Name: Find the Balance Between MPP Databases and Spark for Analytical Processing
Start: 2021-08-25T15:00:00Z
End: 2021-08-25T15:00:59.000Z
Location: BrightTALK
Rating: 5

OpenText has completed the purchase of Micro Focus, including Vertica. Our combined expertise expands our analytics offerings to help customers confidently scale analytics to the largest and most demanding workloads for the fastest predictive insights available on the market.

Do you love OpenText™ Vertica™ but sometimes have difficulty managing your Vertica clusters? Attend this webinar to learn how the latest product innovations bring developer experience and cluster operation to the next level. 
 
You’ll discover recent architectural enhancements to Vertica in Eon Mode—including new features such as sandboxing and in-database restoration/replication—and how they can be game changers for your cluster upgrade. 

We’ll also share how RESTful API and vclusters can deliver these new enhancements so users can easily integrate Vertica into their platforms and applications. 

Plus, get a sneak peek at our short-term roadmap for Kubernetes enhancements, as well as our long-term vision to optimize Vertica for containerization. 

Register today to learn how Vertica powers DevOps!

Future DevOps for OpenText™ Vertica™

Ignite your data with Vertica's High-Performance Analytics Platform .
Join our webinar that briefly introduces the Vertica data analytics platform, with its reduced TCO (Total Cost of Ownership) and total freedom of deployment in multiple environments (cloud, hybrid, on premise) on industry standard hardware. 
Vertica offers maximum integration openness in any context and with a large number of tools, guaranteeing total absence of lock-in.
Let our experts show you how predictive analytics is now a solid and efficient reality.

High performance in data analytics - a key to the success of your business.

Join Vertica and Qwak for an exclusive webinar on May 9th at 11AM EST to learn about the exciting partnership that allows Vertica customers to natively leverage Qwak within their DB, enabling unified analytics and machine learning at unprecedented speed, scale, and value.
In this webinar, Ran Romano, VP of Engineering at Qwak, and Badr Ouali, Head of Data Science at Vertica, will discuss how this partnership empowers organizations to seamlessly integrate advanced machine learning capabilities directly into their Vertica databases using Qwak's cutting-edge platform.
Discover the advantages of leveraging Qwak's innovative technology within Vertica, to simplify and accelerate the development, deployment, and management of machine learning models, eliminating the need for data movement or duplication. With Qwak's native integration, Vertica customers can unlock valuable insights from their data faster and more efficiently, enabling them to make data-driven decisions with confidence.
Don't miss this opportunity to learn from the experts at Vertica and Qwak about how this powerful partnership can revolutionize your analytics and machine learning workflows. Register now to secure your spot and join us on May 9th at 11AM EST to explore the limitless possibilities of unified analytics and machine learning with Vertica and Qwak.

Delivering ML at scale with Vertica and Qwak

Approximately 60% to 80% of business transactions are governed by contractual agreements. A typical Fortune 1000 company maintains 20K to 40K contracts. Manual contract review by legal professionals is expensive and time consuming. Gartner has predicted that by 2024 manual reviewing of contracts will be reduced by 50%. Deloitte estimates companies can achieve a 60% cost reduction by using intelligence contract analysis.  Magellan Contract Analyzer is the process of extracting meaningful business insights from contract data.  It is powered by a branch of Artificial Intelligence (AI) known as Natural Language Processing and can analyze thousands of documents in the time it would take a lawyer, procurement manager, or paralegal to review just a single contract.

Unlocking the value of your contract data with AI

In many ways, data warehousing has changed a lot over the last three decades. There have been optimizations such as massively parallel processing (MPP), in-memory processing, vector processing, and columnar storage. The cloud, and its separation of storage and compute, was a breakthrough bringing forth additional capabilities such as autoscaling and elasticity, multi-cluster concurrency, and freedom from data warehouse physical appliance hardware.
However, in other ways, data warehousing has not changed. The sequel to SQL turned out to be SQL. Throwing all your data into a Hadoop data lake did not obviate the need for the data warehouse, nor the need for the data quality and data governance that prevents data lakes from devolving into data swamps. Data lakehouses are in vogue now, but simply replacing HDFS with object storage in S3 buckets does not auto-magically make the data usable. Where (and how) to house data today and tomorrow requires not forgetting the lessons we have learned along the way.
Join Howard Holton of GigaOm and Jim Harris of Vertica for a webinar discussion about the past, present, and future of data warehousing.
Webinars attendees will also receive access to the related research GigaOm Radar for Data Warehouses, released in December 2022.

Where (and How) to House Data

Vários clientes estão usando a plataforma Vertica para Machine Learning dentro do banco de dados, com todos os seus dados, aumentando a acuracidade dos modelos e extraindo maior valor dos dados. Vamos falar um pouco sobre Machine Learning dentro do banco de dados, principais desafios e como a plataforma Vertica está ajudando nossos clientes a levar seus dados para outro nível. 
Dentre os nossos casos de sucesso destacamos 2:
GUESS?: Utilizam a plataforma Vertica para personalizar recomendações para os clientes online, controle de estoque, previsão de vendas etc. 
PHILIPS HEALTHCARE: Utilizam a plataforma para prever falhas nos equipamentos de saúde e garantir que não tenham manutenção não programada, oferecendo manutenção preventiva e maior tempo de operação em equipamentos críticos.

