Dirigida a directivos y analistas de mediana y gran empresa, Big Data Spain celebró una charla previa a la conferencia de la segunda edición del 7y 8 de noviembre del 2013.
Vídeo youtube: https://www.youtube.com/watch?v=6HbWErRCD1g
¿Quieres saber más?
http://www.paradigmatecnologico.com/
Oscar Méndez, co-fundador de www.paradigmatecnologico.com y www.stratio.com, habló de Big Data desde un punto de vista de negocio, y despejó dudas acerca del coste y recursos necesarios para aprovechar esta tecnología.
Las plataformas v2.0 post-Hadoop permiten el despligue rápido y simple de herramientas integradas de data mining, data processing, data analysis y data visualization. Los avances de los últimos 12 meses dejan atrás las limitaciones de sistemas de Business Intelligence tradicionales.
The objective of this module is to provide an overview of the basic information on big data.
Upon completion of this module you will:
-Comprehend the emerging role of big data
-Understand the key terms regarding big and smart data
- Know how big data can be turned into smart data
- Be able to apply the key terms regarding big data
Duration of the module: approximately 1 – 2 hours
A top-down look at current industry and technology trends for Big Data, Data Analytics and Machine Learning (cognitive technologies, AI etc.). New slides added for Ark Group presentation on 1st December 2016.
Introduction
Big Data may well be the Next Big Thing in the IT world.
Big data burst upon the scene in the first decade of the 21st century.
The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Face book were built around big data from the beginning.
Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
The objective of this module is to provide an overview of the basic information on big data.
Upon completion of this module you will:
-Comprehend the emerging role of big data
-Understand the key terms regarding big and smart data
- Know how big data can be turned into smart data
- Be able to apply the key terms regarding big data
Duration of the module: approximately 1 – 2 hours
A top-down look at current industry and technology trends for Big Data, Data Analytics and Machine Learning (cognitive technologies, AI etc.). New slides added for Ark Group presentation on 1st December 2016.
Introduction
Big Data may well be the Next Big Thing in the IT world.
Big data burst upon the scene in the first decade of the 21st century.
The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Face book were built around big data from the beginning.
Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
Overview of major factors in big data, analytics and data science. Illustrates the growing changes from data capture and the way it is changing business beyond technology industries.
Social media is an umbrella term that defines the various activities that integrate technology, social interaction, and the construction of words, pictures, videos and audio.
Big Data is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it…
Hadoop is an open source framework which is used for storing and processing the large scale of data sets on large clusters of hardware.
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
BIG Data & Hadoop Applications in Social MediaSkillspeed
Explore the applications of BIG Data & Hadoop in Social Media via Skillspeed.
BIG Data & Hadoop in Social Media is a key differentiator, especially in terms of generating memorable customer experiences.
Herein, we discuss how leading social networks such as Facebook, Twitter, Pinterest, LinkedIN, Instagram & Stumble Upon utilize Hadoop.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
In the analogue era information was scarce and came from questionnaires and sampling. Since the dawn of the digital age in 2012 far more data than ever before is stored and it is mainly collected passively, i.e. while people go about doing what they normally do, such as run their businesses, use their cell phones and conduct internet searches.
Analysts, policy makers and business people value business tendency surveys (BTS) and consumer opinion surveys (COS) specifically because the survey results are available before the corresponding (official) quantitative data. However, Big Data has begun to make inroads on areas traditionally covered by BTS and COS. It has a competitive edge over BTS and COS, as it is available in real-time, is based on all observations and does not rely on the active participation of respondents. Furthermore, Big Data has little direct production costs, because it is merely a by-product of business processes. In contrast, putting together and maintaining a sample of active respondents and collecting information through questionnaires as in the case of BTS and COS, require the upkeep of a costly infrastructure and the employment of people with scarce, specialised skills.
