The document summarizes Terapot, a commercial email archiving system that uses Hadoop. It discusses how Terapot addresses the challenges of archiving massive amounts of email data at low cost and high scalability. Terapot leverages Hadoop's distributed architecture for crawling, indexing, and searching emails across thousands of servers. Key components include batch processing for archiving, real-time indexing, distributed search, and analysis tools that mine the archived email data.
The data management industry has matured over the last three decades, primarily based on relational database management system(RDBMS) technology. Since the amount of data collected, and analyzed in enterprises has increased several folds in volume, variety and velocityof generation and consumption, organisations have started struggling with architectural limitations of traditional RDBMS architecture. As a result a new class of systems had to be designed and implemented, giving rise to the new phenomenon of “Big Data”. In this paper we will trace the origin of new class of system called Hadoop to handle Big data.
Module 01 - Understanding Big Data and Hadoop 1.x,2.xNPN Training
This document provides an overview of Big Data and Hadoop. It discusses what Big Data is, why existing data analytics approaches have limitations, and how Hadoop addresses these issues. Hadoop uses a master-slave architecture with the NameNode as master and DataNodes as slaves. It stores data in HDFS as blocks across DataNodes and allows distributed processing via MapReduce. The document covers Hadoop 1.0 and 2.0 components as well as challenges of Hadoop 1.x like single point of failure and lack of high availability of the NameNode.
This document summarizes a PhD dissertation defense about developing a semantic document architecture (SDArch) for desktop data integration and management. The key points are:
1. It proposes a semantic document model (SDM) that represents documents as semantically annotated and interlinked data units identified by URIs and composed of ontological concepts.
2. The semantic document architecture (SDArch) integrates desktop data into a unified information space and enables sharing data across social communities through semantic linking and annotations.
3. An evaluation validated that semantic documents improved information retrieval over traditional keyword search and full text indexing by leveraging semantic annotations and links between document units.
The document describes Megastore, a storage system developed by Google to meet the requirements of interactive online services. Megastore blends the scalability of NoSQL databases with the features of relational databases. It uses partitioning and synchronous replication across datacenters using Paxos to provide strong consistency and high availability. Megastore has been widely deployed at Google to handle billions of transactions daily storing nearly a petabyte of data across global datacenters.
2012.04.26 big insights streams im forum2Wilfried Hoge
This document summarizes IBM's Big Data platform called InfoSphere BigInsights and InfoSphere Streams. It discusses how the platform can integrate and manage large volumes, varieties and velocities of data, apply advanced analytics to data in its native form, and enable visualization and development of new analytic applications. It also describes the key components of the BigInsights platform including Hadoop, data integration, governance and various accelerators.
Characterization of hadoop jobs using unsupervised learningJoão Gabriel Lima
This document summarizes research characterizing Hadoop jobs using unsupervised learning techniques. The researchers clustered over 11,000 Hadoop jobs from Yahoo production clusters into 8 groups based on job metrics. The centroids of each cluster represent characteristic jobs and show differences in map/reduce tasks and data processed. Identifying common job profiles can help benchmark and optimize Hadoop performance.
This document summarizes the 25 most promising open source projects of 2010 according to Bruno Michel of af83. It provides descriptions and advantages for several key-value stores, document databases, distributed databases, workqueue services, and configuration management systems, including Redis, MongoDB, Riak, Cassandra, Resque, Beanstalkd, and Puppet.
This paper discusses implementing NoSQL databases for robotics applications. NoSQL databases are well-suited for robotics because they can store massive amounts of data, retrieve information quickly, and easily scale. The paper proposes using a NoSQL graph database to store robot instructions and relate them according to tasks. MapReduce processing is also suggested to break large robot data problems into parallel pieces. Implementing a NoSQL system would allow building more intelligent humanoid robots that can process billions of objects and learn quickly from massive sensory inputs.
