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How Vertica & Scality deliver cloud analytics on-premises at massive scale

Under the Hood: Companies are moving analytic workloads to the cloud for operational flexibility and efficiency. Yet the risk, cost, and complexity of moving very large data volumes to the cloud is high, and analytics leaders are often forced to weigh their need for cloud innovation with the myriad challenges associated with cloud migration.

Join Maziar Tamadon, Director of Product and Solution Marketing at Scality, and Amit Saha, Principal Product Manager for Big Data Analytics & Cloud for Vertica, to share how Vertica in Eon Mode for Scality RING S3 object storage on HPE Apollo 4000 platform gives customers a cost-optimized on-premises architecture for modern analytic workloads at massive scale and speed. The joint solution combines the power of Vertica’s analytic capabilities with the elasticity of Scality S3 object storage so customers can deliver advanced and predictive analytic outcomes based on the entirety of their data.
Recorded Jan 12 2021 50 mins
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Presented by
Maziar Tamadon, Scality, and Amit Saha, Vertica
Presentation preview: How Vertica & Scality deliver cloud analytics on-premises at massive scale

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  • DataOps enhances data engineering for data science at Moneysupermarket.com Mar 25 2021 12:00 am UTC 45 mins
    Dave Poole, Data Solutions Architect, Moneysupermarket Group & Paige Roberts, Open Source Relations Manager, Vertica
    Data Operations is a methodology combining technological and cultural changes to improve data usage through better collaboration and automation. At Moneysupermarket.com, the DataOps approach is critical to meet the expectations of the business. Several important Vertica features facilitate the adoption of the DataOps culture and simplify the data engineer’s journey. DataOps with Vertica gets new data to data scientists promptly, so they can deliver maximum value to their organisation.
    Join our webinar to discover why Moneysupermarket.com adopted a DataOps approach!
  • Risk Decision-Making: Intellicta & Vertica Inform Smart Decisions Mar 16 2021 5:00 pm UTC 60 mins
    Sushil Madhukar, TechDemocracy, and Paige Roberts, Vertica
    Informed risk decision-making is a big challenge for CISOs and Cyber Security leadership, especially as the scale and speed of data needed to inform those decisions explodes. Enabling effective Risk decisions quickly is a priority for more than 2/3rd of security leadership across the enterprise, especially with the pandemic. But, risk decisions are not made just by IT anymore. More than 1/3rd of the decisions are either made or influenced outside the IT department. To help security leadership, and everyone else, make effective decisions faster, a high-scale data-driven approach is needed.

    Intellicta – an integrated risk platform – and Vertica – a unified analytics warehouse – partnered to measure and visualize the complete risk exposure profile across the enterprise in a single view in near real time for C-Suite executives. Vertica’s high-performance analytics and machine learning at extreme scale supports Intellicta to bridge the visibility gaps across organizational compliance, security, risk, and governance postures. In this webinar from our Data Disruptor series, learn how this clear comprehensive view of data across the enterprise was achieved, what factors drive good risk decisions, and how data analysis can make those clear to decision-makers.
  • Thought Leadership Series: Modernize Data Warehousing – Beyond Performance Mar 16 2021 2:00 am UTC 62 mins
    William McKnight, President, McKnight Consulting Group & Paige Roberts, Open Source Relations Manager, Vertica
    Configuration, management, tuning and other tasks can take away from valuable time spent on business analytics. If a platform leads to coding workarounds, non-intuitive implementations and other problems, it can make a big impact on long-term resource usage and cost. A lot of enterprise analytics platform evaluations focus on query price-performance to the exclusion of other features that can have a huge impact on business value, and can cause major headaches if you don’t take them into consideration.

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  • BNP Paribas accélère l’adoption du « data-driven marketing » Mar 11 2021 10:00 am UTC 60 mins
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    Le « data-driven marketing » ou marketing piloté par les données s’appuie sur le croisement d’informations (data) internes, externes, historiques et dynamiques permettant aux acteurs du marketing de mieux piloter leurs campagnes.
    Une approche maîtrisée permet d’accroître les performances et la satisfaction client tout en rationalisant les coûts. Un alignement des équipes, des processus et le choix des bon outils sont les piliers d’une stratégie réussie.

