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Unify Data Analytics

Natural Language Processing Augmented Analytics

The goal of data analytics, whether business intelligence or advanced analytics like machine learning has always been to guide organizations with solid data, rather than feelings. While every company strives to be data-driven, this requires making analytics accessible to more people. What could be more accessible than asking your data a question in your own language? Tune in to learn about natural language processing, the challenges and benefits of this exciting technology, and how it can democratize data analytics, and bring business results to the next level.
Recorded Nov 17 2020 62 mins
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Featuring Neil Raden, Founder and Principal Analyst of Hired Brains and Paige Roberts, Vertica Marketing
Presentation preview: Unify Data Analytics

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    - Offer data scientist access to the rich data sets often locked away in the data warehouse

    In this session, we will show how data warehouse technologies can be used as a repository for your machine learning models so you can train, manage, and deploy these models on your enterprise data whether on-premises or in the cloud. You will see how to train AI models on large data sets, supporting data scientists with their preferred languages like Python and R.
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  • DataOps enhances data engineering for data science at Moneysupermarket.com Mar 25 2021 12:00 am UTC 45 mins
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  • 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.

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  • Retain your customers and boost your profits with AutoML at scale Recorded: Feb 23 2021 62 mins
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    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
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    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.
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    • 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
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    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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  • Operationalizing Machine Learning for the Enterprise using Python & Vertica Recorded: Dec 16 2020 61 mins
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    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.
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    Colin Mahony, Vertica GM & Joy King, Vertica Product & Marketing VP
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    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 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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  • Title: Unify Data Analytics
  • Live at: Nov 17 2020 4:00 pm
  • Presented by: Featuring Neil Raden, Founder and Principal Analyst of Hired Brains and Paige Roberts, Vertica Marketing
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