However, BTS and COS also have a competitive edge over Big Data in certain aspects. These aspects could broadly be put into two groups, namely 1) BTS and COS offer information that Big Data cannot supply and 2) BTS and COS do not suffer from some of the shortcomings of Big Data. The biggest competitive advantage of BTS and COS is that they measure phenomenon that Big Data does not cover. Big Data records only actual outcomes, while BTS and COS also cover unquantifiable expectations and assessments. Although Big Data often claims that it covers the whole population universe (and not only a selection) this does not necessarily prevent bias. For example, twitter feeds could be biased, because certain demographic or less activist groups are under-represented. In contrast, the research design and random sampling of BTS and COS limit their selection bias.
To remain relevant and survive, producers of BTS and COS will have to adapt and publicise their unique competitive advantage vis-à-vis Big Data in the future. The biggest shift will probably require that producers of BTS and COS make users more aware of the value of the unique forward looking information of BTS and COS (i.e. their recording of expectations about the future).
Big Data Trends - WorldFuture 2015 ConferenceDavid Feinleib
David Feinleib's Big Data Trends presentation from the World Future Society's Annual Conference, WorldFuture 2015, held at the Hilton Union Square, San Francisco, California July 25, 2015.
I volunteered my time to share about big data to those looking to understand the space.
This was for Networking with Grace, a group that is focused on helping those get back to work. I put this presentation together to help people learn about big data and how to transition their skill sets to the space.
Big Data and The Future of Insight - Future FoundationForesight Factory
As Big Data sweeps through consumer-facing businesses, we ask:
- If Big Data is truly a revolution, then what (and whom) will it eliminate or elevate?
- What value will still be derived from conventional market research and brand-building techniques?
- If every brand is backed by Big Data, can every brand prosper?
For more information please contact info@futurefoundation.net or visit www.futurefoundation.net
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
El impacto del big data en la estrategia de los medios de comunicacion by Osc...ACTUONDA
El impacto del Big Data en la estrategia de negocio de los medios de comunicación
Oscar Mendez (CEO, Stratio)
@omendezsoto @stratioDB
Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-BM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es
Overview of major factors in big data, analytics and data science. Illustrates the growing changes from data capture and the way it is changing business beyond technology industries.
Social media is an umbrella term that defines the various activities that integrate technology, social interaction, and the construction of words, pictures, videos and audio.
Big Data is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it…
Hadoop is an open source framework which is used for storing and processing the large scale of data sets on large clusters of hardware.
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
BIG Data & Hadoop Applications in Social MediaSkillspeed
Explore the applications of BIG Data & Hadoop in Social Media via Skillspeed.
BIG Data & Hadoop in Social Media is a key differentiator, especially in terms of generating memorable customer experiences.
Herein, we discuss how leading social networks such as Facebook, Twitter, Pinterest, LinkedIN, Instagram & Stumble Upon utilize Hadoop.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
In the analogue era information was scarce and came from questionnaires and sampling. Since the dawn of the digital age in 2012 far more data than ever before is stored and it is mainly collected passively, i.e. while people go about doing what they normally do, such as run their businesses, use their cell phones and conduct internet searches.
Analysts, policy makers and business people value business tendency surveys (BTS) and consumer opinion surveys (COS) specifically because the survey results are available before the corresponding (official) quantitative data. However, Big Data has begun to make inroads on areas traditionally covered by BTS and COS. It has a competitive edge over BTS and COS, as it is available in real-time, is based on all observations and does not rely on the active participation of respondents. Furthermore, Big Data has little direct production costs, because it is merely a by-product of business processes. In contrast, putting together and maintaining a sample of active respondents and collecting information through questionnaires as in the case of BTS and COS, require the upkeep of a costly infrastructure and the employment of people with scarce, specialised skills.
