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Machine Learning with Tensorflow and Apache Kafka

According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.

In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.

Kafka and Tensorflow can be used together to build comprehensive machine learning solutions on streaming data. Unfortunately, both can become black boxes and it can be difficult to understand what's happening as pipelines are running. In this talk we'll explore how StreamSets can be used to build robust machine learning pipelines with Kafka.

In this session you'll learn:
-How to easily build pipelines with Tensorflow and Kafka
-Visualizing data in Tensorflow pipelines
-Creating reusable code fragments for standardizing pipeline best practices
Recorded Jan 8 2019 26 mins
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Presented by
Clarke Patterson - Head of Product Marketing - StreamSets
Presentation preview: Machine Learning with Tensorflow and Apache Kafka

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  • Machine Learning with Tensorflow and Apache Kafka Sep 19 2019 5:00 pm UTC 25 mins
    Clarke Patterson - Head of Product Marketing - StreamSets
    According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.

    In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.

    Kafka and Tensorflow can be used together to build comprehensive machine learning solutions on streaming data. Unfortunately, both can become black boxes and it can be difficult to understand what's happening as pipelines are running. In this talk we'll explore how StreamSets can be used to build robust machine learning pipelines with Kafka.

    In this session you'll learn:
    -How to easily build pipelines with Tensorflow and Kafka
    -Visualizing data in Tensorflow pipelines
    -Creating reusable code fragments for standardizing pipeline best practices
  • Monitoring and Protecting Data in Apache Kafka Sep 17 2019 5:00 pm UTC 45 mins
    Clarke Patterson - Head of Product Marketing - StreamSets
    According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.

    In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.

    Kafka and Tensorflow can be used together to build comprehensive machine learning solutions on streaming data. Unfortunately, both can become black boxes and it can be difficult to understand what's happening as pipelines are running. In this talk we'll explore how StreamSets can be used to build robust machine learning pipelines with Kafka.

    In this session you'll learn:
    -How to easily build pipelines with Tensorflow and Kafka
    -Visualizing data in Tensorflow pipelines
    -Creating reusable code fragments for standardizing pipeline best practices
  • Stream into Kafka Series: Dead Easy Kafka Pipeline Development Sep 12 2019 5:00 pm UTC 53 mins
    Clarke Patterson, Head of Product Marketing @ StreamSets & Pat Patterson, Technical Director @ StreamSets
    According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.

    In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.

    Getting started with Kafka can be harder than it needs to be. Building a cluster is one thing, but ingesting data into that cluster can require a lot of experience and often a lot of rework. During this session we'll demystify the process of creating pipelines for Apache Kafka and show how you can create Kafka pipelines in minutes, not hours or days.

    In this session you'll learn:
    -Designing any-to-any Kafka pipelines in minutes
    -Snapshotting and monitoring data in Kafka
    -Editing pipelines quickly and easily without major disruption
  • 5 Ways to Scale Kafka with StreamSets Sep 10 2019 5:00 pm UTC 30 mins
    Clarke Patterson, Head of Product Marketing @ StreamSets & Bryan Duxbury, Chief Technologist @ StreamSets
    According to the 2018 Apache Kafka Report, 94% of organizations plan to deploy new applications or systems using Kafka this year. At the same time, 77% of those same organizations say that staffing Kafka projects has been somewhat or extremely challenging.

    In this multi-part webinar series, StreamSets will take learnings from our customers and share practical tips for making headway with Kafka. Each session will discuss common challenges and provide step-by-step details for how to avoid them. By the end of the series you'll have many more tools at your disposal for ensuring your Kafka project is a success.

    When it comes to scaling out Apache Kafka, there's often a trade off between complexity, performance and cost. In this session, we'll look at five different ways to scale up to handle massive message throughput with Kafka and StreamSets

    In this session you'll learn:
    -Scaling pipelines vertically and horizontally
    -Getting scale by streaming in a cluster
    -Leveraging Kubernetes to elastic scaling
  • How Cox Automotive Democratized Data with a Self-Service Data Exchange Aug 29 2019 5:00 pm UTC 62 mins
    Nathan Swetye - Sr. Manager of Platform Engineering - Cox Automotive
    Cox Automotive comprises more than 25 companies dealing with different aspects of the car ownership lifecycle, with data as the common language they all share. The challenge for Cox Automotive was to create an efficient engine for the timely and trustworthy ingest of data capability for an unknown but large number of data assets from practically any source. Working with StreamSets, they are populating a data lake to democratize data, allowing analysts easy access to data from other companies and producing new data assets unique to the industry.