Do Reativo para o Preditivo – In-DB Machine Learning com Python e VerticaPy

Un’introduzione a Vertica e al suo ruolo nell’ambito della cultura “data driven”, i benefici e i valori esclusivi

Adottare una cultura “data driven” con Vertica proteggendo l’investimento

De termostatos inteligentes a dispositivos vestíveis, gerenciamento de rede de telecomunicações, publicidade personalizada e jogos on-line, varejo, manufatura e assistência médica, a Plataforma de dados Vertica ajuda os líderes desde setores a obter vantagens competitivas através da análise de dados. The Trade Desk, Guess, Cerner, entre milhares de outros, confiam na Plataforma de dados Vertica porque o sucesso de seus negócios é construído com base nos insights preditivos descobertos a partir de petabytes de dados em milissegundos.
Vertica é a plataforma de análise unificada, baseada em uma arquitetura massivamente escalável com o mais amplo conjunto de funções analíticas abrangendo eventos e séries temporais, correspondência de padrões, aprendizado de máquina, geoespacial e de ponta a ponta dentro do banco de dados. A plataforma Vertica permite que você aplique facilmente essas funções poderosas às maiores e mais exigentes cargas de trabalho analíticas, fornecendo a você e seus clientes insights de negócios preditivos mais rapidamente do que qualquer data warehouse de análise do mercado. A Vertica fornece uma plataforma de análise unificada nas principais nuvens públicas e data centers locais e integra dados no armazenamento de objetos em nuvem e HDFS sem forçar você a mover nenhum de seus dados.

Adote a cultura Data-Driven com Plataforma de dados unificada Vertica

Vertica, the pioneer of the columnar relational database, and Coffing Data Warehousing's Nexus software, the universal database analytic workstation for relational and cloud platforms, invite you to attend this webinar about data migration, a thorn in the side of every business.

In this webinar, you will learn about Vertica's unique performance-tuning techniques and why Vertica and Nexus provide the perfect environment for integrating and joining any combination of data across all legacy and cloud systems in your enterprise, including the ability to migrate over 20 different database platforms to Vertica using Nexus, with the setup and execution taking only minutes. 

Vertica, capable of deploying on-premises and/or on any cloud, combined with Nexus, enables limitless data migration, and empowers your business users with access to any data, anytime, anywhere.

Limitless Data Migration with Vertica and Nexus

Don’t take your foot off of the electrons. Micro Focus Vertica helps Jaguar TCS Racing compete in the software superiority race, to gain an edge on the competition. As a result of moving to Vertica for its high-performance advanced analytics and machine learning platform, the team now has data for every reading, every signal, every car, and every event.

Vertica’s High-Performance Advanced Analytics Platform Powers Jaguar TCS Racing

You have priorities, and we realize that one of them might not be experimenting with a new database to find better performance, value, and lower cost. However, there is an easy way to create a Vertica database on AWS in a few minutes with our Database as a Service (DBaaS) offering. 

Vertica Accelerator is Vertica-as-a-Service (SaaS), and it delivers great SQL analytics. However, it also offers so much more with high-performance advanced analytics and machine learning. See how the deployment, administration, and management of Vertica running in your own AWS cloud account is streamlined in Vertica Accelerator. Keep your data in Vertica to perform machine learning, geospatial and time-series analytics.

How to Create a Vertica Analytical Database on AWS in Minutes

AIOps (AI for IT Optimization) is a potent new way to handle the increasing complexity of IT systems, and meet the increasing demands of customers for smooth, always on, cellular networks, data centers, containerized deployments, and other IT services. In the past, log monitoring via human eyes was the way to spot the cause of problems. The human-driven "index-and-search" paradigm of 20 years ago, won’t cut it now when stack depth and deployment complexity have grown by orders of magnitude. Poking around logs is slow, dumb alert rules cause alert fatigue, and smarter alert rules are fragile. The future of IT optimization will be autonomous. Vertica’s powerful cloud-native analytics platform is a natural fit. Join Zebrium Founder and CTO Larry Lancaster as he describes how Zebrium, powered by Vertica, delivers real-time incident detection and root cause analysis. 
Learn:
• What AIOps is and how it works in modern applications
• How Zebrium uses AIOps to find incident root cause and speed MTTR
• Other AIOps case studies: HPE Infosight for compute networks, Jaguar TCS Racing for electric cars, SysMech for telecommunications, and more

AIOps Powers Root Cause Analysis, Increases Quality of Service, Decreases Churn

Tune in to learn then adopt the most popular and helpful machine learning techniques in Vertica. Hear directly from the inventor of VerticaPy, Badr Ouali, whose powerful Python library exposes scikit-like functionality to conduct data science projects on data stored in Vertica. VerticaPy has many features that will help you achieve high performance at scale without impacting your cluster. Topics covered include: caching some statistics to avoid recomputing them twice, sending multiple queries iteratively to preserve your cluster, and even sending multiple queries at the same time to gain performance.

