Teradata Connectors for Hadoop enable high-volume data movement between Teradata and Hadoop platforms. LinkedIn conducted a proof-of-concept using the connectors for use cases like copying clickstream data from Hadoop to Teradata for analytics and publishing dimension tables from Teradata to Hadoop for machine learning. The connectors help address challenges of scalability and tight processing windows for these large-scale data transfers.
Big Data: Architecture and Performance Considerations in Logical Data LakesDenodo
This presentation explains in detail what a Data Lake Architecture looks like, how data virtualization fits into the Logical Data Lake, and goes over some performance tips. Also it includes an example demonstrating this model's performance.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/9Jwfu6.
Hybrid Data Warehouse Hadoop ImplementationsDavid Portnoy
The document discusses the evolving relationship between data warehouse (DW) and Hadoop implementations. It notes that DW vendors are incorporating Hadoop capabilities while the Hadoop ecosystem is growing to include more DW-like functions. Major DW vendors will likely continue playing a key role by acquiring successful new entrants or incorporating their technologies. The optimal approach involves a hybrid model that leverages the strengths of DWs and Hadoop, with queries determining where data resides and processing occurs. SQL-on-Hadoop architectures aim to bridge the two worlds by bringing SQL and DW tools to Hadoop.
Data Integration for Big Data (OOW 2016, Co-Presented With Oracle)Rittman Analytics
Oracle Data Integration Platform is a cornerstone for big data solutions that provides five core capabilities: business continuity, data movement, data transformation, data governance, and streaming data handling. It includes eight core products that can operate in the cloud or on-premise, and is considered the most innovative in areas like real-time/streaming integration and extract-load-transform capabilities with big data technologies. The platform offers a comprehensive architecture covering key areas like data ingestion, preparation, streaming integration, parallel connectivity, and governance.
IlOUG Tech Days 2016 - Unlock the Value in your Data Reservoir using Oracle B...Mark Rittman
Mark Rittman from Rittman Mead presented on Oracle Big Data Discovery. He discussed how many organizations are running big data initiatives involving loading large amounts of raw data into data lakes for analysis. Oracle Big Data Discovery provides a visual interface for exploring, analyzing, and transforming this raw data. It allows users to understand relationships in the data, perform enrichments, and prepare the data for use in tools like Oracle Business Intelligence.
The Modern Data Architecture for Advanced Business Intelligence with Hortonwo...Hortonworks
The document provides an overview of a webinar presented by Anurag Tandon and John Kreisa of Hortonworks and MicroStrategy respectively. It discusses the drivers for adopting a modern data architecture including the growth of new types of data and the need for efficiency. It outlines how Apache Hadoop can power a modern data architecture by providing scalable storage and processing. Key requirements for Hadoop adoption in the enterprise are also reviewed like the need for integration, interoperability, essential services, and leveraging existing skills. MicroStrategy's role in enabling analytics on big data and across all data sources is also summarized.
This document discusses strategies for filling a data lake by improving the process of data onboarding. It advocates using a template-based approach to streamline data ingestion from various sources and reduce dependence on hardcoded procedures. The key aspects are managing ELT templates and metadata through automated metadata extraction. This allows generating integration jobs dynamically based on metadata passed at runtime, providing flexibility to handle different source data with one template. It emphasizes reducing the risks associated with large data onboarding projects by maintaining a standardized and organized data lake.
Near real-time, big data analytics is a reality via a new data pattern that avoids the latency and overhead of legacy ETL–the 3 T’s of Hadoop: Transfer, Transform, and Translate. Transfer: Once a Hadoop infrastructure is in place, a mandate is needed to immediately and continuously transfer all enterprise data, from external and internal sources and through different existing systems, into Hadoop. Previously, enterprise data was isolated, disconnected and monolithically segmented. Through this T, various source data are consolidated and centralized in Hadoop almost as they are generated in near real-time. Transform: Most of the enterprise data, when flowing into Hadoop, is transactional in nature. Analytics requires data be transformed from record-based OLTP form to column-based OLAP. This T is not the same T in ETL as we need to retain the granularity in the data feeds. The key is to transform in-place within Hadoop, without further data movement from Hadoop to other legacy systems. Translate: We pre-compute or provide on-the-fly views of analytical data, exposed for consumption. We facilitate analysis and reporting, for both scheduled and ad hoc needs, to be interactive with the data for analysts and end users, integrated in and on top of Hadoop.
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
More and more organizations are moving their ETL workloads to a Hadoop based ELT grid architecture. Hadoop`s inherit capabilities, especially it`s ability to do late binding addresses some of the key challenges with traditional ETL platforms. In this presentation, attendees will learn the key factors, considerations and lessons around ETL for Hadoop. Areas such as pros and cons for different extract and load strategies, best ways to batch data, buffering and compression considerations, leveraging HCatalog, data transformation, integration with existing data transformations, advantages of different ways of exchanging data and leveraging Hadoop as a data integration layer. This is an extremely popular presentation around ETL and Hadoop.
