Simplificando el uso de los datos para la era cognitiva - Daniel González
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Simplificando el uso de los datos para la era cognitiva - Daniel González
- 2. Simplificando el Uso de los Datos para la Era Cognitiva Daniel González Banda – Especialista de Big Data & Analytics, IBM México
- 3. Los negocios digitales están cambiando a las industrias y a las profesiones son vulnerables al cambio en tres años 72%
- 4. Cloudant & Graph dashDB Watson Analytics Watson Personality Insights Provee experiencias personalizadas Descubre insights y provee nuevos servicios Entiende a profundidad a tu comunidad Saca provecho de las capacidades cognitivas para mejorar tu relación con clientes Runkeeper marca el paso en experiencias personalizadas con un enfoque de “Open for Data”.
- 5. ¿Qué es lo que nos está deteniendo? son incapaces de colaborar con datos sencillos 80% requiere de datos y analíticos más rápidos para ser competitivos 9 10más de de dice que los datos fragmentados son un estorbo 84%
- 6. Modernización Reporteo & Data Warehousing Eficiencia Operaciones Explora un modelo de transformación para obtener mayor valor Valor Madurez Analítica de Autoservicio Democratización Monetización Nuevos Modelos de Negocio
- 7. ¿En qué etapa de madurez de datos se encuentra su organización? 1. Operaciones 2. Data Warehouse / Reporteo 3. Analítica de Auto-servicio 4. Nuevos Modelos de Negocio
- 8. Analítica de Autoservicio Democratización Explora un modelo de transformación para obtener mayor valor Valor Madurez Eficiencia Operaciones Modernización Reporteo & Data Warehousing Monetización Nuevos Modelos de Negocio La mayoría se encuentra aquí
- 9. La transformación trae un cambio en expectativas “Datos Simples y Accesibles” Remueve silos creados por los sistemas y herramientas . Innova con la comunidad y código abierto. Auto- servicio confiable y seguro. Impulsa inteligencia más rápido que antes.
- 10. Nuevos profesionistas de datos al frente Profesionistas de negocio Ingeniero de datos Desarrolladores de aplicaciones Científico de datos
- 11. Nuestra misión Simplificar el uso de los datos y hacerlos accesibles para todos.
- 12. IBM Watson Data Platform La primera plataforma de datos y analítica para los Negocios Cognitivos Plataforma Ecosistema Metodología http://ibm.co/makedatasimple
- 13. IBM Watson Data Platform Experimenta nuevas formas para utilizar los datos Ingeniero de Datos Científico de Datos Analista de Negocios Desarrollador de Aplicaciones Abierto Inteligente Híbrido Experiencias tareas específicas, colaborativo Servicios de Datos y Analítica comprehensivo Plataforma
- 15. TRUSTED PARTNERS COMMUNITY ACCEPTED OPEN STANDARDS IBM Watson Data Platform Ecosistema de Asociados IBM Watson Una comunidad abierta para innovar más rápido mediante el uso de los datos Ecosistema
- 16. La metodología de IBM DataFirst representa nuestra experiencia para llevarte al lugar donde necesitas estar Comienza en cualquier punto Enfócate en tus oportunidades de negocio más grandes. Llena los huecos Estrategia. Experiencia. Habilidades. Ni más, ni menos. Valor en cada paso Alcanza una cultura alrededor de los datos. Una iniciativa a la vez. Presentando la metodología Data First Metodología
- 17. Analistas de Industria, Clientes, y Asociados, apoyan la visión de Watson Data Platform "What makes this compelling … is to span data silos with collaboration, overcome data-quality woes with shared data governance and metadata management and to overcome the complexities of deploying and maintaining myriad technologies with a cloud-based platform.” Doug Henschen, VP and Principal Analyst Constellation Research "We're pleased to welcome IBM to the R Consortium. IBM is a longstanding contributor to open source software and has immense expertise in data analytics and computing. Hadley Wickham, Infrastructure Steering Committee Chair R Consortium “IBM has been by our side throughout the journey and has brought deep data, analytics and managed services expertise to ensure that our business and our data is secure and protected in this fast changing world.” Raf Cinaglia, Chief Information Management Officer Macquarie Group
- 18. Visita nuestro sitio IBM Analytics Technology para mayor información Regístrate para cualquiera de nuestros servicios en bluemix.net Explora la metodología DataFirst en un Workshop inicial ¿Estás listo para comenzar? http://ibm.co/makedatasimple
- 19. ¿Cuenta su organización con una estrategia de datos estructurados, semi-estructurados y no estructurados? 1. Si 2. No
- 20. ¿Tiene su organización alguna solución en la Nube? 1. Si 2. No
Notes de l'éditeur
- DIGITAL BUSINESSES ARE DISRUPTING VIRTUALLY EVERY INDUSTRY AND PROFESSION The world’s largest accommodation provider owns no real estate. The world’s most valuable retailer carries no inventory. The world’s largest taxi company owns no vehicles. The world’s most popular media owner creates no content. The phenomenon is REAL. And Business leaders have told us this. In a recent IBM Sponsored study with Harvard Business Review, 72% of Global Line of Business leaders told us they were vulnerable to disruption WITHIN 3 YEARS from digital business and in particular the concept of digital intelligence – the ability to leverage data and digital technologies to understand the customer, sense markets shifts, and innovate faster than the competition. Yet only 23% say they can respond to new threats or capitalize on new opportunities Three years is not very long. Amidst this change – how do you cope?