"A Study of I/O and Virtualization Performance with a Search Engine based on ...Lucidworks (Archived)
Documentum xPlore provides an integrated Search facility for the Documentum Content Server. The standalone search engine is based on EMC's xDB (Native XML database) and Lucene. In this talk we will introduce xPlore and some of its key components and capabilities. These include aspects of a tight integration of Lucene with the XML database: xQuery translation and optimization into Lucene query/API's as well as transactional update Lucene). In addition, xPlore is being deployed aggressively into virtualized environments (both disk I/O and VM). We cover some performance results and tuning tips in these areas.
This document discusses Facebook's deployment of Hadoop and HBase to support real-time applications at massive scale. It describes how Facebook Messages, Insights, and other applications require high throughput writes, large datasets, and low-latency reads. The document outlines why Hadoop and HBase were chosen over other systems to meet these needs, including elasticity, consistency, availability, and fault tolerance. It also describes enhancements made to HDFS and HBase to optimize for Facebook's workloads.
Hadoop summit EU - Crowd Sourcing Reflected IntelligenceTed Dunning
This document discusses how search and big data technologies are evolving to enable reflected intelligence capabilities. It provides backgrounds of Ted Dunning from MapR and Ivan Provalov from LucidWorks. The document outlines various use cases that combine search, analytics and discovery on big data to gain insights from user interactions. It argues that the combination of MapR's data platform and LucidWorks' search technologies provides an integrated solution for building next generation search and discovery applications.
This document discusses the emergence of cloud libraries and cloud computing applications for science and technology (S&T) libraries. It begins by describing the evolution from traditional paper-based libraries to digital libraries without physical walls. It then defines cloud computing and explains how many popular web services already utilize cloud computing. The document outlines different types of cloud services including SaaS, PaaS, IaaS and Daas and provides examples of how libraries currently use cloud computing applications. It raises questions about data ownership, costs, and technical requirements for libraries adopting cloud-based systems and services.
Brig Lamoreaux\'s of Apollo Group worked with his colleagues to put together this WP detailing their evaluation of MongoDB. He also presented at Oracle Openworld 2012 on their use case with MongoDB.
MongoDB on Windows Azure provides two options for deploying the MongoDB database on Microsoft's cloud platform:
1) Windows Azure Virtual Machines allow more control over infrastructure but require more operational effort. Users can choose Windows or Linux and install software themselves.
2) Windows Azure Cloud Services decrease operational effort through automated management but provide less infrastructure control. Only Windows is supported and configurations are pre-defined.
Both options provide scalability and high availability through features like replication and sharding. Developers should evaluate the level of control and effort needed to determine the best deployment model for their application on the Windows Azure cloud.
Dynamo Systems - QCon SF 2012 PresentationShanley Kane
A look at Dynamo-based systems: the architectural principles, use cases and requirements; where they differ from relational databases; and where they are going.
Cassandra is used as an email store to provide horizontal scalability and high availability for storing email metadata and indexing labels. The document discusses storing email metadata like headers, body, and attachments in Cassandra while storing file attachments in a blob store like S3 for better performance due to Cassandra's limitations for large blobs. A polyglot data model is used with Cassandra for metadata and indexing and a blob store for file attachments.
Este documento es un boletín de la Asociación para el Avance de la Ciencia y la Tecnología en España que contiene noticias, artículos de opinión y artículos científicos sobre temas relacionados con la ciencia y la tecnología. Incluye la creación de un nuevo Ministerio de Ciencia e Innovación en España y las implicaciones de este cambio para la gestión de la investigación pública en el país.
Este documento describe las características y beneficios de los blogs de maternidad. Explica que estos blogs comparten experiencias personales de maternidad de una manera cálida que permite a las madres identificarse. También funcionan como un diario para expresar emociones y recibir apoyo de otras madres. Los blogs de maternidad tienen futuro porque las marcas están prestando más atención a ellos como fuente de influencia para las madres.