Hadoop Reporting and Analysis - JaspersoftHortonworks
Hadoop is deployed for a variety of uses, including web analytics, fraud detection, security monitoring, healthcare, environmental analysis, social media monitoring, and other purposes.
Create a Smarter Data Lake with HP Haven and Apache HadoopHortonworks
An organization’s information is spread across multiple repositories, on-premise and in the cloud, with limited ability to correlate information and derive insights. The Smart Content Hub solution from HP and Hortonworks enables a shared content infrastructure that transparently synchronizes information with existing systems and offers an open standards-based platform for deep analysis and data monetization.
- Leverage 100% of your data: Text, images, audio, video, and many more data types can be automatically consumed and enriched using HP Haven (powered by HP IDOL and HP Vertica), making it possible to integrate this valuable content and insights into various line of business applications.
- Democratize and enable multi-dimensional content analysis: - Empower your analysts, business users, and data scientists to search and analyze Hadoop data with ease, using the 100% open source Hortonworks Data Platform.
- Extend the enterprise data warehouse: Synchronize and manage content from content management systems, and crack open the files in whatever format they happen to be in.
- Dramatically reduce complexity with enterprise-ready SQL engine: Tap into the richest analytics that support JOINs, complex data types, and other capabilities only available with HP Vertica SQL on the Hortonworks Data Platform.
Speakers:
- Ajay Singh, Director, Technical Channels, Hortonworks
- Will Gardella, Product Management, HP Big Data
Hortonworks provides an open source Apache Hadoop data platform for managing large volumes of data. It was founded in 2011 and went public in 2014. Hortonworks has over 800 employees across 17 countries and partners with over 1,350 technology companies. Hortonworks' Data Platform is a collection of Apache projects that provides data management, access, governance, integration, operations and security capabilities. It supports batch, interactive and real-time processing on a shared infrastructure using the YARN resource management system.
This document discusses how Apache Hadoop provides a solution for enterprises facing challenges from the massive growth of data. It describes how Hadoop can integrate with existing enterprise data systems like data warehouses to form a modern data architecture. Specifically, Hadoop provides lower costs for data storage, optimization of data warehouse workloads by offloading ETL tasks, and new opportunities for analytics through schema-on-read and multi-use data processing. The document outlines the core capabilities of Hadoop and how it has expanded to meet enterprise requirements for data management, access, governance, integration and security.
Using Hadoop to Offload Data Warehouse Processing and More - Brad AnsersonMapR Technologies
The document discusses using Hadoop to optimize an enterprise data warehouse. It describes offloading some ETL and long-term storage tasks to Hadoop which provides significant cost savings over a traditional data warehouse. The hybrid solution leverages both Hadoop and the data warehouse for optimized querying, presentation and analytics. Examples are provided of real-time and operational applications that can be built using Hadoop technologies.
YARN Ready: Integrating to YARN with Tez Hortonworks
YARN Ready webinar series helps developers integrate their applications to YARN. Tez is one vehicle to do that. We take a deep dive including code review to help you get started.
Data Lake for the Cloud: Extending your Hadoop ImplementationHortonworks
As more applications are created using Apache Hadoop that derive value from the new types of data from sensors/machines, server logs, click-streams, and other sources, the enterprise "Data Lake" forms with Hadoop acting as a shared service. While these Data Lakes are important, a broader life-cycle needs to be considered that spans development, test, production, and archival and that is deployed across a hybrid cloud architecture.
If you have already deployed Hadoop on-premise, this session will also provide an overview of the key scenarios and benefits of joining your on-premise Hadoop implementation with the cloud, by doing backup/archive, dev/test or bursting. Learn how you can get the benefits of an on-premise Hadoop that can seamlessly scale with the power of the cloud.
The document introduces the Teradata Aster Discovery Platform for scalable analytics using analytic algorithms on commodity hardware. It discusses use cases like credit risk analysis, fraud detection, and sentiment analysis. It provides an overview of the discovery process model and instructions for downloading, installing, and using Aster including setting up the Aster Management Console and AsterLens for visualization. It then provides examples of using various Aster analytic functions like k-means clustering, market basket analysis, data unpacking, and nPath analysis for applications in marketing, pricing, and web analytics. It concludes that Aster provides more powerful analytics capabilities than SQL alone for exploring big data.
This document discusses Oracle Data Integration solutions for tapping into big data reservoirs. It begins with an overview of Oracle Data Integration and how it can improve agility, reduce risk and costs. It then discusses Oracle's approach to comprehensive data integration and governance capabilities including real-time data movement, data transformation, data federation, and more. The document also provides examples of how Oracle Data Integration has been used by customers for big data use cases involving petabytes of data.