    Rejoignez Walid Hanachi, head of analytics acceleration chez BNP Paribas à l’occasion de ce webinar afin de découvrir :

    • Le contexte BNP Paribas Personal Finance avant accélération du « data-driven marketing »
    • Pourquoi la combinaison Vertica / Dataviz permet d’accéder aux bonnes données, au bon moment dans un format attractif pour rendre les équipes marketing plus agile
    • Les détails du déploiement et l’organisation de la plateforme data
    • Les usages de la data appliqués au marketing
    • Les perspectives d’évolution autour de la data
  • Retain your customers and boost your profits with AutoML at scale Recorded: Feb 23 2021 62 mins
    Maciej Paliwoda, Solution Architect @ Vertica & Lena Rampula, Data Science Engineer @ H2O.ai
    How H2O.ai & Vertica shorten the end-to-end AI pipeline and improve the accuracy of Machine Learning models to help you retain your customers and increase profits?

    According to various studies, the cost of customer acquisition is 5 to 7 time higher than retention. In addition, the average basket size of a loyal customer (€52.50) is twice the size of a new customer basket according to a McKinsey & Company study.

    Join our webinar presentation and demo to learn how AutoML at scale using H2O.ai & Vertica enables you to retain your customers and increase profits with Auto-ML to dynamically act on the right customer, at the right time through the right channel.

    Vertica enables easy and fast access to the right historical & live data as the event occurs while H2O.ai facilitates the Auto-ML models to create accurate predictions. With the seamless integration back to Vertica, the AI models are deployed at scale for immediate business outcome so data science projects don’t remain in the “black box”.

    Background information:
    H2O.ai, a Silicon Valley founded business, ranked by Gartner as a visionary company, automates machine learning, bringing AI within reach of every company and business users.
    Vertica is the Unified Analytics Warehouse designed for big data that allows you to run your queries and analytics without any compromise in terms of high-concurrency, speed and scalability, and is infrastructure-agnostic.

    Both world-class technologies have enabled thousands of customers in various industries (telecommunications, retail, banking, insurance, health care, pharma, etc.) to accelerate their AI transformations, shortening the end-to-end analytics pipeline and drastically improving the accuracy of predictive models.

    Please note that by registering for this event, our partner and co-host of this webinar H2O.ai may contact you with information about webinars and other news, products, or services that may be of interest to you.
  • Thought Leadership Webcast: Probing the Concept of Cloud-Native Databases Recorded: Feb 18 2021 50 mins
    Steve Sarsfield and Jeff Healey, Vertica
    Today, there’s a lot of buzz about cloud-native databases and how essential their capabilities are when moving data analytics workloads to the cloud. On-premises-only databases are rare, while cloud-only databases are common. What does “cloud-native” actually mean? Does it simply mean “cloud-only?” What’s the real difference, and is it important?
    In your planning to move analytical workloads to the cloud, are there specific reasons to prefer a database that can exist both on clouds and on-premises? Or, are there specific reasons to prefer a database built only for the cloud?

    In this webinar from our Thought Leadership Series, we’ll deconstruct the propaganda around cloud-native databases and discuss their place in your design of analytical systems.
    We’ll discuss:
    • Deployment – when you need simplified deployment or choosing optimal clusters for your specific workloads
    • Compute and Storage Separation – the practical advantages, when it makes sense, and where it can be deployed
    • Autoscaling – Advantages, disadvantages and alternatives
    • Ease of Admin – what the trade-off is for easy administration, how that can be balanced
    • Analytics – the depth of analytics offered on cloud platforms, and exploring options to get the analytic depth you need including machine learning
    • Data Governance – circumstances where business users control costs, handle compliance and data replication versus IT management of those costs

    Attend this webinar to learn how to deal with concerns like GDPR and other privacy regulations, vendor lock-in, pricing predictability, and more in your analytical database design.
  • Thought Leadership Series: Modernize Data Warehousing – Beyond Performance Recorded: Jan 28 2021 63 mins
    William McKnight, President, McKnight Consulting Group & Paige Roberts, Open Source Relations Manager, Vertica
    Configuration, management, tuning and other tasks can take away from valuable time spent on business analytics. If a platform leads to coding workarounds, non-intuitive implementations and other problems, it can make a big impact on long-term resource usage and cost. A lot of enterprise analytics platform evaluations focus on query price-performance to the exclusion of other features that can have a huge impact on business value, and can cause major headaches if you don’t take them into consideration.

    In this webinar, we’ll go beyond price-performance, and focus on everything else needed to modernize your data warehouse.
  • How to Increase Insight with Unified Analytics Recorded: Jan 26 2021 59 mins
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  • How Vertica & Scality deliver cloud analytics on-premises at massive scale Recorded: Jan 12 2021 50 mins
    Maziar Tamadon, Scality, and Amit Saha, Vertica
    Under the Hood: Companies are moving analytic workloads to the cloud for operational flexibility and efficiency. Yet the risk, cost, and complexity of moving very large data volumes to the cloud is high, and analytics leaders are often forced to weigh their need for cloud innovation with the myriad challenges associated with cloud migration.