However, BTS and COS also have a competitive edge over Big Data in certain aspects. These aspects could broadly be put into two groups, namely 1) BTS and COS offer information that Big Data cannot supply and 2) BTS and COS do not suffer from some of the shortcomings of Big Data. The biggest competitive advantage of BTS and COS is that they measure phenomenon that Big Data does not cover. Big Data records only actual outcomes, while BTS and COS also cover unquantifiable expectations and assessments. Although Big Data often claims that it covers the whole population universe (and not only a selection) this does not necessarily prevent bias. For example, twitter feeds could be biased, because certain demographic or less activist groups are under-represented. In contrast, the research design and random sampling of BTS and COS limit their selection bias.
To remain relevant and survive, producers of BTS and COS will have to adapt and publicise their unique competitive advantage vis-à-vis Big Data in the future. The biggest shift will probably require that producers of BTS and COS make users more aware of the value of the unique forward looking information of BTS and COS (i.e. their recording of expectations about the future).
Big Data Trends - WorldFuture 2015 ConferenceDavid Feinleib
David Feinleib's Big Data Trends presentation from the World Future Society's Annual Conference, WorldFuture 2015, held at the Hilton Union Square, San Francisco, California July 25, 2015.
I volunteered my time to share about big data to those looking to understand the space.
This was for Networking with Grace, a group that is focused on helping those get back to work. I put this presentation together to help people learn about big data and how to transition their skill sets to the space.
Big Data and The Future of Insight - Future FoundationForesight Factory
As Big Data sweeps through consumer-facing businesses, we ask:
- If Big Data is truly a revolution, then what (and whom) will it eliminate or elevate?
- What value will still be derived from conventional market research and brand-building techniques?
- If every brand is backed by Big Data, can every brand prosper?
For more information please contact info@futurefoundation.net or visit www.futurefoundation.net
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
El impacto del big data en la estrategia de los medios de comunicacion by Osc...ACTUONDA
El impacto del Big Data en la estrategia de negocio de los medios de comunicación
Oscar Mendez (CEO, Stratio)
@omendezsoto @stratioDB
Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-BM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es
Óscar Méndez - Big data: de la investigación científica a la gestión empresarialFundación Ramón Areces
El 3 de julio de 2014, organizamos en la Fundación Ramón Areces una jornada con el lema 'Big Data: de la investigación científica a la gestión empresarial'. En ella estudiamos los retos y oportunidades del Big data en las ciencias sociales, en la economía y en la gestión empresarial. Entre otros ponentes, acudieron expertos de la London School of Economics, BBVA, Deloite, Universidades de Valencia y Oviedo, el Centro Nacional de Supercomputación...
Now companies are in the middle of a renovation that forces them to be analytics-driven to
continue being competitive. Data analysis provides a complete insight about their business. It
also gives noteworthy advantages over their competitors. Analytics-driven insights compel
businesses to take action on service innovation, enhance client experience, detect irregularities in
process and provide extra time for product or service marketing. To work on analytics driven
activities, companies require to gather, analyse and store information from all possible sources.
Companies should bring appropriate tools and workflows in practice to analyse data rapidly and
unceasingly. They should obtain insight from data analysis result and make changes in their
business process and practice on the basis of gained result. It would help to be more agile than
their previous process and function.
Gain New Insights by Analyzing Machine Logs using Machine Data Analytics and BigInsights.
Half of Fortune 500 companies experience more than 80 hours of system down time annually. Spread evenly over a year, that amounts to approximately 13 minutes every day. As a consumer, the thought of online bank operations being inaccessible so frequently is disturbing. As a business owner, when systems go down, all processes come to a stop. Work in progress is destroyed and failure to meet SLA’s and contractual obligations can result in expensive fees, adverse publicity, and loss of current and potential future customers. Ultimately the inability to provide a reliable and stable system results in loss of $$$’s. While the failure of these systems is inevitable, the ability to timely predict failures and intercept them before they occur is now a requirement.