    In this webinar, Nathan Swetye from Cox Automotive will discuss how they:

    -Took on the challenge of ingesting data at enterprise scale and the initial efficiency and data consistency struggles they faced.
    -Created a self-service data exchange for their companies based on an architecture that decoupled data acquisition from ingestion.
    -Reduced data availability from weeks to hours and developer time by 90%.
  • Recipes for Success How to Build Continuous Ingest Pipelines Aug 27 2019 5:00 pm UTC 62 mins
    Arvind Prabhakar - Co-Founder and CTO - StreamSets
    Modern data infrastructures are fed by vast volumes of data, streamed from an ever-changing variety of sources. Standard practice has been to store the data as ingested and force data cleaning onto each consuming application. This approach saddles data scientists and analysts with substantial work, creates delays getting to insights and makes real-time or near-time analysis practically impossible.
  • Ultralight Data Movement for IoT with SDC Edge Aug 22 2019 5:00 pm UTC 34 mins
    Guglielmo Iozzia - Big Data Lead - Optum | Pat Patterson - Technical Director - StreamSets
    Edge computing and the Internet of Things bring great promise, but often just getting data from the edge requires moving mountains.

    During this webinar, we will discuss:

    -How to make edge data ingestion and analytics easier using StreamSets Data Collector edge, an ultralight, platform independent and small-footprint Open Source solution for streaming data from resource-constrained sensors and personal devices (like medical equipment or smartphones) to Apache Kafka, Amazon Kinesis and many others.

    -We'll provide an overview of the SDC Edge main features, supported protocols and available processors for data transformation, insights on how it solves some challenges of traditional approaches to data ingestion, pipeline design basics, a walk-through some practical applications (Android devices and Raspberry Pi) and its integration with other technologies such as StreamSets Data Collector, Apache Kafka, and more.
  • Modern Streaming Data Stack with Kinetica & StreamSets Aug 20 2019 5:00 pm UTC 60 mins
    Matt Hawkins - Principal Solutions Architect - Kinetica | Mark Brooks - Solutions Architect - StreamSets
    Enterprises are now faced with wrangling massive volumes of complex, streaming data from a variety of different sources, a new paradigm known as extreme data. However, the traditional data integration model that’s based on structured batch data and stable data movement patterns makes it difficult to analyze extreme data in real-time.

    Join Matt Hawkins, Principal Solutions Architect at Kinetica and Mark Brooks, Solution Engineer at StreamSets as they share how innovative organizations are modernizing their data stacks with StreamSets and Kinetica to enable faster data movement and analysis.

    During this webinar, we will discuss:

    -The modern data architecture required for dealing with extreme data
    -How StreamSets enables continuous data movement and transformation across the enterprise
    -How Kinetica harnesses the power of GPUs to accelerate analytics on streaming data
    -A live demo of StreamSets and Kinetica connector to enable high speed data ingestion, queries and data visualization
  • Modernize Cybersecurity Threat Detection Aug 15 2019 5:00 pm UTC 55 mins
    Nathan Necaise - VP of Data Sciences Emerging Services - Optiv
    The convergence of streaming data platforms with cyber security solutions presents real opportunity for combating and predicting future threats. Join StreamSets and Optiv as we discuss common use cases and architectural patterns used by leading Fortune 500 organizations to modernize their cyber architecture.

    During this webinar, we will discuss:

    -Common challenges facing today’s SIEM’s and how to effectively augment them with streaming data platforms
    -Show customer examples and demonstrate how they are leading to transformative effects
    -How to optimize security architectures that use technologies like Splunk using StreamSets
  • Operationalize Data Movement to Supercharge Your Architecture Aug 13 2019 5:00 pm UTC 59 mins
    Julian Ereth - Research Analyst - Eckerson Group | Arvind Prabhakar - Co-Founder & CTO - StreamSets
    DataOps borrows concepts from agile development to streamline the process of building, deploying and operating dataflow pipelines at scale. Putting DataOps into action requires not only the right technology, but more broadly a thoughtful approach to align the people and the process behind such an initiative.

    Eckerson Group research analyst Julian Ereth join StreamSets' Co-Founder and CTO, Arvind Prabhakar to explore the emerging trend of DataOps.

    During this webinar, we will discuss:

    -Principles and benefits of DataOps
    -Common DataOps use cases
    -Practical guidelines for putting DataOps into action
    -How StreamSets can help on a DataOps journey
  • If Cloud is the Problem DataOps is the Solution Aug 8 2019 5:00 pm UTC 44 mins
    Kirit Basu - VP of Product - StreamSets
    According to research firm Gartner, at least 75% of large and global organizations will implement a multicloud-capable hybrid integration platform by 2021. Join StreamSets Head of Product Management, Kirit Basu, and Head of Product Marketing, Clarke Patterson as they discuss how StreamSets customers are taking a DataOps approach to hybrid-cloud integration.

    We explore how Fortune 500 customers are using StreamSets to streamline Apache Kafka and Data Lake projects using principles adopted from DevOps.

