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Ana mdz ferrell la-iniquida
Este documento explora la diferencia entre pecado e iniquidad. La iniquidad se refiere a lo que se tuerce del camino recto de Dios y es la raíz de donde surge todo el mal. Se transmite de generación en generación y es la base para las maldiciones y problemas que afectan a las familias. Mientras que el pecado es el fruto visible de la iniquidad, Dios perdona la iniquidad para liberarnos totalmente de las obras del diablo.
Diccionario de religiones__denominaciones_y_sectas
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The document discusses the three parts of an essay: the introduction, body, and conclusion. It states that the introduction should address the topic and present three examples or ideas to support the opinion. The body consists of three paragraphs that each detail one of the three examples, and should be three to five sentences each and use transitional words. The conclusion restates the introduction. An outline is recommended to help organize the essay and keep the body paragraphs focused on the thesis. The outline will also save time by allowing quicker writing of the rough draft.
Habilidades directivas
Las habilidades gerenciales incluyen capacidades como el manejo de recursos humanos y materiales, la toma de decisiones y el trabajo en equipo. Estas habilidades se clasifican en tres grupos: habilidades técnicas, habilidades humanas y habilidades estratégicas o conceptuales. Un gerente exitoso debe dominar estas tres áreas de habilidades para liderar y coordinar efectivamente un grupo de trabajo u organización.
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As you walk into your office on Monday morning, before you've even had a chance to grab a cup of coffee, your CEO asks to see you. He's worried: both customer churn and fraudulent transactions have increased over the past 6 months. As Data Manager, you have 6 months to solve this problem.
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As you walk into your office on Monday morning, before you've even had a chance to grab a cup of coffee, your CEO asks to see you. He's worried: both customer churn and fraudulent transactions have increased over the past 6 months. As Data Manager, you have 6 months to solve that.
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The document discusses applying a DevOps mindset to machine learning. It notes traditional problems in ML like data scientists not being engineers, lack of versioning and scaling issues. Applying continuous integration/deployment practices from DevOps can help address these by facilitating collaboration, versioning of code and data, continuous evaluation, packaging, deployment and model serving. This requires culture change and bridging the gap between data scientists and engineers. DevOps practices may help achieve the collaboration, automation and monitoring needed between ML development and operations.
devopsdays Warsaw 2018 - Chaos while deploying ML
AI is such a buzzword, with its futuristic implementations and sophisticated machine learning algorithms (Hello, Deep learning!). We are using ML when we need external data to reach a working product because it would be impossible to solve it with the regular for/if/loops. What are the next steps? Moreover, what about Test, Release, and Deployment? We always value data and call our organizations “data-driven,” but now the impact is even more significant. If you are using an ML component, misused/dirty/problematic data will affect not your internal reports as before… but your application deployment and quality of service. Let’s hear discuss some AI implementations stories (its advantages/problems) finding common mistakes and future challenges for such a hyped theme.
Level Up – How to Achieve Hadoop Acceleration
The Briefing Room with Robin Bloor and HP Vertica
Live Webcast on August 26, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=3dd6d1b068fe395f665c75adb682ac41
Hadoop has long passed the point of being a nascent technology, but many users have found that when left to its own devices, Hadoop can be a one trick pony. To get the most out of Hadoop, organizations need a flexible platform that empowers analysts and data managers with a complete set of information lifecycle management and analytics tools without a performance tradeoff.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he outlines Hadoop’s role in a big data architecture. He’ll be briefed by Walt Maguire of HP Vertica, who will showcase his company’s big data solutions, including HAVEn and the HP Big Data Platform. He will demonstrate how HP Vertica acts as a complement to Hadoop, and how the combination of the two provides a versatile and highly performant solution.
Visit InsideAnlaysis.com for more information.
Transform Legacy Enterprise into Data-Driven Digital Business
Businesses have realized that data are key differentiators and those that understand how to ingest, store, transform and analyze data can make better predictive and prescriptive decisions which in turn affect your business outcomes. Hence It is essential to predict, prevent and prepare than to restrict, repent and repair!
I will go over levels of maturity in this journey and share some practices that will help you carve out a successful data strategy for your enterprise.
More in-depth content will be shared on May 14th 2016 at Big Data Bootcamp Dallas( http://globalbigdataconference.com/64/dallas/big-data-bootcamp/schedule.html ) when we will have more time to delve on this topic.