    Join Maziar Tamadon, Director of Product and Solution Marketing at Scality, and Amit Saha, Principal Product Manager for Big Data Analytics & Cloud for Vertica, to share how Vertica in Eon Mode for Scality RING S3 object storage on HPE Apollo 4000 platform gives customers a cost-optimized on-premises architecture for modern analytic workloads at massive scale and speed. The joint solution combines the power of Vertica’s analytic capabilities with the elasticity of Scality S3 object storage so customers can deliver advanced and predictive analytic outcomes based on the entirety of their data.
  • Operationalizing Machine Learning for the Enterprise using Python & Vertica Recorded: Dec 16 2020 61 mins
    Waqas Dhillon, Badr Ouali and Jeff Healey, Vertica
    Under the Hood: Data science has the potential to help businesses gain a competitive edge, but the difficulty of putting machine learning models into production is a huge impediment. Vertica ML unifies machine learning with data warehousing, which not only democratizes access to core machine learning capabilities but also greatly simplifies putting these models into production.

    In this session, we will share with you how you can use Vertica’s Python interface to perform the entire machine learning cycle – from data preparation to model deployment on very large datasets spanning several nodes in a cluster. We will also demonstrate the use Vertica as a repository for your machine learning models so you can archive, manage, and deploy these models on your enterprise data whether on-premises or in the cloud.
  • Vertica CI/CD на Gitlab Recorded: Dec 9 2020 42 mins
    Dmitry Volodin, QCD architect, Sibur Digital
    В своем выступлении Дмитрий Володин, архитектор КХД в компании Сибур Digital, определяет ключевые проблемы параллельной разработки приложений для баз данных и делится опытом по решению этих проблем. Он рассказывает о применяемых подходах по решению конфликтов разработки. Описывает процесс автоматизации тестирования, контроля совместимости и развертывания доработок в продуктив в концепции CI/CD. Делится опытом внедрения новой методологии разработки и развертывания для приложений на Vertica, описывает полученный результат внедрения.
  • Новые крутые «фишки» в Vertica 10: Часть 2 Recorded: Dec 9 2020 33 mins
    Gianluigi Vigano, Senior Architect, Vertica
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  • Vertica и машинное обучение в масштабе Recorded: Dec 9 2020 39 mins
    Badr Ouali, Head of Data Science, Vertica
    Специалист по машинному обучению в Vertica Бадр Ули демонстрирует возможности функций машинного обучения Vertica в базе данных, функционирующие на инфраструктуре корпоративного уровня, для достижения быстрой и хорошо масштабируемой аналитики. Система управления ресурсами Vertica облегчает одновременную работу пользователей с возможностью изоляции пользовательской среды с применением привычного SQL-синтаксиса. Бадр демонстрирует, как работать с алгоритмами машинного обучения через SQL, и представляет возможности новой библиотеки VerticaPy для использования Vertica в аналитике на Python и Juniper Notebook.
  • Новые крутые «фишки» в Vertica 10: Часть 1 Recorded: Dec 9 2020 44 mins
    Maurizio Felici, Chief Field Technologist, Vertica
    Ведущий эксперт Vertica Маурицио Феличи описывает некоторые из захватывающих новых «фишек» Vertica 10, включая новые функции SQL, изменения в клиентских драйверах и конфигурациях, проекциях и многое другое, а затем демонстрирует новые функции, предлагаемые Vertica в Eon Mode для развертывания на площадке заказчика.
  • План развития Vertica Recorded: Dec 9 2020 24 mins
    Mark Lyons, Head of Product Management
    Директор по управлению продуктом Vertica Марк Лайонс представляет обзор того, как Vertica развивается в рамках версии Vertica 10, рассказывает о поддержке большего числа провайдеров публичных и частных облаков, чтобы позволить осуществлять гибридное развертывание Унифицированного хранилища данных.