Serious Games und Social Media: Ein ZukunftsmarktJohannes Konert
Die Verwendung von user-generated Content und Interaktionsformen aus Social Media Anwendungen ermöglicht einen Wissensaustausch und Interaktion der Spieler (bspw. eines Lernspiels) untereinander. Mit der Verbindung von Serious Games (Computerspielen die für einen weiteren Zweck als reines Entertainment eingesetzt werden) und Social Media eröffnet sich das Forschungsfeld der "Social Serious Games".
Der Vortrag auf der Learntec 2013 in Karlsruhe erörtert Definitonen, Marktvolumen, nötige Komponenten und zeigt erste Implementierungen und Evaluationsergebnisse.
CFW Domestic Sprinkler Regulations - Bafsa Fire Sprinkler WalesRae Davies
The document discusses the British Automatic Fire Sprinkler Association's (BAFSA) efforts to develop vocational qualifications and skills training for the fire sprinkler industry in the UK. It outlines BAFSA's achievements since 2012, which include developing the first National Occupational Standards, conducting a labor market survey, and creating a Level 2 National Qualification in Fire Sprinkler Installation. The qualification is being delivered through BAFSA-preferred training providers to help formalize training and address skills gaps in the industry workforce. BAFSA aims to continue developing career pathways and additional qualifications to ensure industry workers have the skills needed.
El documento habla sobre aprender a ver la escultura. Explica que la escultura puede realizarse en varios materiales y que cada escultor expresa algo personal en sus obras para mostrar sentimientos y formas al espectador. Sin embargo, el espectador puede tener percepciones diferentes de las obras según su experiencia o sensibilidad personal.
Este documento es una hoja de afiliación al sindicato ATES Catalunya. Contiene secciones para proporcionar información personal como nombre, dirección y datos de contacto. También incluye opciones para la autorización de descuento de cuotas sindicales ya sea a través de banca o nómina, indicando los detalles bancarios requeridos. El solicitante firma al final para dar su consentimiento.
Este documento presenta el syllabus de la asignatura de Propedéutica y Terapéutica Ocular. La asignatura cubre conceptos sobre formulación de fármacos oftálmicos y tratamientos paliativos para el cuidado primario ocular de acuerdo con la ley, desarrollando habilidades de diagnóstico, reconocimiento de patologías y exámenes de apoyo. La metodología incluye casos clínicos simulados y talleres con laboratorios farmacéuticos. La evaluación consta de cuatro componentes: conceptos
This document outlines the author's qualifications and training which include:
- Numerous NVQ qualifications in areas like business improvement techniques, lean office practices, manufacturing and engineering operations, warehousing and storage, business and administration, and customer service.
- Apprenticeships in customer service, business and administration, information technology, manufacturing operations, and engineering operations.
- Training in rapid improvement workshops covering topics like 5S workplace organization, continuous improvement, failure mode effect analysis, and lean leadership.
The document also provides information on the benefits and costs of various training programs the author can facilitate.
Este documento describe el sitio web Expedia, incluyendo sus funciones principales como reserva de vuelos, hoteles, alquiler de autos y paquetes de viaje. También explica cómo las empresas pueden promocionarse en el sitio a través de un programa de afiliación que ofrece comisiones e incentivos. Finalmente, resume testimonios mixtos sobre la experiencia de los usuarios con el sitio.
El documento describe una empresa de consultoría llamada Progestión Occidente. Progestión Occidente ofrece servicios de asesoría, consultoría, capacitación y acompañamiento en diversas áreas como finanzas públicas, desarrollo económico local, ordenamiento territorial, desarrollo social y capital humano. La empresa está conformada por un equipo multidisciplinario de profesionales con experiencia en estas áreas. Su misión es brindar soluciones de calidad a entidades públicas y privadas para impulsar el desarrollo regional de manera s
Ethical hacking Chapter 2 - TCP/IP - Eric VanderburgEric Vanderburg
The document describes the TCP/IP protocol stack and key networking concepts. It explains that TCP/IP has four layers - network, internet, transport, and application. The transport layer handles encapsulation and uses TCP for connection-oriented communication, while the internet layer handles packet routing between hosts using IP addresses. It also covers binary, octal, and hexadecimal numbering systems used in IP addressing and packet headers.