A modern data platform meets the needs of each type of data in your business
Durante algo más de 20 años nuestros clientes han construído con confianza las bases de datos de sus aplicaciones críticas para el negocio sobre bases de datos comerciales robustas como Oracle y DB2 sobre Power Systems. A medida que la transformación digital de sus empresas evoluciona, impulsada por la migración hacia plataformas móbiles y web, se ven enfrentados a la necesidad de extraer más valor de su bien más preciado: sus datos.
Muchas empresas ahora necesitan comenzar a explorar y explotar otros tipos de datos y otros volúmenes de datos, para ellos Cognitive Systems presenta soluciones para una plataforma moderna de datos basados en bases de datos de clave y valor, documentales, de grafos, de fuente abierta y paralelas como Hadoop.
Building Resiliency and Agility with Data Virtualization for the New Normal
Watch: https://bit.ly/327z8UM
While the impact of COVID-19 is uniform across organisations in the region, a lot of how the organisation can recover from the impact and strive in the market would depend on their resiliency and business agility. An organisation’s data management strategy holds the key, as they tackle the challenges of siloed data sources, optimising for operational stability, and ensuring real time delivery of consistent and reliable information, irrespective of the data source or format.
Join this session to hear why large organisations are implementing Data Virtualization, a modern data integration approach in their data architecture to build resiliency, enhance business agility, and save costs.
In this session, you will learn:
- How to deliver clear strategy for agile data delivery across the enterprise without pains of traditional data integration
- How to provide a robust yet simple architecture for data governance, master data, data trust, data privacy and data access security implementation - all from single unified framework
- How to deploy digital transformation initiatives for Agile BI, Big Data, Enterprise Data Services & Data Governance
Codemotion Milan 2018 - AI with a devops mindset: experimentation, sharing an...
AI is the buzzword while ML is the underlying component... but when do we use ML? To solve problems that machines can find patterns without explicitly programming them to do so. But do you have a team building an ML model? How far are they from the IT team? Do they know how to deploy and serve that? Testing? And sharing what they have done? That's where a devops mindset comes in: reduce the batch size, continuous-everything and a culture of failure/experimentation are vital for your data team! In the end, I will show how the workflow of a data scientist can be in real life with a live demo!
Thiago de Faria - AI with a devops mindset - experimentation, sharing and eas...
AI is the buzzword while ML is the underlying component... but when do we use ML? To solve problems that machines can find patterns without explicitly programming them to do so. But do you have a team building an ML model? How far are they from the IT team? Do they know how to deploy and serve that? Testing? And sharing what they have done? That's where a devops mindset comes in: reduce the batch size, continuous-everything and a culture of failure/experimentation are vital for your data team! In the end, I will show how the workflow of a data scientist can be on the real life with a live demo!
Hot tech 20161116-ep0019-idera - data modeling in an agile environment-dez-sl...
Modern software development involves collaboration between different roles including developers and data experts. Agile methodologies like Scrum are increasingly used in projects instead of traditional waterfall approaches. For data-focused projects to be successful, specialists like data architects and database administrators must be intimately involved in development as developers do not have the expertise to handle many data-related challenges alone. The right tools are also critical to enabling effective collaboration between team members.
Fire in the Hole: How a Spark-Powered Platform Charges Analytics
The Briefing Room with Dr. Robin Bloor and Platfora
Live Webcast on October 28, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=0a3c69090358622b0acbf58c474c2df0
The future of big data analytics depends heavily on two factors: access and performance. Within the current landscape, business analysts can be limited by the data preparation process, which is often greatly slowed when requesting data from multi-structured sources such as Hadoop. The result? An encumbered workflow. Fortunately, a new solution built on Apache Spark, the open source cluster computing framework, has emerged and has the potential to disrupt the current analytics paradigm.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains how big data has forced a sea change in analytical processes. He'll be briefed by Denise Hemke of Platfora, who will tout her company's Big Data Analytic Platform for Hadoop. She will provide a demo and show how Platfora's end-to-end platform can bring next generation capabilities to analytical workflows, including faster access for analysts and more robust development for data scientists.
Visit InsideAnlaysis.com for more information.
Future Proofing Your Office 365 & SharePoint Strategy
Having an effective Office 365 and SharePoint strategy is essential to getting the full value out of your platform investment. But how do you create an effective strategy and where do you start?