A possible solution to the problem can be found is in the huge volumes of diagnostic big data generated at hardware, firmware, middleware, application, storage and management layers indicating failures or errors. Machine analysis and understanding of this data is becoming an important part of debugging, performance analysis, root cause analysis and business analysis. In addition to preventing outages, machine data analysis can also provide insights for fraud detection, customer retention and other important use cases.
La arquitectura de microservicios persigue maximizar la adaptabilidad de las soluciones mediante la distribución de las responsabilidades del software en servicios con ciclo de vida independiente.
Lograr la independencia de los microservicios es clave para beneficiarse de las ventajas de la arquitectura. Esto exige un profundo entendimiento del dominio funcional, lo que se logra mediante DDD.
Por otro lado la arquitectura hexagonal nos permite estructurar el software de manera que la capa de código relacionada con el dominio funcional no se vea interferida por aspectos tecnológicos, es decir, que dicha capa sólo exprese el Ubiquitous Language, es decir el lenguaje del modelo en según lo llama DDD.
Dicha separación en capas y el invertir las dependencias permite además garantizar la máxima portabilidad del código.
¿Qué vamos a ver?
1. Beneficios
2. Domain Driven Design.
- Conceptos - Big Picture.
- Conceptos - Code architecture.
- Event Storming.
3. Clean Code Architecture.
- Hexagonal Architecture.
- Onion Architecture.
Bots 3.0: Dejando atrás los bots conversacionales con Dialogflow.Paradigma Digital
Atención personalizada y automatización de operativas con IA de forma sencilla con DialogFlow. Al terminar esta charla serás capaz de crear un bot con Dialogflow que solucione tareas sencillas.
En esta charla veremos:
- Cuales son las necesidades de negocio que satisface este tipo de soluciones
- Alternativas en el mercado
- Solución de la necesidad con DialogFlow
Ponente: Alex Asensio - Business Lead en Paradigma Digital
Pragmático y siempre enfocado a objetivos de negocio. Enamorado de la tecnología pero también con la forma en que entregamos software a nuestros clientes, basada en el "empirismo". Tech + Biz mano a mano es la fórmula de éxito que queremos compartir con ellos.
En esta nueva entrega sobre service-mesh veremos el que probablemente se convertirá en el producto de referencia: Istio.
Analizaremos las funcionalidades que aporta, su arquitectura interna, la integración con productos de terceros así como su repercusión
dentro de las arquitecturas actuales. Realizaremos algunos ejemplos para mostrar la funcionalidad y configuración
Ponente:
Abraham Rodríguez está especializado en soluciones cloud native con arquitecturas de microservicios, stack con el que ha trabajado en diversos proyectos. Apasionado defensor de todo lo relacionado con cloud, metodologías ágiles, software libre y devops.
En esta presentación hablamos de Linkerd, uno de los pioneros en el ámbito de las "arquitecturas Service Mesh". Haremos un repaso por la historia de este producto, conoceremos sus principales funcionalidades y tendremos una parte práctica en la que mostraremos su integración en arquitecturas distribuidas junto a Docker y Kubernetes.
¿Cómo hago que mis APIs sean usables?
A través de un ejemplo desarrollado en Spring veremos como realizar todo el proceso de diseño aplicando un conjunto de buenas prácticas que te ayuden en el proceso de toma de decisión a la hora de enfrentarte al diseño de APIs.
En este meetup vamos a analizar uno de los pilares básicos en el proceso de transformación digital de las empresas: API Management. Para ello, explicaremos en qué consiste esta estrategia, y los diferentes conceptos y componentes que intervienen en la misma.Además, para completar esta visión con un caso práctico, mostraremos un ejemplo de implementación mediante uno de los productos OpenSource de API Management más exitoso del mercado: WSO2.
https://www.meetup.com/Microservicios
¿Cómo se despliega y autoescala Couchbase en Cloud? ¡Aprende de manera práctica!Paradigma Digital
En el pasado Meetup, presentamos Couchbase de manera general, pero ha llegado el momento de ir ahondando en los detalles del producto para conocer todas sus capacidades. Esto nos permitirá estar en mejor disposición para adoptarlo en nuestros proyectos.