- OK, so we all see the value here – 92% of LOB’s do based upon our IBM/HBR study. But what is keeping us from moving ahead? Your business colleagues told us: 80% are unable to collaborate on common data – specifically the idea of marshalling teams together to work on a core set of data inhibits intelligence use of data. Teaming across the organization to drive more intelligent use of the data is what the business leaders are demanding. 84% say fragmented data gets in the way – data access across all functions is one of the main themes we saw coming across in this study. More fragmentation – means more time – more time wasted. Finally more than 90% require speed – speed to COMPETE. They recognize disruption is happening – speed is a competitive advantage – and IT needs to deliver the speed and agility that LOB see has holding them back.
- As we have engaged organizations around the world in every industry to understand how they use data, we realized when it comes to data, the rules of the game have changed. We believe forever. And we are reinventing it. Value is shifting from how data is stored to how easily data is accessed. As organizations mature, there has been a shift in expectations. To enable true innovation, we must enable:emove silos created by systems & tools Value generation from collaborating together to create the insights that help you drive better decisions and create smarter apps. We must break down the silos that exist today. rust & security Leveraging the cloud and the innovation it a need to access multiple data sources and have easy self-service access of those data sources. Not only that, but providing the necessary integration and governance to ensure that data trusted data and that you’re gaining accurate and valuable insights from it With paygo models independent of a traditional IT buying process community Making it easy for data professionals to access open source technologies and the ideals and take advantage of the innovation of a broader community as well as contributing back to that community so it continues to grow. Finally, with as much data as we have, it is no longer enough to use one analytic technique at a time. Value is from being able to mix and match the right combination of algorithms, machine learning and cognitive to easily arrive at the best possible insight. Then being able to iterate and provision quickly and continually improve the results.
- As we make data more accessible throughout the organization, we see certain roles within begin to surface as crucial for successful exploitation of data and analytics. Specifically, these individuals across the organization need to transform to inject speed and agility into the organization. Successful progression requires these roles to be empowered with the right set of capabilities, and the right culture so they can make an impact to the business. For example: Business Professionals need easy ways to discover data, and experiment with data thru algorithms and visualizations. Application Developers use a range of data services and integrate models to build apps that drive business innovation and competitive advantage. They require a toolset that ensure secure application development or deployment in the cloud. Data Engineers seek to maximize the ability to become more data-driven and look for simplified data management and governance as well as ensure they are equipped with the right capabilities can work with everything they’ve built so far. Data Scientists are challenged by the requirements for their in-demand skills from across the organization and need to produce value from all data sources they have access to… Like scientists in the physical realm, they too need to form and test hypothesis, experiment, test some more, learn and iterate- but they have to do it at the speed of business. The number of data scientists has doubled over the last four years Getting all of these groups working together more easily can speed time to insight and results. Today, that is really hard. Ideally a business analyst would identify the business problem and then collaborate with the data scientist to find the root cause and the solution. They have to work with the data engineer to get access to the data; the data engineer needs to connect the integrate the services as well as potentially cleanse it. For the developer building a reactive application, they are dependent on the data scientists to build a model and the data engineer to help get it into a production system. Lastly, the CDO needs to define the logical business object models so all of these groups can work together as well as ensure governance and control. * International Data Corporation (IDC) predicts that by 2018 for 181,000 people with deep analytical skills, and a requirement five times that number for jobs with the need for data management and interpretation skills. To put that in perspective it’s estimated there are less than 20,000 data scientists around the globe right now
- Data is the world’s new natural resource, and it is transforming all industries and professions. IBM has been building and acquiring the capabilities necessary to lead in data and analytics, deepening our industry expertise and growing partnerships and ecosystems. Today, our data and analytics business is the industry leader, generating revenue of $18 billion in 2015. Our mission at IBM is to make data simple and accessible to all. It’s no longer just about the data. It’s about how we put data to work to create more value and competitive advantage for your organization.