Big Data Platform Processes Daily Healthcare Data for Clinic Use at Mayo ClinicDataWorks Summit
The document summarizes Mayo Clinic's implementation of a big data platform to process and analyze large volumes of daily healthcare data, including HL7 messages, for enterprise-wide clinical and non-clinical usage. The platform, built on Hadoop and using technologies like Storm and Elasticsearch, reliably handles 20-50 times more data than their current daily volumes. It provides ultra-fast free text search capabilities. The system supports applications like processing data for colorectal surgery, exceeding requirements and outperforming previous RDBMS-only systems. Ongoing work involves further enhancing capabilities and integrating with additional components as part of a unified data platform.
Teradata - Presentation at Hortonworks Booth - Strata 2014Hortonworks
Hortonworks and Teradata have partnered to provide a clear path to Big Analytics via stable and reliable Hadoop for the enterprise. The Teradata® Portfolio for Hadoop is a flexible offering of products and services for customers to integrate Hadoop into their data architecture while taking advantage of the world-class service and support Teradata provides.
Working with informtiaca teradata parallel transporterAnjaneyulu Gunti
The document discusses different techniques for loading and extracting data from Teradata databases using Informatica and Teradata tools. It describes several Teradata load utilities including FastLoad, MultiLoad, TPump, and FastExport that can be used in Informatica sessions. The Teradata Parallel Transporter (TPT) provides high-speed parallel data loading and extraction and supports operators like Export, Load, Update, and Stream. Configuring Informatica sessions to use TPT connections allows direct execution of TPT operators through APIs for improved performance.
The Big Data Analytics Ecosystem at LinkedInrajappaiyer
LinkedIn has several data driven products that improve the experience of its users -- whether they are professionals or enterprises. Supporting this is a large ecosystem of systems and processes that provide data and insights in a timely manner to the products that are driven by it.
This talk provides an overview of the various components of this ecosystem which are:
- Hadoop
- Teradata
- Kafka
- Databus
- Camus
- Lumos
etc.
The document discusses big data and Hadoop. It provides an introduction to Apache Hadoop, explaining that it is open source software that combines massively parallel computing and highly scalable distributed storage. It discusses how Hadoop can help businesses become more data-driven by enabling new business models and insights. Related projects like Hive, Pig, HBase, ZooKeeper and Oozie are also introduced.
Teradata Listener™: Radically Simplify Big Data StreamingTeradata
Teradata Listener™ is an intelligent, self-service solution for ingesting and distributing extremely fast moving data streams throughout the analytical ecosystem. Listener
is designed to be the primary ingestion framework for organizations with multiple data streams. Listener reliably delivers data without loss and provides low-latency ingestion for near real-time applications.
Taming the ETL beast: How LinkedIn uses metadata to run complex ETL flows rel...rajappaiyer
Data is the lifeblood of many LinkedIn products and must be delivered to the appropriate systems in a reliably and timely manner. This talk provides details of a metadata system that we built at LinkedIn to help manage the set of ETL flows that are responsible for data delivery at scale.
The document discusses using Attunity Replicate to accelerate loading and integrating big data into Microsoft's Analytics Platform System (APS). Attunity Replicate provides real-time change data capture and high-performance data loading from various sources into APS. It offers a simplified and automated process for getting data into APS to enable analytics and business intelligence. Case studies are presented showing how major companies have used APS and Attunity Replicate to improve analytics and gain business insights from their data.
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.
Modernizing Architecture for a Complete Data StrategyCloudera, Inc.
The document outlines a presentation about modernizing data strategies. It discusses how companies' relationships with data are changing and the business drivers for adopting big data and analytics. It then provides guidance on building a modern data strategy, emphasizing the importance of people, process, and technology. Specifically, it recommends starting with high-impact use cases, staying agile, and evolving capabilities over time to maximize value from data. The presentation also covers how Hadoop is being used for different workloads in both on-premise and cloud environments.
How to Operationalise Real-Time Hadoop in the CloudAttunity
Hadoop and the Cloud are two of the most disruptive technologies to have emerged from the last decade, but how can you adapt to the increasing rate of change whilst providing the enterprise with the right data, quickly?
Watch this webinar with Attunity, Cloudera and Microsoft and learn:
-How to ingest the most valuable enterprise data into Hadoop
-About real life use cases of Cloudera on Azure
-How to combine the power of Hadoop and the scalable flexibility of Azure
Enable your business with more data in less time. Visit www.attunity.com for more information.
Hadoop for the Data Scientist: Spark in Cloudera 5.5Cloudera, Inc.
Inefficient data workloads are all too common across enterprises - causing costly delays, breakages, hard-to-maintain complexity, and ultimately lost productivity. For a typical enterprise with multiple data warehouses, thousands of reports, and hundreds of thousands of ETL jobs being executed every day, this loss of productivity is a real problem. Add to all of this the complex handwritten SQL queries, and there can be nearly a million queries executed every month that desperately need to be optimized, especially to take advantage of the benefits of Apache Hadoop. How can enterprises dig through their workloads and inefficiencies to easily see which are the best fit for Hadoop and what’s the fastest path to get there?