En esta ocasión, se hablará de la capa de operaciones y despliegue de Couchbase aunque no con un enfoque tradicional en máquinas físicas, sino siguiendo las buenas prácticas del mercado. Explicaremos y haremos el despliegue en Google Cloud con escalabilidad horizontal elástica y automática.
Para llevar a cabo esto haremos uso, entre otras, de las siguientes tecnologías: Google Cloud, Kubernetes, Python y, por supuesto, Couchbase.
Pondremos a prueba nuestra infraestructura con una pequeña aplicación, si queréis ver los resultados, no os lo podéis perder!
Google Analytics es una herramienta de analítica la que se conoce sólo una parte de su potencial. Además de medir audiencias y su comportamiento, Google Analytics permite priorizar las inversiones en marketing online, recoger comportamientos de Single Page Applications y visualizar datos offline, por ejemplo de CRM y combinarlos con los de visitas online. También es posible recoger datos en tiempo real de ventas, por ejemplo de ecommerce y de dispositivos físicos como bluetooth beacons. Las funcionalidades de Google Analytics, en combinación con Big Query y otros servicios de Google Cloud Platform, la convierte en una de las plataformas más interesantes de analítica para la transformación digital.
Si quieres ver el vídeo en el que fue usada esta presentación, pulsa aquí: https://www.youtube.com/watch?v=2mfIU-NXGXI
Para ver la convocatoria en nuestra web, clic aquí: https://www.paradigmadigital.com/eventos/usar-google-analytics/
La convocatoria a través del grupo de Meetup.com, clic aquí: https://www.meetup.com/es-ES/Front-end-Developers-Madrid/events/231793469/
¿Cómo definir el roadmap de transformación digital? En Paradigma llevamos más de 20 años ayudando a grandes compañías en su camino hacia la digitalización.
Esta presentación nos muestra qué es la programación reactiva, en qué consiste, qué nos permite hacer y por qué está tan de moda. Además, podemos ver el uso concreto de esta programación utilizando RxJava.
Autor: Juan Pablo González de Gracia.
En Paradigma creemos que los grandes dragones digitales han desbancado a las empresas tradicionales. La clave para combatir esos dragones es la transformación digital.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
2. Big Data
Is it a real need or just trendy?
Why does it apply to my case?
3. Petabytes: Google 300 PB, facebook: 45 PB, Yahoo! 180 PB
Exabytes: U.S. healthcare
Zetabytes: 2011, 1.8 ZB created. World Information 9.57 ZB
YottaByte, Brontobyte, GeopByte to be reached
I do not have such a big volume of data
A big European company = Terabytes
4. But could or will have it:
Ever increasing amount of data, and more
heterogeneous:
Ubiquity, mobility, geolocation, social
networks, internet, sensors, M2M
CRMs, Call Centers, Emails, Documents, logs,
voice…
5. "There were 5 exabytes of information created by the entire world between the
dawn of civilization and 2003. Now that same amount is created every two days."
Google Ceo Eric Schmidt
6. Unstructured or semi structured data, equal to 85% of available data,
is not used by companies
This represent the new Fuel for companies
7. 83% of the surveyed companies were
able to do things with Big Data that
seemed impossible to achieve before
“The art of possible”
“Impossible is not a fact, it’s an opinion”
