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Here’s your chance to get hands-on with Splunk for the first time! Bring your modern Mac, Windows, or Linux laptop and we’ll go through a simple install of Splunk. Then, we’ll load some sample data, and see Splunk in action – we’ll cover searching, pivot, reporting, alerting, and dashboard creation. At the end of this session you’ll have a hands-on understanding of the pieces that make up the Splunk Platform, how it works, and how it fits in the landscape of Big Data. You’ll experience practical examples that differentiate Splunk while demonstrating how to gain quick time to value.

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At Cricket Communications, Splunk started as a way to correlate all of our data into one view to help our operations team keep processes humming. Then we gave secured access to our developers, now they’re addicted. In fact, Splunk is critical in helping us speedup deployment of new systems (like our recent multi-million dollar billing system implementation). Learn how we use Splunk to display key metrics for the business, track overall system health, track transactions, optimize license usage, and support capacity planning.

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This Splunk tutorial will help you understand what is Splunk, benefits of using Splunk, Splunk vs ELK vs Sumo Logic, Splunk architecture - Splunk Forwarder, Indexer and Search Head with the help of Dominos use-case, Splunk careers & jobs. Check the Splunk tutorial video here: https://www.youtube.com/watch?v=Ekai8Ln11Iw. You can also read the tutorial blog here: https://goo.gl/eoZFWV. The slides consist of following topics: Need for Data Management & Analytics What is Splunk and Why Splunk? Splunk vs ELK vs Sumo Logic Splunk Use Case: Domino's How Splunk Works? Splunk Architecture Heavy Forwarders Splunk Architecture Diagram Splunk Jobs & Careers

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Your IT department supports critical business functions, processes and products. You're most effective when your technology initiatives are closely aligned and measured with specific business objectives. This session covers best practices and techniques for designing and building an effective service model, using the domain knowledge of your experts and capturing and reporting on key metrics that everyone can understand. We will design a sample service model and map them to performance indicators to track operational and business objectives. We will also show you how to make Splunk service-ware with Splunk IT Service Intelligence (ITSI).

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As organizations increase their adoption of AWS cost and control, cost management becomes a fundamental part in a successful journey in adopting the cloud. AWS provides organizations with deep functionality, flexible purchasing options and a growing portfolio of tools to manage and optimize their costs. In this session, we will cover the fundamentals on how to understand the principles of cost optimization, how to leverage best practices, and how to track, monitor and control spend. Learning Objectives: • Cost management, cost optimization, lower TCO and increase business value.

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Serverless architectures involve building applications and services with infrastructure resources that require zero administration. When building and operating web applications, you have to provision and manage servers to run your application code, install and operate distributed databases, and scale servers to handle API requests. AWS provides you a stack of scalable, fully-managed services that eliminates these operational complexities. In this session, we will briefly review how you can build web applications using a serverless architecture. We will run through a demo of setting up a simple serverless blogging web application that allows user authentication and the ability to create posts and comments. We will dive into the details of how AWS Lambda, Amazon API Gateway, Amazon S3, Amazon DynamoDB, and Amazon Cognito are used in each component of the web application. Learning Objectives: • Review components and benefit of serverless architectures • Learn how to build a serverless blogging web application

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Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.

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With an ever-increasing set of technologies to process big data, organizations often struggle to understand how to build scalable and cost-effective big data applications. In this webinar, we will simplify big data processing as a pipeline comprising various stages; and then show you how to choose the right technology for each stage based on criteria such as data structure, design patterns, and best practices. Learning Objectives: Understand key AWS Big Data services including S3, Amazon EMR, Kinesis, and Redshift Learn architectural patterns for Big Data Hear best practices for building Big Data applications on AWS Who Should Attend: Architects, developers and data scientists who are looking to start a Big Data initiative

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El Cloud Computing es una nueva manera de ofrecer o utilizar servicios de tecnologías de la información (TI), en la que básicamente utilizamos servicios de aplicaciones informáticas en la nube, servicios de plataformas informáticas en la nube o servicios de infraestructuras informáticas en la nube a través de un acceso web (utilizando internet) los cuales son suministrados por proveedores de servicios cloud.

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Large Web Applications are by nature resource intensive, expensive to customize, and difficult to manage at scale. What if we can change this perception and help developers architect a web application that is high performance and low cost, high security and low maintenance? This talk will focus on 3 key topics: 1) serverless infrastructure, 2) microservices architecture and 3) hands-on demos. We will describe a serverless solution and propose a scalable architecture that will help Generator Hub community to adopt cloud-native approach without huge efforts or expensive resources allocation.