Cloudera Navigator Optimizer is the solution - analyzing existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop. As the newest addition to Cloudera’s enterprise Hadoop platform, and now available in limited beta, Navigator Optimizer has helped customers profile over 1.5 million queries and ultimately save millions by optimizing for Hadoop.
Optimize Data for the Logical Data WarehouseAttunity
Rodan Zadeh, Director of Product Management at Attunity talks about how to optimize data for the logical data warehouse for the Cisco Virtual Tradeshow.
The document provides an overview of Hive architecture and workflow. It discusses how Hive converts HiveQL queries to MapReduce jobs through its compiler. The compiler includes components like the parser, semantic analyzer, logical and physical plan generators, and logical and physical optimizers. It analyzes sample HiveQL queries and shows the transformations done at each compiler stage to generate logical and physical execution plans consisting of operators and tasks.
The document discusses SQL Parallel Data Warehouse (PDW), which is a massively parallel processing appliance for large data warehousing workloads. It describes the different types of nodes in PDW, including control nodes that manage query execution, compute nodes that store and process data, and administrative nodes. The document also explains how PDW uses a hub and spoke architecture with the PDW appliance acting as a central data hub and individual data marts acting as spokes optimized for different user groups.
Securing the Data Hub--Protecting your Customer IP (Technical Workshop)Cloudera, Inc.
Your data is your IP and its security is paramount. The last thing you want is for your data to become a target for threats. This workshop will focus on the realities of protecting your customer’s IP from external and internal threats with battle hardened technologies and methodologies. Another key concept that will be examined is the connection of people, processes and technology. In addition, the session will take a look at authentication and authorisation, auditing and data lineage as well as the different groups required to play a part in the modern data hub. We will also look at how to produce high impact operation reports from Cloudera’s RecordService a new core security layer that centrally enforces fine-grained access control policy, which helps close the feedback loop to ensure awareness of security as a living entity within your organisation.
NYC Open Data Meetup-- Thoughtworks chief data scientist talkVivian S. Zhang
This document summarizes a presentation on data science consulting. It discusses:
1) The Agile Analytics group at ThoughtWorks which does data science consulting projects using probabilistic modeling, machine learning, and big data technologies.
2) Two case studies are described, including developing a machine learning model to improve matching of healthcare product data and using logistic regression for retail recommendation systems.
3) The origins and future of the field are discussed, noting that while not entirely new, data science has grown due to improvements in technology, programming languages, and libraries that have increased productivity and driven new career opportunities in the field.
The Intelligent Thing -- Using In-Memory for Big Data and BeyondInside Analysis
The Briefing Room with John O'Brien and Teradata
Live Webcast on June 11, 2013
http://www.insideanalysis.com
For traditional Data Warehousing and Big Data Analytics, research shows that a small percentage of enterprise data often comprises the lion's share of what's needed for queries. That's hot data, and organizations that know how to effectively harness that data can stay on top of what's happening. Conversely, cold data can certainly provide value at times, but should ideally be stored in ways that minimize cost. The more dynamically a company can manage this hot and cold data, the more efficient its information systems become.
Register for this episode of The Briefing Room to hear veteran database expert John O'Brien of Radiant Advisors as he outlines a strategy for managing hot and cold data. He'll be briefed by Alan Greenspan of Teradata, who will tout his company's Intelligent In-Memory solution, which optimizes the management of hot and cold data to keep analysts fueled with the data they need most. He'll also discuss Teradata Virtual Storage, which helps optimize the storage and provisioning of information assets.
Amazon Redshift is a data warehouse service that runs on AWS. It has a leader node that coordinates queries and compute nodes that store and process the data in parallel. The compute nodes can use either HDD storage optimized for large datasets or SSD storage optimized for fast queries. Data is stored in columns and compressed to reduce I/O. Queries are optimized using statistics on the data distribution, sort keys and other metadata. The EXPLAIN command and STL tables provide visibility into query plans and performance.
Enterprise Hadoop is Here to Stay: Plan Your Evolution StrategyInside Analysis
The Briefing Room with Neil Raden and Teradata
Live Webcast on August 19, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=1acd0b7ace309f765dc3196001d26a5e
Modern enterprises have been able to solve information management woes with the data warehouse, now a staple across the IT landscape that has evolved to a high level of sophistication and maturity with thousands of global implementations. Today’s modern enterprise has a similar challenge; big data and the fast evolution of the Hadoop ecosystem create plenty of new opportunities but also a significant number of operational pains as new solutions emerge.