8. Value and real ROI are the best KPIs
•Increase of client acquisitions
• Increase in sales
• Resource optimization
• Customer loyalty
15. Extract value from data in any point of their life cycle
• Past: Stored data, Batch
mode
• Present: Current data
flows, Real time
• Future: Data and future
actions, Predictive
16. Big volume of data
Get value from Unstructured data
Get value from external data
Need for time or cost processsing reduction
Need for Data streaming analysis in real time
Algorithms, prediction or interactive analysis
Transform data into insights and value
Transformation to a Data driven company
20. Iterative and Cyclical
Choose a particular use case with a clear ROI
and time and budget limits
vs Big Bang
Avoid building a Big Data generic system and
then implementing projects over them
23. CUSTOMER SOLUTION
Big Data 2.0
∙
Up to 100x faster than Big Data 1.0
∙
Interactive analysis
∙
NoSQL with SQL Interface
∙
No need to change previous way of work
24. Which technology?
BIG DATA 2.0
Stratio
Cloudera Impala
Cloudera CDH4*
BIG DATA 1.0
NoSQL
Stream Processing
Hortonworks HDP*
EMC Pivotal HD
VoltDB
Storm
Microsoft HDInsight
C-Store
Apache HBASE
MapR Apache Drill
Espresso
Apache CouchDB
Scribe Aurora
SQLStream Platform
Cassandra FS
Apache HDFS
Open Source
Google Big Query
IBM Inphosphere Biginsight
Datastax Platform
Hadapt platform
Basho Riak
VMWare Redis
HP Vertica
Hstreaming Platform
Apache Giraph
Amazon EMR _& Red shift
MapR M3-M5-M7
EMC Greenplum
Voldemort
Apache S4 Apache Flume Kafka
NEO Techonology Neo4j*
Almacenamiento
Intel Hadoop
Mencache
EsperTech ESPER
Graph database
Hortonworks Stinger
StreamBase Platform
IBM Inphosphere Streams
FlockDB
EMC Isilon OnFS
Closed based on Open Source
Closed
Apache Cassandra
25. From Big Data 1.0
Batch of new technologies that allow us to extract value out of a dataset which, due
to it’s volume, variety or velocity, was not previously exploited
To Big Data 2.0
“Set of new technologies that extract value from all the available data of a
company”
29. Antena 3, nubeox : Big Data Recommendation engine
Monitoring of Streaming Videos
Description:
Recommendation Engine based not
only in the purchase history of the
customer, but also in their navigation
Advantages:
Increase in clickthrough
Increasing Conversions
Increase in sales
30. Customizing Web Sites: Behavioural Customization
Description:
Customizing homepages based on user navigation
Analysis and customization of the homepage and site in
real time for each user based on their browsing
Modification of contents, highlights, ads, in real time
based on user history
Advantages:
Over 300% increase in clickthrough
Creating millions of web pages in real time
Increasing Conversions
Increase in sales
Cost ten times lower than other solutions
Recommended links
News Interests
Top Searches
+79% clicks +160% clicks +43% clicks
vs. randomly selected
vs. one size fits all
vs. editor selected
31. Personalized Marketing with DataShake integration
Description:
Newsletter development, email-marketing or any
other sent material segmented by individual
preferences
Analyzes and takes into account:
• Financial information and user data
• Navigation and usage information from previous
marketing shipments
• Mobile app data (GPS, payments, browsing of
offers…)
• Users’ information from the social networks
Advantages:
Increased clickthrough
Increase in conversions and sales
Natural language processing – semantics and
sentiments
Combines private and public data
32. Complement private structured data with unstructured and
public data
Description:
Complementing the internal data of a company by
combining the structured and the unstructured
data, with the data generated by the web and
social networks, allows us to determine the validity
of the data of our brand, product or company.
The comparison and analysis of internal and
external data (web) increases the value of our data
and allows us to gain a competitive advantage over
our competitors.
Advantages:
It allows sales improvement.
Improves loyalty.
Increases Conversions.
Detects errors or data manipulation.
SEO improvement with regards to the users and
the public data.
Improves marketing and product boosting with
regards to trends.
