FLaNK...

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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

OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines

Timothy Spann

Building Real-time Travel Alerts In this session, we will walk through how to build a complete streaming application to send alerts based on travel advisories from public data. We will also join in other data sources of relevance and push out alerts. We will show you how to build this streaming application with Apache NiFi, Apache Kafka, and Apache Flink and show you when/why/how, and what to build to maximize performance, productivity, and ease of development. Let's get streaming. Apache Flink Apache Kafka Apache NiFi FLaNK Stack Tim Spann Big Data Conference Europe 2023

Building Real-Time Travel Alerts

Timothy Spann

JConWorld: Continuous SQL with Kafka and Flink In this talk, I will walk through how someone can setup and run continous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas and publishing data. We will then cover consuming Kafka data, joining Kafka topics and inserting new events into Kafka topics as they arrive. This basic over view will show hands-on techniques, tips and examples of how to do this. Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html https://www.youtube.com/channel/UCDIDMDfje6jAvNE8DGkJ3_w?view_as=subscriber

JConWorld_ Continuous SQL with Kafka and Flink

Timothy Spann

[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines https://dssconf.pl/en/#agenda-section Integrating LLM with Streaming Data Pipelines Timothy Spann, Principal Developer Advocate, Cloudera APACHE NIFI, APACHE FLINK, APACHE KAFKA, LLM, HUGGINGFACE, REST, STREAMING LESS In this talk and demo I will walk through how to add LLMs to your streaming pipelines by integration through Apache NiFi. https://github.com/tspannhw/FLaNK-watsonx.ai Cloudera streaming llm generative ai slack to slack

[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines

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Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo

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AIDevWorld 23 Apache NiFi 101 Introduction and Best Practices https://sched.co/1RoAO Timothy Spann, Cloudera, Principal Developer Advocate In this talk, we will walk step by step through Apache NiFi from the first load to first application. I will include slides, articles and examples to take away as a Quick Start to utilizing Apache NiFi in your real-time dataflows. I will help you get up and running locally on your laptop, Docker or in CDP Public Cloud. Wednesday November 1, 2023 12:00pm - 12:25pm PDT VIRTUAL AI DevWorld -- Main Stage https://app.hopin.com/events/api-world-2023-ai-devworld/stages Retail & E-Commerce AI (Industry AI Conference) Session Type OPEN TALK Track or Conference Retail & E-Commerce AI (Industry AI Conference), Industry AI Conference, VIRTUAL, Tensorflow & PyTorch & Open Source Frameworks (AI/ML Engineering Conference), AI/ML Engineering Conference, AI DevWorld In-Person/Virtual Virtual, Virtual Exclusive apache nifi Timothy Spann Cloudera Principal Developer Advocate for Data in Motion Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. cloudera dataflow

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In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.

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Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance

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In an era where artificial intelligence (AI) stands at the forefront of business innovation, Information Architecture (IA) is at the core of functionality. See “There’s No AI Without IA” – (from 2016 but even more relevant today) Understanding and leveraging how Information Architecture (IA) supports AI synergies between knowledge engineering and prompt engineering is critical for senior leaders looking to successfully deploy AI for internal and externally facing knowledge processes. This webinar be a high-level overview of the methodologies that can elevate AI-driven knowledge processes supporting both employees and customers. Core Insights Include: Strategic Knowledge Engineering: Delve into how structuring AI's knowledge base is required to prevent hallucinations, enable contextual retrieval of accurate information. This will include discussion of gold standard libraries of use cases support testing various LLMs and structures and configurations of knowledge base. Precision in Prompt Engineering: Learn the art of crafting prompts that direct AI to deliver targeted, relevant responses, thereby optimizing customer experiences and business outcomes. Unified Approach for Enhanced AI Performance: Explore the intersection of knowledge and prompt engineering to develop AI systems that are not only more responsive but also aligned with overarching business strategies. Guiding Principles for Implementation: Equip yourself with best practices, ethical guidelines, and strategic considerations for embedding these technologies into your business ecosystem effectively. This webinar is designed to empower business and technology leaders with the knowledge to harness the full potential of AI, ensuring their organizations not only keep pace with digital transformation but lead the charge. Join us to map a roadmap to fully leverage Information Architecture (IA) and AI chart a course towards a future where AI is a key pillar of strategic innovation and business success.

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Real time stock processing with apache nifi, apache flink and apache kafka

1. Real-Time Stock Processing With Apache NiFi, Apache Flink and Apache Kafka Timothy Spann, Principal DataFlow Field Engineer @ Pierre Villard, Senior Product Manager @

2. Who? Tim Spann @PaasDev // Blog: www.datainmotion.dev Principal DataFlow Field Engineer. Princeton Future of Data Meetup. https://github.com/tspannhw/EverythingApacheNiFi https://community.cloudera.com/t5/Community-Articles/Real-Time-Stock-Processing-With-A pache-NiFi-and-Apache-Kafka/ta-p/249221 Pierre Villard Twitter & Github - @pvillard31 // Blog: www.pierrevillard.com Committer and PMC member for Apache NiFi (in the community since 2015) Senior Product Manager at Cloudera for products around Apache NiFi, NiFi Registry and MiNiFi Previously at Google & Hortonworks

3. What? This talk is about ingesting real-time data from many sources and build a dashboard on top it to track in real time what our stocks are. This use case is a good example to show the combination of some of the best Apache solutions for streaming applications.

4. NiFi, Kafka and Flink in a few numbers - Apache NiFi (version 1.12.x) - created and open sourced by the NSA - initial release in 2006 350+ contributors, 1200+ people in Slack, 3.1M+ docker pulls Many sub-projects: NiFi, MiNiFi Java, MiNiFi C++, NiFi Registry, etc - Apache Kafka (version 2.6.x) - created and open sourced by LinkedIn - initial release in 2011 700+ contributors - Apache Flink (version 1.11.x) - initial release in 2011 750+ contributors, 2nd top repository by number of commits, top active project on mailing lists

5. What is NiFi used for?

6. Analyze Streaming OLAP Analytics & Time Series Store Powered by Druid & Kudu Buffer Apache Kafka Topics Ingest Gateway Powered by Kafka Distribute Apache NiFi Data Flow Apps Powered by NiFi Buffer Apache Kafka Syndicate topics Syndicate Services Powered by Kafka Collect Syndicate topics Syndicate Services Powered by Kafka Replication / Data Deployment Analyze Streaming Analytics Apps Stream Processing Powered by Flink Streaming Reference Architecture Data Collection at the Edge Apache NiFi / MiNiFi - sensors, IoT - databases - ﬁle systems - app sidecar - live streams - MQ - logs - network Anything… you name it!

7. Where? CDP services are optimized for the elastic compute & ‘always-on’ storage services provided by any cloud provider Web service hosted and managed by Cloudera Hosted in the your cloud environment, but managed by the CDP Management Console Shared Data Experience (SDX) technologies form a secure and governed data lake backed by object storage (S3, ADLS, GCS) Flow Management Streams Messaging Streaming Analytics

8. How? This use case architecture Stock Data Logs Errors Aggregates Other data SQL Analytics

9. Demonstration Let’s see all of this in action…

10. Thanks! Questions? Timothy Spann, Principal DataFlow Field Engineer @ Pierre Villard, Senior Product Manager @

Real time stock processing with apache nifi, apache flink and apache kafka

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Real time stock processing with apache nifi, apache flink and apache kafka