Register for this episode of The Briefing Room to hear veteran Analyst Neil Raden as he explores the details and nature of Hadoop’s evolution. He’ll be briefed by Cesar Rojas of Teradata, who will share how Teradata solves some of the Hadoop operational challenges. He will also explain how the integration between Hadoop and the data warehouse can help organizations develop a more responsive and robust data management environment.
Visit InsideAnlaysis.com for more information.
This document summarizes Syncsort's high performance data integration solutions for Hadoop contexts. Syncsort has over 40 years of experience innovating performance solutions. Their DMExpress product provides high-speed connectivity to Hadoop and accelerates ETL workflows. It uses partitioning and parallelization to load data into HDFS 6x faster than native methods. DMExpress also enhances usability with a graphical interface and accelerates MapReduce jobs by replacing sort functions. Customers report TCO reductions of 50-75% and ROI within 12 months by using DMExpress to optimize their Hadoop deployments.
This document discusses strategies for combining Hadoop and a data warehouse to leverage the strengths of both platforms. It outlines four architectures: split workloads where Hadoop handles large datasets and the warehouse operational data; ETL where Hadoop performs preprocessing; secure access where the warehouse provides SQL access to Hadoop data; and active archive where Hadoop stores cold warehouse data. Case studies demonstrate how these architectures provide benefits like reduced costs, improved analytics and access to more data. The key is finding the right balance of workloads between the platforms.
Diyotta DataMover is an intuitive and easy to use tool built
to develop, monitor and schedule data movement jobs to
load into Hadoop from disparate data sources including
RDBMS, flatfiles, mainframes and other Hadoop instances.
DataMover enables users to graphically design data import or
export jobs by identifying source objects and then schedule
them for execution.
Big Data Taiwan 2014 Track2-2: Informatica Big Data SolutionEtu Solution
講者:Informatica 資深產品顧問 | 尹寒柏
議題簡介:Big Data 時代,比的不是數據數量,而是了解數據的深度。現在,因為 Big Data 技術的成熟,讓非資訊背景的 CXO 們,可以讓過去像是專有名詞的 CI (Customer Intelligence) 變成動詞,從 BI 進入 CI,更連結消費者經濟的脈動,洞悉顧客的意圖。不過,有個 Big Data 時代要 注意的思維,那就是競爭到最後,不單只是看數據量的增長,還要比誰能更了解數據的深度。而 Informatica 正是這個最佳解決的答案。我們透過 Informatica 解決在企業及時提供可信賴數據的巨大壓力;同時隨著日益增高的數據量和複雜程度,Informatica 也有能力提供更快速彙集數據技術,從而讓數據變的有意義並可供企業用來促進效率提升、完善品質、保證確定性和發揮優勢的功能。Inforamtica 提供了更為快速有效地實現此目標的方案,是精誠集團在 Big Data 時代的最佳工具。
Modernize Your Existing EDW with IBM Big SQL & Hortonworks Data PlatformHortonworks
Find out how Hortonworks and IBM help you address these challenges to enable success to optimize your existing EDW environment.
https://hortonworks.com/webinar/modernize-existing-edw-ibm-big-sql-hortonworks-data-platform/
Introduction sur Tez par Olivier RENAULT de HortonWorks Meetup du 25/11/2014Modern Data Stack France
During this presentation, Olivier will introduce Apache Tez. What it does ? Why is it seen by many as the Map Reduce v2. How is it helping Hive / Pig / Cascading and other increase their performance.
Speaker: Olivier Renault is a Principal Solution Engineer at Hortonworks the company behind Hortonworks Data Platform. Olivier is an expert on how to deploy Hadoop at scale in a secure and performant manner.
Prashanth Shankar Kumar has over 8 years of experience in data analytics, Hadoop, Teradata, and mainframes. He currently works as a Hadoop Developer/Tech Lead at Bank of America where he develops Hive queries, Impala queries, MapReduce programs, and Oozie workflows. Previously he worked as a Hadoop Developer at State Farm Insurance where he installed and managed Hadoop clusters and developed solutions using Hive, Pig, Sqoop, and HBase. He has expertise in Teradata, SQL, Java, Linux, and agile methodologies.
"Analyzing Twitter Data with Hadoop - Live Demo", presented at Oracle Open World 2014. The repository for the slides is in https://github.com/cloudera/cdh-twitter-example
Partner Ecosystem Showcase for Apache Ranger and Apache AtlasDataWorks Summit
This document provides information about Apache Ranger and Apache Atlas partner ecosystems and integration partnerships. It discusses Hortonworks' partner certification programs for SEC Ready and GOV Ready, and showcases partner technologies that have been integrated and certified with Apache Ranger and Apache Atlas, including from Talend, Arcadia Data, and Protegrity. The document also provides timelines and release information for Apache Ranger and Apache Atlas community development and integration with Hortonworks Data Platform (HDP) releases.