Big Data
Page 32
33. BI and data analytics
Description:
Creation and/or complementation of BI systems and
data analytics
ETL tools and data uploading with a much higher
volume than the traditional ones
Capacity for analysis and visualization of all types of
data, including graphs and new data types
Advantages:
Ability to work with larger datasets without the need
to add or delete
Much faster and reliable systems
Massive reduction in cost (M € versus k €)
Natural language processing – semantics and
sentiments
A possibility to combine internal data with external
data (private and public data)
34. Telefónica Dynamic Insights (Smart Steps)
Description:
Collect mobile data, anonymised and
aggregated, to understand how segments of
the population collectively behave. Trace
trends and the behaviours of crowds, not
individuals. Use this insight to enlighten the
space between organisations and their
users, enabling them to improve their
propositions, and businesses.
Focus:
By being able to measure real behaviour, in
near real-time, 24/7, 365 days a year, we
can show the actual impact on society,
therefore enabling businesses and local
government to make better decisions.
35. Security and fraud detection
Description:
Analysis of large volumes of data, logs, security
systems, transactional systems
Faster correlation mechanisms and machine learning
algorithms allow early detection of attacks and
security risks with extra care to false positives
Internal fraud detection analyzing data and events
from applications and risk operations
Advantages:
Combines data from transactional systems with the
SIEM to help fight fraud
Tracks and identifies new fraud methods and trends
via user reviews
Fraud detection techniques specified through the use
of built-in patterns
Much larger data volumes and much higher velocity
Combines private and public data
36. M2M IoT: PARK AIR SYSTEMS
NORWAY (RMMS)
Description:
The Remote Maintenance & Monitoring System
(RMMS), provide a powerful, scalable and flexible
SCADA system to perform and wide range of tasks
required by CNS agents such as maintenance,
supervision, configuration and operation.
Integration of different systems and equipment shall be
possible and straightforward using open standard
protocols, real time monitoring, data storage, testing,
reporting, events notification,…
Focus:
The main task of the RMMS is to provide complete
access to the equipment supervised in order to monitor
every single available parameter as a mean of avoiding
personnel mobilization to the remote location.
Different levels of control over the system are also
provided to cover the requirements of supervision,
maintenance and control.
Five main elements compose the RMM system:
• RCSU: Remote Control and Status Unit.
• TP: Tower Panel.
• RMM: Remote Management & Monitoring.
• LMT/RMT: Local / Remote Management Terminal.
• CMMS: Central Management & Monitoring System.
37. Search Engines
Description:
Big Data Search Assist: Search engines optimized for Big
Data with self-learning improvements based on use
Search engines for websites, intranets, apps
With instant real-time search, single box with natural
language processing, suggestions, highlighting,
automatic corrections, “you wanted to say” tips, etc ...
Advantages:
Easy management for business users: Order of results,
filters, etc ...
Advanced features of the search engines with a cost ten
times lower than other solutions
Improved performance and scalability compared to
other solutions
Easy to integrate and use
38. ORM and social dialogue
Description:
It gives a full 360 º of a company or brand online,
showing a tool that integrates the three aspects that
define your actual online image:
How am I doing on social networks?:
Do I know how to usevfacebook, twitter, google +,
youtube, linkedin? How many followers do you have,
are you an influencer, do you generate content that
spreads out?
What is my presence and reputation on the Internet:
When it comes to me, how do people talk about me,
what is said, how does it evolve over time, what is my
position on the Internet regarding my competitors in
the different aspects that interest me.
SEO:
Simple and practical analysis of both internal SEO and
external SEO to complement and give an integrated
view of the above aspects of reputation and social
dialogue.
Advantages:
Real improvement of the company or the product by
analysing the evolution over time of the three major
aspects that define your online reputation.
It improves the negative aspects, and reinforce the
positive ones.
Increase in sales: Helps optimize and follow
marketing campaigns and improve sales.
Improving conversions and attracting new customers.
39. Social Mining
Description:
Analyzing various social networks and
movements, looking for brand penetration,
identifying influencers in conversations and
a static map of associated terms.