Este documento menciona varios lugares y monumentos históricos de la ciudad de Granada, España, incluyendo la Alhambra, el Albaicín, el Generalife y otros como la Plaza del Triunfo, la Fuente del Triunfo, la Facultad de Medicina, varias iglesias y la catedral, así como ríos y fuentes emblemáticas de la ciudad. Finaliza deseando un buen día.
Ameet Talwalkar, assistant professor of Computer Science, UCLA at MLconf SFMLconf
Abstract:
Apache Spark’s MLlib is a terrific library for fitting large-scale machine learning models. However, translating high-level problem statements like “learn a classifier” into a working model presently requires significant manual effort (via ad hoc parameter tuning) and computational resources (to fit several models). We present our work on the MLbase optimizer – a system designed on top of Spark to quickly and automatically search through a hyperparameter space and find a good model. By leveraging performance enhancements, better search algorithms, and statistical heuristics, our system offers an order of magnitude speedup over standard methods.
A Conversation manager faciltates conversations between consumers and between consumers and the brand. This from a strong believe that word-of-mouth is the key driver of business growht. And so...integrate word-of-mouth in everything that you do.
Este documento presenta el plan de convivencia de un centro educativo. Establece objetivos generales como promover la cultura de paz, mejorar la convivencia y fomentar valores como el respeto. Los objetivos específicos incluyen concienciar al profesorado sobre la convivencia intercultural y de género, dotarlos de herramientas para gestionar conflictos, e implicar al alumnado en la prevención y resolución de problemas de convivencia.
El acné es una enfermedad inflamatoria crónica de la piel causada por el taponamiento de los poros. Se diagnostica identificando las lesiones como puntos negros, blancos y otras inflamatorias. Los tratamientos incluyen terapias tópicas con retinoides y terapias orales con antibióticos como tetraciclina, eritromicina, doxiciclina o minociclina, dependiendo de la gravedad de las lesiones.
Please view to understand why this is Australia\'s fasted adopting email archiving solution. Highly Functional E-Discovery capability, unlimited storage, zero hardware. Solve your PST nightmare while having real time access to ALL company email.
This document discusses real-time big data applications and provides a reference architecture for search, discovery, and analytics. It describes combining analytical and operational workloads using a unified data model and operational database. Examples are given of organizations using this approach for real-time search, analytics and continuous adaptation of large and diverse datasets.
Large-Scale Search Discovery Analytics with Hadoop, Mahout, SolrDataWorks Summit
This document discusses search, discovery, and analytics (SDA) using large-scale distributed technologies. It describes an SDA architecture using Apache Solr, Apache Mahout, and Apache Hadoop. Challenges of implementing SDA at scale are discussed, such as determining authoritative data stores and balancing real-time and batch processing. Specific techniques for implementing search, discovery, and experiment management are also covered.
Apachecon Euro 2012: Elastic, Multi-tenant Hadoop on DemandRichard McDougall
Elastic, Multi-tenant Hadoop on Demand! Richard McDougall, Chief Architect, Application Infrastructure and Big Data, VMware, Inc @richardmcdougll ApacheCon Europe, 2012. Broadens the application of Hadoop technology with horizontal and vertical use cases. Hadoop enables parallel processing through a programming framework for highly parallel data processing using MapReduce and the Hadoop Distributed File System (HDFS) for distributed data storage. Serengeti automates deployment of Hadoop on virtual platforms in under 30 minutes for multi-tenant elastic Hadoop as a service.
This document provides an overview and introduction to Hadoop, an open-source framework for storing and processing large datasets in a distributed computing environment. It discusses what Hadoop is, common use cases like ETL and analysis, key architectural components like HDFS and MapReduce, and why Hadoop is useful for solving problems involving "big data" through parallel processing across commodity hardware.