Office 365 and SharePoint are constantly evolving as a platform so once you have a strategy, how do you ensure it will be successful over time?
Join Richard Harbridge as he discusses the importance of effective Office 365 strategies and outlines real-world best practices in the industry.
Cloudera Hunk
Learn about the combination of Cloudera CDH and Hunk: Splunk Analytics for Hadoop and NoSQL Data Stores
Dataiku - data driven nyc - april 2016 - the solitude of the data team m...
This document discusses the challenges faced by a data team manager named Hal in developing a data science software platform for his company. It describes Hal's background in technical fields like functional programming. It then outlines some of the disconnects Hal experienced in determining the appropriate technologies, hiring the right people, accessing needed data, and involving product teams. The document provides suggestions for how Hal can find solutions, such as taking a polyglot approach using open source technologies, creating an API culture, and focusing on solving big business problems to gain support.
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
Hadoop is a great platform for storing and processing massive amounts of data. Elasticsearch is the ideal solution for Searching and Visualizing the same data. Join us to learn how you can leverage the full power of both platforms to maximize the value of your Big Data.
In this webinar we'll walk you through:
How Elasticsearch fits in the Modern Data Architecture.
A demo of Elasticsearch and Hortonworks Data Platform.
Best practices for combining Elasticsearch and Hortonworks Data Platform to extract maximum insights from your data.
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
Transcript of a discussion on how HTI Labs in London provides the means and governance with their Schematiq tool to bring critical data to the interface that users want most.
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Hot tech 20170329-idera - health check - maintaining enterprise bi-dez-slides
This document discusses the complexity of modern business intelligence platforms and the challenges of managing them at scale. It notes that BI platforms have many interdependent components that must work together, including data sources, databases, administration, security, interfaces, analytics tools, and reporting. Any issues with performance can significantly impact business operations like decision making, reporting, compliance, and staff productivity. As BI platforms are complex ecosystems, a single problem in one area can affect overall performance. Smart tools are needed to monitor all the potential factors that could influence BI platform health.
CDO Summit 2017 - Sydney - 20170315 - Dez Blanchfield
My talk on the biggest disruptions to CDO's, 1) The Gravity of Data, 2) DevOps & Software Defined Everything, and 3) Watson the horizon for Cognitive Computing
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This document discusses the exponential growth of data from sources like aircraft, autonomous vehicles, the internet of things, and how traditional storage solutions are insufficient to handle the massive amounts of data being created. It suggests that a new, scalable, fault-tolerant, and cost-effective open source filesystem is needed to store today's data volumes and types as data growth continues rapidly.
Young it - digital transformation on a personal level
A talk I gave to an amazing community of young professionals and university graduates in the Busines and Technology industry groups through the NSW chapter of the Australian Computer Society, about my personal journey through the professional life long need to re-invent yourself as trends / technologies / markets change and shift in form and shape.
Hot tech 20161221 - ep0022 - IDERA - an ounce of prevention - Forging Healthy BI
This document discusses the challenges of maintaining and monitoring modern business intelligence platforms. It notes that BI platforms have many complex interconnected parts, and any performance issues can impact the entire organization. It lists several key areas that must be monitored and managed to ensure optimal platform performance, including data sources, databases, security, user access, analytics tools, and reporting. The document emphasizes that properly managing BI platform performance is critical because outages or poor performance can significantly hurt business operations and decision making.
Smart Cities Expo - World Forum - Sydney - 2016 - Dez Blanchfield
The document discusses the shift from centralized cloud and data center computing to distributed edge and fog computing. It notes that as more data is generated at the network edge by IoT devices, moving analytics and processing to the edge instead of sending all data to centralized cloud data centers is needed. It also discusses how non-traditional devices like vehicles and infrastructure can act as distributed cloud resources at the network edge. Security challenges around protecting data and systems at the edge are also mentioned.
Hot tech 20161207 - ep0021 - IDERA - Protect your database - High availabilit...
This document discusses the challenges of achieving high availability for database systems. It addresses that high availability is complex with no single solution, involving factors like uptime percentages, service level agreements, load balancing, fault tolerance, redundant infrastructure, and cost-benefit tradeoffs. The document also explains definitions of availability and high availability, and that each organization's high availability needs are unique depending on their business and technical constraints.