Advantages:
Entering the social dialogue and hot topics at
the right time multiplies by 100 times the
viralization
View how a social network moves as time goes
by
Allows to know what that the user is talking
about when referring to my products or my
brand.
Detection of influencers and detractors
Optimal visualization of the information.
Identification of the tags used most frequently
by the network to improve your SEO.
40. Social Network Tracking
Description:
Search the social network comments and
mentions of interest of a particular issue or event
for further evaluation, influencers detection and
graphical display of the conversation to facilitate
analysis.
Advantages:
Show real-time event (symposium, forum,
seminar, etc..) with visual information.
Get opinions and feelings about a topic in social
networks in real time
Identify the influencers of a hot topic
Risk detection and prevention
Emotional mining: Know the term that is most
popular for some people, brand, event, etc.and
this way you can know about the generated
feelings by the most important terms.
41. Web Content Scraping
Description:
Search the network content and publications on
specific subjects of our interest, to detect, filter,
collect and process relevant information in semireal time or batch.
Associated with the semantic analysis this allows
the detection and classification of the contents
effectively.
Advantages:
Allows the generating of sites in a dynamic way
without any intervention or exhaustive searches,
with the contents collected and categorized.
Unifies in a single web all the tasks that users have
to do manually, so it saves them money and
generates loyalty.
42. Tele5: Monitoring of logs for Streaming Videos
Description:
Monitoring the download and
streamming of videos.
Analysis of streaming
Quality of streaming
Peaks of service and bottle neck
Advantages:
Problems detection and alerts
Optimization of service
Tracking of campains
43. Massive information tagging
Description:
Allows you to label and categorize automatically and
massively, any type of content or information.
Advantages:
Allows searching, categorization, clustering, and be
able to extract value out of information otherwise
hardly findable and usable.
Utilizes state of the art tools to identify entities, NED
systems, NERD. These tools combined with the use of
disambiguation of entities using a Big Data system
containing the Wikipedia and other sources of
information.
Speed processing capabilities and data volume
superior to that of other systems.
45. Is not about Big Data, is about getting maximum value from data:
Get all the value data can give
Process and analyze new types of data: Unstructured, semistructured, streams of data
Convert data into big insights
Become a Data driven company
46. “the best way to predict the future is to create it”
Hilo de la presentación:TESIS----------Aparación de Big Data 2.0 (cambioedparadigma Big Query)Requerimientos: 100XNecesidad de arquitectura NO-HADOOP paraconseguirestosrequerimientosOPORTUNIDAD------------------------Dado quees la únicaplataforma NO-HADOOP open source, si la tesisescorrectaserá:The Open Source Big Data 2.0 Platform
A technological Change from Big Data 1.0 to Big Data 2.0, from Batchanalysis 12 years old technology Batch analysis, to interactive analysisstate of the art.Este proyecto se basa en la tesis de que se estáproduciendo un cambiotecnológico en el mundo de Big Data, querequiere un mayor rendimientocon capacidades de analisisinteractivo y capacidades de queries entiempo real. Se requiere un rendimiento 100X superior paraconvertir enunospocosminutoslashorasque se necesitaban con lastecnologíasanteriores.Para conseguirestascapacidadesesnecesarioabandonarhadoop, cuyaarquitecuraestálimitadaporconceptos con 12 años de antiguedad, comosunecesidad y dependendia de la persistencia en disco, y escrituras nooptimizads, que no permitiráalcanzar los requerimientos de 100XPerformace.En lugar de sin seguir con retraso los pasosya dados porotros, Stratiodesarrolla y proporciona la únicaplataforma Big Data open source nobasada en hadoop, creando y definiendonuevosparadigmas y posibilidadesquehanpermitidorealizarunaarquitecturaintegradaúnicatotalmenteconcebidapara el máximorendimiento 100X requeridoactualmente,adaptable, y sin vendor lock-in.