The document provides an overview of big data technologies including Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, MongoDB, and Cassandra. It discusses how these technologies enable processing and analyzing very large datasets across commodity hardware. It also outlines the growth and market potential of the big data sector, which is expected to reach $48 billion by 2018.
Predictive Analytics and Machine Learning…with SAS and Apache HadoopHortonworks
In this interactive webinar, we'll walk through use cases on how you can use advanced analytics like SAS Visual Statistics and In-Memory Statistic with Hortonworks’ data platform (HDP) to reveal insights in your big data and redefine how your organization solves complex problems.
The millions of people that use Spotify each day generate a lot of data, roughly a few terabytes per day. What does it take to handle datasets of that scale, and what can be done with it? I will briefly cover how Spotify uses data to provide a better music listening experience, and to strengthen their busineess. Most of the talk will be spent on our data processing architecture, and how we leverage state of the art data processing and storage tools, such as Hadoop, Cassandra, Kafka, Storm, Hive, and Crunch. Last, I'll present observations and thoughts on innovation in the data processing aka Big Data field.
Crowd-Sourced Intelligence Built into Search over HadoopDataWorks Summit
Search is increasingly being used to gather intelligence on multi-structured data leveraging distributed platforms such as Hadoop in the background. This session will provide details on how search engines can be abused to use not text, but mathematically derived tokens to build models that implement reflected intelligence. The session will describe how to integrate Apache Solr/Lucene with Hadoop. Then we will show how crowd-sourced search behavior can be looped back into analysis and how constantly self-correcting models can be created and deployed. Finally, we will show how these models can respond with intelligent behavior in realtime.
Hadoop makes data storage and processing at scale available as a lower cost and open solution. If you ever wanted to get your feet wet but found the elephant intimidating fear no more.
We will explore several integration considerations from a Windows application prospective like accessing HDFS content, writing streaming jobs, using .NET SDK, as well as HDInsight on premise or on Azure.
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...Amr Awadallah
Apache Hadoop is revolutionizing business intelligence and data analytics by providing a scalable and fault-tolerant distributed system for data storage and processing. It allows businesses to explore raw data at scale, perform complex analytics, and keep data alive for long-term analysis. Hadoop provides agility through flexible schemas and the ability to store any data and run any analysis. It offers scalability from terabytes to petabytes and consolidation by enabling data sharing across silos.
HBaseCon 2012 | Overcoming Data Deluge with HBase to Help Save the Environmen...Cloudera, Inc.
Opower is a fast moving energy management SaaS company that collects sensor data from nearly all of the major utilities in the United States–meaning from more than 45 million American households–along with major utilities in 5 countries throughout Europe and AsiaPac. Opower manages more than 100 billion meter reads, ranging from high frequency power data (AMI), smart thermostats data, and weather data. Currently all data at Opower is stored in HBase or Hadoop (and is notably not security sensitive). This discussion will discuss Opower’s HBase architecture, highlight potential and current uses of data in HBase, share the vision of Opower’s future projects and directions, and reveal how Opower’s big data management has allowed the company to help its utility clients save enough energy to power a city of nearly 200,000 people and save utility customers more than $70 million since only 2008!
Hadoop World 2011: Data Ingestion, Egression, and Preparation for Hadoop - Sa...Cloudera, Inc.
One of the first challenges Hadoop developers face is accessing all the data they need and getting it into Hadoop for analysis. Informatica PowerExchange accesses a variety of data types and structures at different latencies (e.g. batch, real-time, or near real-time) and ingests data directly into Hadoop. The next step is to parse the data in preparation for analysis in Hadoop. Informatica provides a visual IDE to deploy pre-built parsers or design specific parsers for complex data formats and deploy them on Hadoop. Once the analysis is complete, Informatica PowerExhange delivers the resulting output to other information management systems such as a data warehouse. Learn in this session from Informatica and one of their customers, how to get all the data you need into Hadoop, parse a variety of data formats and structures, and egress the resultant output to other systems.