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Watch the live presentation on-demand now: https://goo.gl/QanW35 Organizations are fast adapting cloud to lower the IT costs, and increase agility. Watch this Denodo DataFest 2017 session to discover: • How Logitech migrated their on-premise data warehouse and big data systems to the cloud and minimizing costs and immensely improved their time-to-market. • The four main challenges Logitech faced when moving their data to the cloud. • The benefits of adding a data virtualization layer to your data architecure.

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At Sams Club we have a long history of using Apache Spark and Hadoop. Projects from all parts of the company use Apache Spark, from fraud detection to product recommendations. Because of the scale of our business with billions of transactions and trillions of events it is often essential to use big data technologies. Until recently all of this work has run on several large on-premise Hadoop clusters. As part of our transition to public cloud we needed to build out an enterprise scale data platform. Azure Databricks is a key component of this platform giving our data scientist, engineers, and business users the ability to easily work with the companies data. We will discuss our architecture considerations that lead to using multiple Databricks workspaces and external Azure blob storage. We will also discuss how we move massive amounts of data to Azure on a daily basis with Airflow. Further we will discuss the self-service tools that we created to help users get their data to Azure and for us to manage the platform. Finally we will discuss our security considerations and how that played out in our architecture. Authors: Andrew Ray, Craig Covey

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We know Splunk helps us solve problems at the IT operations level. But more and more Splunk helps us to make machine-generated data relevant for non-technical business users. With Splunk you can ask any question at any time, without planning questions or structures in advance. And once you’ve built initial dashboards, you can empower business users to access them so they can get instant, accurate data on their own. Join us for this session where we’ll review how to build custom dashboards that provide both up-to-the-minute and long-term trending analysis that business users need to make the decisions that impact revenue.

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IBM i systems handle some of the most mission-critical transactions in your organization. In the past, they operated in relative isolation, but today they’re connected to other systems across your IT infrastructure to support mission-critical business services. They’re also connected to networks or the Internet, making them vulnerable to cybersecurity threats and incidents. It’s critical that the operational and security data generated by your IBM i systems is visible in your Splunk platform for enterprise-wide analysis, but it’s difficult to capture it and make it usable for reporting. View this webinar on-demand to learn how organizations like yours are using Ironstream to forward IBM i log data to Splunk, to gain insight into operations, security and service delivery for the ultimate success of their business. We will cover: • Key use cases for IBM i log analysis • Challenges of using IBM i data in Splunk • How Ironstream and Splunk deliver key insight into IBM i operational health and security in the broader context of your enterprise

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Valuable mainframe data is often the missing piece in a holistic infrastructure view within Splunk. But if you're not a mainframe expert, knowing which data sources, fields and calculations are needed to get results within Splunk can be a challenge. Even those with mainframe knowledge can sometimes struggle. With Syncsort Ironstream® you can easily capture the elements you need in real-time – and Ironstream's new Mainframe Data Model makes it easier than ever to work with complex mainframe metrics in Splunk. View this webinar on-demand to learn more about this new feature, as well as how to: • See categorized mainframe metrics in easily understood terms • Get results faster – no need to research data sources, fields and calculations • Broaden access to more team members – without the need for deep mainframe knowledge • Use built-in Splunk tooling to get up and running quickly • Realize valuable ROI sooner and eliminate the mainframe blind spot

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The Briefing Room with Mark Madsen and WebAction Live Webcast Feb. 10, 2015 Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=fa83c6283de99dfb6f38b9d7199cb452 In our increasingly interconnected world, the windows of opportunity for meaningful action are shrinking. Where hours once sufficed, minutes are now the norm. For some transactions, seconds make all the difference, even sub-seconds. Meeting these demands requires a new approach to information architecture, one that embraces the many innovations that are fundamentally changing the data-driven economy. Register for this episode of The Briefing Room to hear veteran Analyst Mark Madsen of Third Nature as he explains how a confluence of advances are changing the nature of data management. He'll be briefed by Sami Akbay of WebAction, who will showcase his company's real-time data platform, designed from the ground up to meet the challenges of leveraging Big Data in concert with all manner of operational enterprise systems. Visit InsideAnalysis.com for more information.

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While developer tools and a typical SDLC are important to us all, it is not uncommon for field sales engineering organizations that make customer-facing product demos to have such a coordinated process. We will show how using Docker (and a CI pipeline) we modernized a field sales engineering "Demo Center", made it more efficient, flexible and a capable of handling lots of new use cases.has become truly enabling service. We will show you how to go from a very manual devops process, to a Docker Service based product demonstration center using features of Docker 1.12 (Swarm Mode) and using Splunk for Analytics, how truly enabling it has become.

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