    During this webinar, we will discuss:
    -Pitfalls to avoid for any hybrid-cloud project
    -Key requirements to ensure continuous movement of data across any cloud
    -How StreamSets customers are using the platform to drive real value from DataOps
  • The Evolution of DataOps at GSK (GlaxoSmithKline) Aug 6 2019 5:00 pm UTC 58 mins
    Chuck Smith - VP of Data Strategy - GlaxoSmithKline | Bryan Duxbury - Chief Technologist - StreamSets
    GlaxoSmithKline is a pharmaceutical company that has pioneered a transformation of its R&D data and analytics infrastructure. Creating a new drug can take anywhere from 8 years to 20 years for a pharmaceutical company and GSK aimed to shorten that development time by giving over 8,000 scientists access to trial data. GSK is focused on bringing siloed data together into a primary data and information platform where users across the enterprise can consume all the data in different ways.

    In order to deliver these capabilities GSK has set up a Center of Excellence (COE) around data delivery and dataops. The team is responsible for dynamically scaling its data flows to meet the demands of new data sources. They have evolved the data practices over time to automate aspects of data acquisition and delivery utilizing bot-driven pipelines.

    VP of Strategy at GSK Chuck Smith joins us for a look at the solution and talks about the future.

    During this webinar, we will discuss:

    -Building a DataOps practice
    -High-level solution and architecture overview
    -Best practices for automation
  • Hadoop Creator Doug Cutting: How to Operationalize Machine Learning and Advanced Aug 1 2019 5:00 pm UTC 56 mins
    Doug Cutting - Hadoop Creator & Chief Architect - Cloudera | Arvind Prabhakar - Co-Founder & CTO - StreamSets
    When streaming data meets machine learning and advanced analytics, the innovation possibilities can be endless. Operationalization of data movement in a hybrid cloud architecture is key to making your technology investments deliver on their promises. Without it comes frustrated developers, failed projects and technology disillusionment.

    Join Doug Cutting, Apache Hadoop creator and Chief Architect at Cloudera, and Arvind Prabhakar, co-founder and CTO at StreamSets as they discuss how to use DataOps to avoid common pitfalls associated with adopting modern analytics platforms.
  • DataOps for Digital Transformation Jul 25 2019 5:00 pm UTC 57 mins
    Sheryl Kingstone - VP of Customer Experience & Commerce - 451 Research | Sean Anderson - Dir. of Product Marketing - StreamSe
    Every organization wants to know more about its customers. More data can lead to a more comprehensive Customer 360 view—but only if all that data can be captured, managed, and kept safe from unauthorized use.

    Companies today are forced to piece together partial views of customer behavior, managing to the limitations of their systems and not to their analytic goals. When data lives in silos it can create gaps in analytic outputs and poor visibility for business intelligence. StreamSets built a DataOps platform to help manage complex data flows into analytics environments with pre-built connections for popular customer data systems. Join 451’s research director Sheryl Kingstone to discuss how DataOps is fueling digital transformation.

    In this webinar you will learn...

    -How to build Customer 360 in a scalable way to capture customer data—across all an enterprise’s systems, securely and in real-time.
    -How to deliver a unified, complete picture of the organization’s interactions with its customers.
    -Challenges that make it difficult to adequately protect customer data, including personally identifiable information (PII).
  • Making Apache Kafka Dead Easy With StreamSets Jul 23 2019 5:00 pm UTC 58 mins
    Clarke Patterson - Head of Product Marketing
    Apache Kafka has become a popular choice for stream processing due to its throughput, availability guarantees and open source distribution. However, it also comes with complexity, and many enterprises struggle to get productive quickly as they attempt to connect Kafka to a diversity of data sources and destination platforms.

    In this webinar, expert Clarke Patterson will discuss and demonstrate best practices that will help make your Kafka deployment successful, including:

    -How to design any-to-any batch and streaming pipelines into and out of Kafka.
    -How to monitor end-to-end dataflows through Kafka.
    -How to operate continuous data movement with agility as data sources and architecture evolve.
  • CDC for Snowflake Recorded: Jul 18 2019 58 mins
    Sean Anderson - Director of Product Marketing at StreamSets | Dash Desai - Technology Evangelist at StreamSets
    Your cloud database is helpful only if it is real-time, which means looking beyond migration and batch uploads. Whether synchronous and asynchronous syncing, we explore how users can design robust change/data/capture (CDC) jobs between Snowflake and on-premise data warehouses. We will configure a CDC pipeline with prebuilt origins for popular data warehouses and destinations to the Snowflake service. We will show an initial load with full table creation and a schedule to initiate incremental data captures.