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Hot tech 20161005-ep0016-idera - index insanity - how to avoid database chaos...
This document discusses database performance and indexing. It notes that database performance can be improved through high performance server hardware, optimized operating systems, fast CPUs, plenty of RAM, high throughput backplanes, fast storage arrays, low latency networking, and clustering. It also discusses different types of databases (SQL, noSQL) and indexing techniques like B-Trees, bitmaps, hashes, clustered vs non-clustered indexes, and spatial, filtered, XML and full text indexes. The document emphasizes that database indexing is a critical tool for improving performance but that even expert DBAs need the right tools to deliver optimal index tuning.
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Hot tech 20160922-ep0015-dell statistica - edge analytics - the io_t economy ...
The document discusses how the scale and volume of data generated by the Internet of Things (IoT) requires a shift from centralized to distributed architectures. It notes that distributed processing and analytics have already been necessitated by large networks like the internet, content delivery, and cybersecurity. As more devices connect to the IoT, there will need to be new approaches to access, process, and analyze the large amount of streaming data at the network edge rather than solely in centralized locations. This shift is being driven by the immediate need to react to the high volumes and real-time analytics demands of the IoT.
Briefing room 20160920-ep017-striim - a real-time version of the truth-dez-sl...
In less than a lifetime, data processing has accelerated from punched cards to real-time analytics, where data streams continuously in seconds, hours, or less. Early big data architectures relied on disk and RAM storage, which have plummeted in cost. Customers now expect always-on, real-time experiences across banking, recommendations, and more due to factors like social media, fitness trackers, mobile devices, and the internet of things, which generates perpetual streams of data. Current architectures have adapted to handle real-time data streams rather than batched data.
OpenStack Australia Government Day 2016 - Dez Blanchfield
The document discusses the importance of building an open cloud architecture where cloud services are widely adopted. It covers cloud computing basics like virtualization platforms and private clouds. The document emphasizes that 99% of the value of cloud computing comes from services above the hypervisor layer, including compute, storage, and leveraging private, public and hybrid clouds. It also discusses how containers are now integrated into clouds and how cloud orchestration works. The overall message is that cloud computing provides value through scaling and on-demand services above the basic virtualization layer.
Hot tech 20161102 - ep0018 - idera - application acceleration - faster perfor...
The document discusses how managing application performance and service level agreements (SLAs) has become significantly more complex over the past decade. Where once a few system administrators could manage performance on a single server, applications and infrastructure are now massively distributed across physical, virtual, and cloud environments with a wide range of technologies. This hyper-scaled, complex modern IT landscape is far beyond human capabilities to manage performance and meet SLAs without automated tools.
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Hot tech 20160602 - ep007 - sync sort - big iron meet big data - liberating m...
While newer technologies like commodity clusters and Hadoop have gained popularity, mainframe systems still power many critical applications today. A survey found that over 350 organizations still own and manage mainframes, which is likely more than the number of large-scale Hadoop clusters worldwide. Mainframes have been in use for over 60 years and are still relied on by most Fortune 500 companies, banks, retailers, insurers, and governments for applications like banking, manufacturing, defense systems, and more. New tools are now available to connect mainframe data with modern analytics platforms.
Hot tech 20160914-ep0014-idera - who what where and how - why you want to kno...
The document discusses data compliance and security challenges for organizations. It mentions that compliance is an ongoing issue that requires the proper tools. Some of the top challenges listed are security and compliance, performance monitoring, incident detection and response, management and administration, and design and development. Reducing risks and improving security are also discussed as ongoing challenges.
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Over the past five decades, database administration has evolved from a simple task to a complex role. Originally, mainframe computers had small amounts of data that were easy to administer, but now powerful servers contain huge amounts of data requiring specialized skills and tools. Database administrators must now adapt to new technologies like cloud databases and scale their skills and knowledge accordingly.
Equinix Insurance - 2016Round Table Series - 20160728
The document discusses how digital disruption is impacting various industries, including financial services and insurance. It argues that insurance is ripe for disruption through approaches like using health data from apps to offer customized premiums in real-time. It also suggests thinking outside the box to develop innovative solutions, such as building trust with accurate health apps before offering lower premiums, endorsing ride-sharing services rather than penalizing them, and using open data and smart technologies to provide more personalized customer experiences.
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Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
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Bob Boule
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Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
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Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentationsEssentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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