Big Data Integration Webinar: Getting Started With Hadoop Big DataPentaho
This document discusses getting started with big data analytics using Hadoop and Pentaho. It provides an overview of installing and configuring Hadoop and Pentaho on a single machine or cluster. Dell's Crowbar tool is presented as a way to quickly deploy Hadoop clusters on Dell hardware in about two hours. The document also covers best practices like leveraging different technologies, starting with small datasets, and not overloading networks. A demo is given and contact information provided.
Santosh Dandge is an experienced IT professional with over 5 years of experience as a Teradata and Hadoop Administrator. He is Teradata Certified and has extensive knowledge of Teradata architecture. As a Teradata DBA, he has experience managing databases, users, space, backups and performance optimization. He is also trained in Hadoop administration and has experience installing, configuring and managing Apache Hadoop clusters on AWS. He has worked as a Teradata DBA for several large clients in the US and UK.
With the advent of new open source platforms around Hadoop, NoSQL databases & in-memory databases, the data management stack in the enterprise is undergoing complete re-platforming. Batch and stream processing are two distinct data processing paradigms that need to be supported over this new stack. In this session I will talk about the importance of having a unified batch and stream processing engine and share my learning around -
Sample use cases to that bring out the need to have a unified stream & batch processing engine
Important features needed in the unified platform to tackle the above use cases.
Big SQL Competitive Summary - Vendor LandscapeNicolas Morales
IBM's Big SQL is their SQL for Hadoop product that allows users to run SQL queries on Hadoop data. It uses the Hive metastore to catalog table definitions and shares data logic with Hive. Big SQL is architected for high performance with a massively parallel processing (MPP) runtime and runs directly on the Hadoop cluster with no proprietary storage formats required. The document compares Big SQL to other SQL on Hadoop solutions and outlines its performance and architectural advantages.
This document summarizes Hortonworks' Data Cloud, which allows users to launch and manage Hadoop clusters on cloud platforms like AWS for different workloads. It discusses the architecture, which uses services like Cloudbreak to deploy HDP clusters and stores data in scalable storage like S3 and metadata in databases. It also covers improving enterprise capabilities around storage, governance, reliability, and fault tolerance when running Hadoop on cloud infrastructure.
Not Your Father’s Data Warehouse: Breaking Tradition with InnovationInside Analysis
The Briefing Room with Dr. Robin Bloor and Teradata
Live Webcast on May 20, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=f09e84f88e4ca6e0a9179c9a9e930b82
Traditional data warehouses have been the backbone of corporate decision making for over three decades. With the emergence of Big Data and popular technologies like open-source Apache™ Hadoop®, some analysts question the lifespan of the data warehouse and the future role it will play in enterprise information management. But it’s not practical to believe that emerging technologies provide a wholesale replacement of existing technologies and corporate investments in data management. Rather, a better approach is for new innovations and technologies to complement and build upon existing solutions.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains where tomorrow’s data warehouse fits in the information landscape. He’ll be briefed by Imad Birouty of Teradata, who will highlight the ways in which his company is evolving to meet the challenges presented by different types of data and applications. He will also tout Teradata’s recently-announced Teradata® Database 15 and Teradata® QueryGrid™, an analytics platform that enables data processing across the enterprise.
Visit InsideAnlaysis.com for more information.
Apache Tez - A unifying Framework for Hadoop Data ProcessingDataWorks Summit
This document provides an overview of Apache Tez, a framework for building data processing applications on Hadoop YARN. It describes how Tez allows applications to define complex data flows as directed acyclic graphs (DAGs) and handles distributed execution, fault tolerance, and resource management. Tez has improved the performance of Apache Hive and Pig by an order of magnitude by enabling more flexible DAG definitions and runtime optimizations. It also supports integration with other data processing engines like Spark, Storm and interactive SQL queries. The document outlines how Tez works and provides guidance on how developers can contribute to the open source project.
Similar to Partners 2013 LinkedIn Use Cases for Teradata Connectors for Hadoop (20)
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In a shocking turn of events, renowned Bollywood actress Urvashi Rautela found herself at the center of an unwarranted privacy invasion. A private bathroom video of the actress surfaced online, leading to widespread outrage and discussions about the importance of privacy in the digital age. This incident highlights the ongoing struggle celebrities face in safeguarding their personal lives from public scrutiny.
Softwide Security is a security company providing the world's best IT security solutions with the best support.
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□ Contact : 02-6052-5701
Steps to Register Company in Dubai Mainland.pptxblackswanbss
Discover the essential steps to register a company in Dubai Mainland. Learn about choosing business activities, legal structures, obtaining approvals, and securing a trade license to ensure a smooth setup process in Dubai.
POSH Act Training refers to the training programs conducted to ensure compliance with the Sexual Harassment of Women at Workplace (Prevention, Prohibition, and Redressal) Act, 2013, commonly known as the POSH Act. This Act mandates the prevention and redressal of sexual harassment in the workplace.