Offline processing with Hadoop allows for scalable, simplified batch processing of large datasets across distributed systems. It enables increased innovation by supporting complex analytics over large data sets without strict schemas. Hadoop adoption is moving beyond legacy roles to focus on data processing and value creation through scalable and customizable systems like Cascading.
Hadoop World 2011: How Hadoop Revolutionized Business Intelligence and Advanc...Cloudera, Inc.
"Amr Awadallah served as the VP of Engineering of Yahoo's Product
Intelligence Engineering (PIE) team for a number of years. The PIE
team was responsible for business intelligence and advanced data
analytics across a number of Yahoo's key consumer facing properties (search, mail, news, finance, sports, etc). Amr will share the data architecture that PIE had implementted before Hadoop was deployed and the headaches that architecture entailed. Amr will then show how most, if not all of these headaches were eliminated once Hadoop was deployed. Amr will illustrate how Hadoop and Relational Database complement each other within the traditional business intelligence data stack, and how that enables organizations to access all their data under different
operational and economic constraints."
Solr is an open source enterprise search platform built on Apache Lucene. It provides powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., word, pdf) handling. Solr powers the search capabilities of many large websites and is highly scalable, fault tolerant, and easy to use.
The document describes the evolution of Facebook's big data architectures from 2007 to 2011. It started with a traditional data warehouse using MySQL and grew significantly over time. Facebook moved to Hadoop and Hive in 2008 to enable data science at scale and store all data online. In 2009, they further democratized data with tools to make it accessible. Later improvements focused on isolation, efficiency, utilization and monitoring to control the growing chaos. By 2011, they developed Puma for real-time analytics and Peregrine for fast queries to go beyond Hadoop.
Similar to Hw09 Terapot Email Archiving With Hadoop (20)
The document discusses using Cloudera DataFlow to address challenges with collecting, processing, and analyzing log data across many systems and devices. It provides an example use case of logging modernization to reduce costs and enable security solutions by filtering noise from logs. The presentation shows how DataFlow can extract relevant events from large volumes of raw log data and normalize the data to make security threats and anomalies easier to detect across many machines.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
The document outlines the 2021 finalists for the annual Data Impact Awards program, which recognizes organizations using Cloudera's platform and the impactful applications they have developed. It provides details on the challenges, solutions, and outcomes for each finalist project in the categories of Data Lifecycle Connection, Cloud Innovation, Data for Enterprise AI, Security & Governance Leadership, Industry Transformation, People First, and Data for Good. There are multiple finalists highlighted in each category demonstrating innovative uses of data and analytics.
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
The document outlines the agenda for Cloudera's Enterprise Data Cloud event in Vienna. It includes welcome remarks, keynotes on Cloudera's vision and customer success stories. There will be presentations on the new Cloudera Data Platform and customer case studies, followed by closing remarks. The schedule includes sessions on Cloudera's approach to data warehousing, machine learning, streaming and multi-cloud capabilities.
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
The document discusses the benefits and trends of modernizing a data warehouse. It outlines how a modern data warehouse can provide deeper business insights at extreme speed and scale while controlling resources and costs. Examples are provided of companies that have improved fraud detection, customer retention, and machine performance by implementing a modern data warehouse that can handle large volumes and varieties of data from many sources.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
TrustArc Webinar - Innovating with TRUSTe Responsible AI CertificationTrustArc
In a landmark year marked by significant AI advancements, it’s vital to prioritize transparency, accountability, and respect for privacy rights with your AI innovation.
Learn how to navigate the shifting AI landscape with our innovative solution TRUSTe Responsible AI Certification, the first AI certification designed for data protection and privacy. Crafted by a team with 10,000+ privacy certifications issued, this framework integrated industry standards and laws for responsible AI governance.