Best Practices for VerticaPy

Data mesh is not something enterprises can buy off the shelf. Data mesh is a sociotechnical approach to share, access, and manage analytical data in complex and large-scale environments — within or across organizations. The technical aspect is more architecture than tool or platform, with almost a religious mantra of, “Data mesh is not about technology.” But the number one question data architecture and data engineering teams have about data mesh is, what are the strategies I use to implement it? 
Tune into this webinar to learn from guest speaker Michele Goetz,  VP/Principal Analyst at Forrester:
• some of the principles behind the data mesh concept 
• how to translate data mesh soft artifacts to deployable products
• what data capabilities exploit the decoupled nature of compute, storage, and state
• and where a scalable, high value for performance database like Vertica fits in a data mesh implementation

De-Mystifying the Data Mesh

As Cloudera ends support for CDH 6, platform owners are scrambling to decide what’s next for their big data strategy…

Whether you're looking to replace Cloudera, or augment it with a more modern analytics platform, join us Wednesday, September 14th at 12pm as we discuss what options are available for current Cloudera customers, and, detail how VAST & Vertica allied to create a leading alternative data analytics platform that helps enterprises consolidate their structured, semi-structured, and unstructured data silos on a flash-powered data lake.

What's Next? Life After Hadoop & Cloudera in the Middle East

As Cloudera ends support for CDH 6, platform owners are scrambling to decide what’s next for their big data strategy… 

Whether you're looking to replace Cloudera, or augment it with a more modern analytics platform, join us Tuesday, August 30th at 11am ET as we discuss what options are available for current Cloudera customers, and, detail how VAST & Vertica allied to create a leading alternative data analytics platform that helps enterprises consolidate their structured, semi-structured, and unstructured data silos on a flash-powered data lake.

What’s Next? Life After Hadoop & Cloudera…

Jump into the driver’s seat for a first-hand look at what it actually takes to prepare for race day at our Virtual Garage Tour in NYC!

Meet Team Principal, James Barclay, as he gives you a look at the all-electric Jaguar I-TYPE 5 race car—the future of racing. Learn about the technological innovations that power the fastest growing global motorsport in the world—ABB FIA Formula E World Championship.

Then, experience a deeper dive into the technology used behind the wheel as we discuss how Micro Focus Vertica helps Jaguar TCS Racing compete in the software arms race to gain an edge on the competition. As a result of moving to Vertica for its high-performance advanced analytics and machine learning platform, the team now has data for every reading, every signal, every car, and every event.

In this session, you’ll learn:
• How Vertica technology enables the racing team to glean important insights into data, blazingly fast
• How access to almost 700 in-database functions means key data is available to query within seconds and all the event data is available in minutes
• How engineers and strategists can now make critical adjustments to the powertrain, suspension, steering, braking and power management that were just not possible before

Don’t miss this rare, behind-the-scenes opportunity!

Jaguar TCS Racing Virtual Garage Tour―NYC, Vertica's Advanced Analytics Platform

Jump into the driver’s seat for a first-hand look at what it actually takes to prepare for race day at our Virtual Garage Tour in Berlin!

Meet Team Principal, James Barclay, as he gives you an up-close look at the new, all-electric Jaguar I-TYPE 5 race car—the future of racing. Learn about the technological innovations that power the fastest growing global motorsport in the world—ABB FIA Formula E World Championship.

Then, experience a deeper dive into the technology used behind the wheel as we discuss how Micro Focus Vertica helps Jaguar TCS Racing compete in the software arms race to gain an edge on the competition. As a result of moving to Vertica for its high-performance advanced analytics and machine learning platform, the team now has data for every reading, every signal, every car, and every event.

In this session, you’ll learn:
• How Vertica technology enables the racing team to glean important insights into data, blazingly fast
• How access to almost 700 in-database functions means key data is available to query within seconds and all the event data is available in minutes
• How engineers and strategists can now make critical adjustments to the powertrain, suspension, steering, braking and power management that were just not possible before

Don’t miss this rare, behind-the-scenes opportunity!

Both Apache Spark and massively parallel processing (MPP) databases are designed for the demands of analytical workloads. Each has strengths related to the full data science workflow, from consolidating data from many siloes, to deploying and managing machine learning models. Understanding the power of each technology, and the cost and performance trade-offs between them can help you optimize your analytics architecture to get the best of both. Learn when using Spark accelerates data processing, and when it spreads far beyond what you want to maintain. Learn when an MPP database can provide blazing fast analytics, and when it can fail to meet your needs. Most of all, learn how these two powerful technologies can combine to create a perfect balance of power, cost, and performance.

Find the Balance Between MPP Databases and Spark for Analytical Processing

Vertica

Apache Spark

Analytics

Data Science

Machine Learning

Data Architecture

Data Processing

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Find the Balance Between MPP Databases and Spark for Analytical Processing

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