The ROI of Implementing Generative AI in Your Business.pptxdigitalxplive
Dive into the transformative potential of generative AI in our latest SlideShare presentation, "The ROI of Implementing Generative AI in Your Business." This engaging and informative presentation explores how generative AI can drive innovation, enhance efficiency, and create a competitive edge for modern enterprises.
Understanding the ROI of generative AI is crucial as it integrates seamlessly into existing workflows, making it challenging to isolate its impact. Our presentation addresses these complexities, providing strategies to maximize value and key metrics to track for success.
Learn about the importance of evaluating ROI for generative AI, including how it helps secure budget approvals and highlights areas where AI is most effective. Discover specific, quantifiable metrics for various business functions, from development and quality assurance to marketing, sales, and customer service.
This presentation showcases real-world examples and a multifaceted approach to measuring ROI, ensuring your AI investments are justified and optimized for maximum impact. Uncover how businesses have successfully implemented generative AI to achieve significant efficiency gains, improved employee productivity, and innovative breakthroughs.
Unlock the full potential of generative AI and pave the way for sustained success in today's fast-paced digital environment. Explore our detailed insights and actionable strategies in this comprehensive presentation.
Read the full blog for in-depth insights and details at: https://digitalexperience.live/roi-implementing-generative-ai-business
Honoring and Understanding the Significance of Guru PurnimaExotic India
In the oldest beliefs, it is believed that the day marks the first transmission of the Yogic sciences from Lord Shiva (The Adi yogi or first yogi) to his disciples, the ‘Saptarishi
"𝑩𝑬𝑮𝑼𝑵 𝑾𝑰𝑻𝑯 𝑻𝑱 𝑰𝑺 𝑯𝑨𝑳𝑭 𝑫𝑶𝑵𝑬"
𝐓𝐉 𝐂𝐨𝐦𝐬 (𝐓𝐉 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions. 𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
➢2024 GROUNDBREAKING CEREMONY OF SK LEAVEO PLANT
➢2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
➢2024 CHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
➢SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
➢WOW K-Music Festival 2023
➢ Winner [CROSS] Tour in HCM
➢ Super Show 9 in HCM with Super Junior
➢ HCMC - Gyeongsangbuk-do Culture and Tourism Festival
➢ Korean Vietnam Partnership - Fair with LG
➢ Korean President visits Samsung Electronics R&D Center
➢ Vietnam Food Expo with Lotte Wellfood
➢ Daewon Pharm Year End Party
➢ Giant Lantern Festival in Ha Noi with Gamuda Land
➢ Light Festival 2019 in HCMC with Phu My Hung Corp
(etc)
"𝐄𝐯𝐞𝐫𝐲 𝐞𝐯𝐞𝐧𝐭 𝐢𝐬 𝐚 𝐬𝐭𝐨𝐫𝐲, 𝐚 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐣𝐨𝐮𝐫𝐧𝐞𝐲. 𝐖𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐬𝐡𝐨𝐫𝐭𝐥𝐲 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐨𝐮𝐫 𝐬𝐭𝐨𝐫𝐢𝐞𝐬."
Most Disruptive Tech Companies Shaping the Future, 2024.pdfmirrorworldmagazine
This edition features a handful of business Most Disruptive Tech Companies Shaping the Future, 2024 that are at the forefront of leading us into a digital future
Solution manual for canadian income taxation 20222023 25th edition by william...stanslausnzuki569
Solution manual for canadian income taxation 20222023 25th edition by william buckwold joan kitunen matthew roman.pdf
Solution manual for canadian income taxation 20222023 25th edition by william buckwold joan kitunen matthew roman.pdf
The Fastest Way to Build Your Own App Without Code: ShipYourAppsFast!SOFTTECHHUB
Creating and selling your own software products can be a game-changer for online entrepreneurs. However, the barrier to entry has always been high, requiring either extensive coding knowledge or a significant investment in hiring developers. Enter ShipYourAppsFast, a revolutionary Windows software that aims to democratize app creation for internet marketers and content creators.
ShipYourAppsFast is designed to empower non-technical users to create their own applications without writing a single line of code. This tool focuses specifically on generating prompt-based apps that leverage the power of AI to assist content creators across various niches. The software promises to transform the way marketers approach product creation, offering a streamlined path from concept to launch.
As we dive deeper into this review, we'll explore how ShipYourAppsFast could potentially reshape your approach to product development and digital asset creation. Whether you're a seasoned marketer looking to expand your product line or a newcomer seeking to make your mark in the software space, this tool might just be the key to unlocking new possibilities.
Navigate the Narrative Landscape Measuring Change with Stories FiveWhyz.pdfDaniel Walsh
In a world where change and organizational transformation are ever-shifting landscapes, 'Sense-making' and participative narrative inquiry emerge as fit-for-purpose methods to guide leaders at every level through the fog. This session delves into the art of detecting weak signals and understanding the dynamics and patterns of organizations through the lived experiences shared by individuals.