This webinar will review:
- How compliance can play a role in the development and deployment of AI systems
- How to model trust and transparency across products and services
- How to save time and work smarter in understanding regulatory obligations, including AI
- How to operationalize and deploy AI governance best practices in your organization
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
Choosing the Best Outlook OST to PST Converter: Key Features and Considerationswebbyacad software
When looking for a good software utility to convert Outlook OST files to PST format, it is important to find one that is easy to use and has useful features. WebbyAcad OST to PST Converter Tool is a great choice because it is simple to use for anyone, whether you are tech-savvy or not. It can smoothly change your files to PST while keeping all your data safe and secure. Plus, it can handle large amounts of data and convert multiple files at once, which can save you a lot of time. It even comes with 24*7 technical support assistance and a free trial, so you can try it out before making a decision. Whether you need to recover, move, or back up your data, Webbyacad OST to PST Converter is a reliable option that gives you all the support you need to manage your Outlook data effectively.
Generative AI technology is a fascinating field that focuses on creating comp...Nohoax Kanont
Generative AI technology is a fascinating field that focuses on creating computer models capable of generating new, original content. It leverages the power of large language models, neural networks, and machine learning to produce content that can mimic human creativity. This technology has seen a surge in innovation and adoption since the introduction of ChatGPT in 2022, leading to significant productivity benefits across various industries. With its ability to generate text, images, video, and audio, generative AI is transforming how we interact with technology and the types of tasks that can be automated.
Redefining Cybersecurity with AI CapabilitiesPriyanka Aash
In this comprehensive overview of Cisco's latest innovations in cybersecurity, the focus is squarely on resilience and adaptation in the face of evolving threats. The discussion covers the imperative of tackling Mal information, the increasing sophistication of insider attacks, and the expanding attack surfaces in a hybrid work environment. Emphasizing a shift towards integrated platforms over fragmented tools, Cisco introduces its Security Cloud, designed to provide end-to-end visibility and robust protection across user interactions, cloud environments, and breaches. AI emerges as a pivotal tool, from enhancing user experiences to predicting and defending against cyber threats. The blog underscores Cisco's commitment to simplifying security stacks while ensuring efficacy and economic feasibility, making a compelling case for their platform approach in safeguarding digital landscapes.
Top 12 AI Technology Trends For 2024.pdfMarrie Morris
Technology has become an irreplaceable component of our daily lives. The role of AI in technology revolutionizes our lives for the betterment of the future. In this article, we will learn about the top 12 AI technology trends for 2024.
It's your unstructured data: How to get your GenAI app to production (and spe...Zilliz
So you've successfully built a GenAI app POC for your company -- now comes the hard part: bringing it to production. Aparavi addresses the challenges of AI projects while addressing data privacy and PII. Our Service for RAG helps AI developers and data scientists to scale their app to 1000s to millions of users using corporate unstructured data. Aparavi’s AI Data Loader cleans, prepares and then loads only the relevant unstructured data for each AI project/app, enabling you to operationalize the creation of GenAI apps easily and accurately while giving you the time to focus on what you really want to do - building a great AI application with useful and relevant context. All within your environment and never having to share private corporate data with anyone - not even Aparavi.
Cracking AI Black Box - Strategies for Customer-centric Enterprise ExcellenceQuentin Reul
The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
- Implement AI responsibly to build trust and foster strong customer relationships
Whether you're at the early stages of your AI journey or looking to optimize existing initiatives, this session will provide you with actionable insights and strategies needed to leverage AI as a powerful catalyst for customer-driven enterprise success.
The History of Embeddings & Multimodal EmbeddingsZilliz
Frank Liu will walk through the history of embeddings and how we got to the cool embedding models used today. He'll end with a demo on how multimodal RAG is used.
1. Next Revolution
Toward Open Platform
Terapot: Massive Email Archiving
with Hadoop & Friends
- Commercial Hadoop Application
Jaesun Han
Founder & CEO of NexR
jshan@nexrcorp.com
2. #2
About NexR
Offering Hadoop & Cloud Computing Platform and Services
Hadoop & Cloud Computing Services
Hadoop Provisioning & Management
Academic Support
Massive Email Archiving MapReduce Workflow
Program
Massive Data Storage & Processing Platform
Cloud Computing Platform
(Compatible with Amazon AWS)
icube-cc icube-sc
(Compute) (Storage)
3. #3
What is Email Archiving?