    In this webinar we will:
    -Show how to configure a CDC pipeline with prebuilt origins for popular data warehouses and destinations to the Snowflake service.
    -Show an initial load with full table creation and a schedule to initiate incremental data captures.
  • Bulk Load Amazon Redshift from Relational Databases with StreamSets Recorded: Jul 16 2019 61 mins
    Sean Anderson - Director of Product Marketing at StreamSets | Pat Patterson - Director of Evangelism at StreamSets
    You have options when bulk loading data into RedShift from relational database (RDBMS) sources. These options include manual processes or using one of the numerous hosted as-a-service options.

    But, if you have broader requirements than simply importing, you need another option. Your company may have requirements such as adhering to enterprise security policies which do not allow opening of firewalls. They might have a need to operationalize and automate data pipelines, masking, encryption or removal of sensitive information such as PII before landing in RedShift. In this case, your best option to use is StreamSets.

    In this webinar you will learn about the StreamSets and the Amazon Redshift Service which will include:
    -An overview of cloud managed database services
    -How StreamSets helps optimize data movement to your cloud data warehouse
    -How to setup the connection between your source and Amazon Redshift
    -How to correctly setup your data collectors
    -Thoughts and best practices
  • DataOps: Practical Advice for Your Journey Recorded: Jul 11 2019 51 mins
    John Schmidt - President - Proact Digital Transformation
    DataOps is the current hot topic in data management, as companies work hard to figure out how to make use of the real-time, unstructured and streaming data in modern analytics platforms that support data science and machine learning. They realize that traditional batch-oriented data integration has reached its natural limits but are not clear how to augment or replace it in order to turn their use of data into an always-on, quality-controlled operation.

    Join industry expert John Schmidt, author of “Lean Integration” and “Integration Competency Center” as he helps you decode the new DataOps trend. He will focus on:
    -What DataOps is and why DataOps is a vital paradigm shift for enterprises who want to be “data competitive”.
    -The long-standing but increasingly critical enterprises data challenges that DataOps resolves.
    -The specific practices that define DataOps and how to take the first steps to implementing them.
  • Avoid Data Drift with for Cloud Data Warehouse Recorded: Jul 9 2019 51 mins
    Sean Anderson - Director of Product Marketing at StreamSets | Dash Desai - Technology Evangelist at StreamSets
    Cloud Data Warehouses are on the rise. As companies aim to make analytics pervasive across their organization, cloud data warehouses and data marts became a logical solution for delivering a familiar analytics experience but without the constraints of managing large DW infrastructure. Cloud Data Warehouses help reduce management and infrastructure costs, offload maintenance and uptime responsibilities, and allow users to simply load data and run queries instead of managing databases.

    However, migrating and streaming data to these new cloud managed services remains a freshman effort with many tools offering only simple ingestion functionality and limited data destinations. StreamSets has built an advanced integration with popular cloud Sw solutions like Snowflake, one of the world’s most popular cloud data warehouses. This level of integration provides fast synchronous and asynchronous ingest, multi-table uploads, and data drift compensation. StreamSets Control Hub helps users then manage a variety of pipelines, on-premise; across public clouds and cloud services.

    In this webinar you will...
    -Take a look at common usage patterns for Cloud Data Warehousing.
    -Understand the core functionality of the Snowflake connector.
    -Get information on the installation and operation of the new tool.
  • DataOps Summit 2019 Recorded: Jun 11 2019 2 mins
    StreamSets
    http://dataopssummit-sf.com

    StreamSets is proud to be hosting the first annual DataOps Summit in San Francisco, California at the Hilton San Francisco Financial District on September 3rd-5th. The summit will feature a full day of data operations training and two days of comprehensive content featuring major brands, high-scale use cases, ecosystem partners, and community heros. Keynote discussions will feature data luminaries from companies like Humana, Snowflake, GSK and Ericsson explaining how they built a discipline of DataOps and a culture that reaps the benefits. Take advantage of the opportunity to uplevel your skillset, hear from thought leaders and network with your peers.
Continuous Dataflows that Unleash Pervasive Intelligence
The StreamSets DataOps platform enables companies to build, execute, operate and protect batch and streaming dataflows. It is powered by StreamSets Data Collector, award-winning open source software with approximately 2,000,000 downloads to date from thousands of companies. The commercial StreamSets Control Hub is the platform's cloud-native control plane through which enterprises design, monitor and manage complex data movement that is executed by multiple Data Collectors. Unique Intelligent Pipeline technology automatically inspects the data in motion, detecting unexpected changes, errors and sensitive data in-stream.

Global 2000 customers use StreamSets for data lake ingestion, Apache Kafka enablement, cybersecurity, IoT, customer 360, GDPR compliance and more. In 2017, the company tripled its customer count and quadrupled revenues.

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  • Live at: Jan 8 2019 6:00 pm
  • Presented by: Clarke Patterson - Head of Product Marketing - StreamSets
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