Sense-making is a participatory form of ethnography. Individuals share personal experiences or observations and enrich these narratives by answering targeted questions, adding depth and layers of meaning. This method uniquely marries hard data with soft, qualitative insights. It inherently reduces bias, as participants, rather than external analysts, interpret and code their own stories. This approach not only lends authenticity to the data but also ensures that real-life stories, supported by data, are at the forefront of driving culture change and measuring progress.
The power of these narratives, especially when they reveal consistent patterns supported by quantitative evidence, is undeniable. They offer a detailed, multifaceted view, aiding leaders in spotting trends and behaviors within their organizations. By analyzing a broad collection of such narratives, organizations can detect subtle changes and inform targeted actions, making sense-making an invaluable tool for understanding complex systems and guiding interventions.
In this workshop, we'll learn how to apply sense-making and narrative inquiry methods to identify patterns and measure change. Additionally, we'll share how participants can leverage this same approach within their organizations as part of a retrospective or as a way to measure progress for a transformation.
Maximize Your AI Potential with These 15 ChatGPT-4o Prompts.pdfSOFTTECHHUB
Hey there! So, you've probably heard all the buzz about this new AI whiz kid on the block, ChatGPT-4o. It's like the cool new kid that everyone wants to hang out with - tech geeks, business folks, and artsy types are all lining up to see what it can do. But here's the thing: it's not just about how smart this AI is, it's about how clever we can be in using it.
Think of ChatGPT-4o as this super-smart friend who's read every book in the library and has a knack for quick comebacks. It's the result of a bunch of really smart people spending years tinkering with language and computers. But don't mistake it for just another chatbot - this AI can hold its own in a deep conversation, tackle tricky problems, and even come up with some pretty creative stuff. Sometimes, it's so good it makes you wonder if we're dealing with a machine or a really well-read human hiding behind a screen. Pretty wild, right?
Importance of effective prompts
Yet, for all its power, ChatGPT-4o is only as good as the prompts we feed it. Think of prompts as the keys to unlocking the AI's vast potential. The right prompt can open doors to insights you never knew existed, while a poorly crafted one might leave you knocking on wood. It's the difference between asking a master chef to "cook something" and providing them with a detailed recipe and premium ingredients.
Purpose of the article
This is where our journey begins. In the pages that follow, we'll embark on an exploration of the art and science of prompt engineering. We'll uncover the secrets of crafting prompts that can transform ChatGPT-4o from a mere tool into a powerful ally in your quest for knowledge, creativity, and innovation.
Whether you're a seasoned AI enthusiast or a curious newcomer, this article aims to equip you with the skills to maximize your AI potential. We'll dig into the intricacies of ChatGPT-4o, unravel the mysteries of effective prompt creation, and provide you with a treasure trove of 15 powerful prompts that can revolutionize the way you interact with AI.
Maximise your Business Potential: Annual Planning Workshopchris908327
Are you striving to elevate your business to new heights? Prepare to transform your aspirations into actionable plans with our exclusive 90-Day Planning Workshop, meticulously designed for owners and managers of family and privately owned businesses. Led by Russell Cummings, Australia’s premier business coach from Shifft, this online workshop is your golden ticket to crafting a focused roadmap for the April to June 2024 quarter.
The Indisputable Value of an Effective Qualitative Data PracticeRocketSource
Qualitative data is perhaps one of the most critical parts of modern organizational strategies today, yet many enterprises don’t know where to start collecting it or how to collect it properly. Even more of a struggle is analyzing the qualitative data available to extract insights that can shape the trajectory of the business as a whole.
With emerging technologies, such as Large Language Models and Generative AI breaking onto the enterprise scene with force, organizations today want to dive in and leverage these tools for maximum growth. There are more opportunities than ever to take data and speed the time to insights, but it all starts with having the right data to train these models on and the right strategic framework to extract the best insights to deliver higher ROI on your marketing campaigns, higher ROAS, lower CAC, higher LTV, and lower churn rates.
Partners 2013 LinkedIn Use Cases for Teradata Connectors for Hadoop
1. LINKEDIN USE CASES FOR
TERADATA CONNECTORS
FOR HADOOP
Eric Sun:
Jason Chen:
esun@LinkedIn.com
www.linkedin.com/in/ericsun
jason.chen@Teradata.com
www.linkedin.com/in/jason8chen
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Release of a SQL-H solution for the Teradata database with Teradata Database 14.10.Teradata SQL-H provides dynamic SQL access to Hadoop data in Teradata. With TeradataSQL-H, users can join Hadoop data with Teradata tables.Teradata SQL-H is important to customers because it enables analysis of Hadoop data in Teradata. It also allows standard ANSI SQL access to Hadoop data, leverages existing BI tool investments, as well as lowers costs by making data analysts self-sufficient.