The Objectives of Email Archiving
- Regulatory compliance
- e-Discovery: Litigation and legal discovery
- E-mail backup and disaster recovery
- Messaging system & storage optimization
- Monitoring of internal and external e-mail content
4. #4
The Architecture of Email Archiving
Data Acquisition Data Processing Data Access
Journaling Indexing Search
Mailbox Crawling Filtering Discovery
Email
Servers
Journaling Crawling
Search employee
Indexing Indexes
Email Archiving
Server
Discovery auditor
administrator
Archival Storage
email data
5. #5
The Challenges of Email Archiving
Explosive growth of digital data
- 6 times (988XB) in 2010 than 2006
- 95% (939 XB) unstructured data including email
- Increasing the cost and complexity of archiving
Requiring scalable & low cost archiving
Reinforcement of data retention regulation
- Retention, Disposal, e-Discovery, Security
- HIPPA(Healthcare) 21 ~ 23 yrs, SEC17(Trading) 6 yrs,
OSHA(Toxic) 30 yrs, SOX(Finance) 5 yrs, J-SOX, K-SOX
Requiring scalable archiving & fast discovery
Needs for intelligent data management
- Knowledge management from email data
- Filtering, monitoring, data mining, etc
Requiring integration with intelligent system
6. #6
New Requirements of Email Archiving
High Scalability
Low Cost
High Performance
Intelligence
7. #7
Terapot: When Hadoop Met Email Archiving…
Scale-out architecture with Hadoop
- Hadoop HDFS for archiving email data
- Hadoop MapReduce for crawling & indexing
- Apache Lucene for search & discovery
Email
Servers
Distributed Crawling
Journaling
Hadoop MapReduce
(Crawling, Indexing, etc)
Journaling Hadoop HDFS
Server (Archiving)
Distributed Search & Discovery
8. #8
Features of Terapot
Distributed Massive Email Archiving
High Scalability by Shared-Nothing Architecture
- Thousands of servers, billions of emails
Low Cost by Inexpensive Hardware
- Entry servers under $5,000
High Performance by Parallelism
- Fast search under 1-2 seconds for each user account
- Fast discovery in parallel with MapReduce
Intelligence by Data Mining
- Contact network analysis, content analysis, statistics
Support Both On-premise Version and Cloud(hosted)
Version
Development with Various Open Source Software
9. #9
The Architecture of Terapot
Terapot Clients Email Sources
HTTP/
SOAP REST JSON POP3 Mail NAS/
FTP/SFTP
Server Server NFS
Server
Terapot Frontend
MR Workflow Manager MailServer Search Gateway Analyzer
Batch processing Analysis 4 key
Real-Time
Crawling Indexing Merging Searching ETL Mining components
Indexing
Hadoop MapReduce, Lucene, & Hive
HDFS
(email)
Local
(index)
10. #10
Batch Processing Component
Email Sources
HDFS
Crawling Archiving policies
(MR) An archive file per user
An archive file per user Several archive files per crawling
(sequence file)
configured
period
Indexing
(MR)
a temporary index file
per user
(lucene index file)
Local file system
Merging shard 1 shard 0
Search
a merged index file
(for backing up)
index shard
(3 copy replication)
11. #11
Real-Time Indexing Component
Journaling
Server
Forwarding Database
Memory
Indexing Real-Time Archiving
Indexing
Crawling
Real-Time
HDFS
Index
Flushing
archive
Batch
Processing index
Component
12. #12
Search & Discovery Component
Search
Gateway
Locating
index shards
Distributed
Search
Assigning
shards
Search Nodes Real-Time
copy index shards Indexing Nodes
to local file system
Zookeeper
Updating
shard status HDFS
index shards