    Улучшения будут включать в себя повышение автоматизации и упрощение использования, расширенные функции машинного обучения и прогнозирования, интеграцию и лучшую совместимость с экосистемой Machine Learning, расширение перечня поддерживаемых аналитических функций базы данных, улучшенное управление моделями ML и многое другое.
  • Как компании становятся лидерами с Унифицированным хранилищем данных Vertica Recorded: Dec 9 2020 45 mins
    Fouad Teban, Intl. Head of Field Engineering
    Фуад Тебан, руководитель отдела инженерных разработок Vertica в регионе EMEA, рассказывает, как Vertica помогает компаниям стать лидерами в своих рыночных сегментах. Фуад отмечает прорывные идеи Vertica, в том числе создание первой на рынке колоночной базы данных и базы данных в архитектуре MPP, первой, которая реализовала алгоритмы машинного обучения в базе данных, и первой, которая разделила вычислительные ресурсы и хранилище в гибридных архитектурах развертывания, особенно тех, которые объединяют локальное развертывание, развертывание на HDFS и в облаках. Он объясняет, как Vertica позволяет комбинировать аналитику над озерами данных и корпоративными хранилищами данных и унифицировать архитектуру всех хранилищ данных, работающих на любом оборудовании или в публичном облаке в любых масштабах.
  • Будущее аналитики и унифицированного хранилища данных Vertica Recorded: Dec 9 2020 60 mins
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    Унифицированное хранилище данных Vertica - это результат того, над чем команда Vertica работала в течение многих лет. В этом видео главный архитектор Vertica Чак Беар показывает, как Vertica осталась верной своему первоначальному замыслу. Он рассказывает о добавлении функций работы с комплексными типами данных и о планах по поддержке большего количества комплексных структур данных в будущем; о мультиоблачной конвергентной инфраструктуре; об аналитических кластерах, об изменениях в механизме выполнении запросов в части оптимизации для облаков, а также о поддержки интеграции: где найти документацию по внедрению и эксплуатации (включая открытый код на GitHub, обучающие модули Vertica Academy и обмен опытом на Vertica Forums).
  • Сила унифицированного хранилища данных Vertica Recorded: Dec 9 2020 48 mins
    Colin Mahony, Vertica GM & Joy King, Vertica Product & Marketing VP
    Видео состоит из двух частей. В первой части генеральный директор Vertica Колин Махони объясняет, как Vertica отвечает на основные запросы рынка, такие как: 1. стремительный рост объемов данных; 2. использование облачных схем развертывания и 3. растущую популярность алгоритмов машинного обучения для прогнозной аналитики. Он рассказывает, как клиенты, использующие Vertica, решают задачи, с которыми они сталкиваются следуя этим основным рыночным тенденциям.

    Во второй части вице-президент Vertica Джой Кинг рассказывает о концепции Унифицированного хранилища Vertica, о миссии Vertica, которая позволяет всем аналитиков получать быстрый доступ к данным, где бы они ни находились, без перемещения больших объемов данных или тяжелых процессов ETL.
  • Data Disruptors: Build augmented analytics with NLQ and the power of a question Recorded: Dec 3 2020 57 mins
    Saurabh Mishra, Director Data Analytics; Varun Gaur, Director Product Management; Paige Roberts, Vertica
    With Lumenore’s “Ask Me” Natural Language Query (NLQ) feature, you can ask your data questions in your own language and get clear answers, whether in a dashboard, a chart, an email, or the response of your choice. This powerful augmented analytics capability puts a lot of demands on the underlying infrastructure. Come learn what it does, how it works, how it can democratize analytics in your business, and why Lumenore uses Vertica to power this cutting-edge capability.
  • How ELISA successfully migrated its DWH to Vertica in record time Recorded: Dec 3 2020 60 mins
    Elina Tuominen, Service Manager, Elisa
    Elisa is a leading telecommunications provider in Finland founded in 1882. For almost 140 years Elisa has been a trailblazer in the deployment of new technologies. In 2018 Elisa launched the world's first commercial 5G NR network in the Finnish city of Tampere and in the Estonian capital of Tallinn.

    After 20 years of data warehousing of different generations and vendors also faced with an end-of-life deadline on 30 June 2020, Elisa had to select a replacement technology that is easy to implement, cost-effective, and meet all performance and integration criteria. After a thorough selection process and benchmark, Elisa embarked on a very challenging migration project with the mission to deliver a fully operational new platform in less than seven months with no impact on business reporting and operations.

    Join this webcast to hear from Elina Tuominen, Service Mgr, as she describes how she managed to turn this around and achieve “the best IT project ever”.
Data Analytics without Limits
The Vertica Analytics Platform is built to handle the most demanding analytic use cases and is trusted by thousands of leading data-driven enterprises around the world, including Etsy, Bank of America, Intuit, Uber and more. Vertica delivers speed, scale and reliability on mission-critical analytics at a lower total cost of ownership than legacy systems. All based on the same powerful, unified architecture, the Vertica Analytics Platform provides you with the broadest range of deployment models, so that you have complete choice as your analytical needs evolve. Deploy Vertica on-premise, in the clouds (AWS, Azure and GCP), on Apache Hadoop, or as a hybrid model. Find more information on Vertica at www.vertica.com.

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