- To help you address the new needs of the organization and the different data-driven data professionals, I would like to introduce you to the the IBM Watson Data Platform. IBM Watson Data Platform builds on the path that IBM has been on to provide cloud-based data and analytics services over the last two years. -IBM started to build its cloud-native portfolio in 2014 with the acquisition of the leading No-SQL DB-as-a-Service company Cloudant. We followed that a year later with the acquisition of Compose that offers a scalable delivery and management platform in the cloud for the lead open source data management technologies and introduced our own Graph database service based on open source. -We also introduced a cloud-native data warehouse called dashDB, which we have extended to support on-premises/private cloud deployments as well as transactional workloads. -We have also made a strong commitment to serving the needs to open analytics and data science. IBM is the second largest contributor to Spark, we believe is The analytics operating system. We also introduced the Data Science Experience to provide a means for data scientists to easily access the tools they want to use as well as the ability to consume content and interact with a community. -Lastly, we have continued to make it easier to consume key data sources. We initiated an agreement with Twitter and we purchased The Weather Company. All of this investment has culminated in the Watson Data Platform which is the industry’s FIRST platform to integrate all data types for AI-powered decision making. This platform automates the intelligent deployment of data products on the IBM Cloud using Machine Learning and Apache Spark. It provides one environment for collaboration for everyone in your business. In addition to a platform, we also offer the DataFirst Method that provides the expertise and proven practices to ensure you get the most value from data. Lastly, IBM has also created an ecosystem of partners who build on open source to easily snap into the platform. We create Watson Data Platform to be open as we want our clients to be able to benefit from the best innovations that the industry as to offer.
- Let’s see how IBM Watson Data Platform all fits together. It starts with the collaborative workspaces for the data professional - The data engineers, data scientists, data developers and business analysts - We call these “Experiences” as they are not just new, self-service tools. Rather, they include content and a community infrastructure so data professionals can learn from each other and work faster and better by finding and sharing in a collaborative environment IBM Watson Data Platform also Individual Data and Analytics Services in the areas of Information integration and governance, Data Storage, and Advanced Analytics …. And these can be applied across the entire data and analytics lifecycle. It uses cognitive-assisted capabilities and machine learning to simply and automate the develop, deployment, and management of insights and models that power a cognitive business. So depending on the initial and long term needs of users, IBM Watson Data Platform was built to provide you with flexibility and speed of adoption needed to gain meaningful insights & transform your business.
- One of the core principles of IBM Watson Data Platform is that it is open. Its built on Open Standards with well respected organizations including Apache, ODPi, and now NUMFocus. Its built with Open Communities including Apache Hadoop, H2O.ai, R & Python, Spark and many more. Last, we have open partnerships meaning our partners integrated with IBM Watson Data Platform in a non-proprietary way and participate openly with other partners and clients. IBM Watson Data Platform partner ecosystem provides certified solutions based on the IBM Watson Data Platform to expand the data and analytics capabilities available to you. With the ecosystem you gain flexibility and choice of an open community with all the security, governance and cloud capabilities to innovate faster with data. More on the IBM Data Platform partner ecosystem The ecosystem is about expanding the value we can provide to clients by offering partner solutions that embrace open to be part of the IBM Watson Data Platform value. Today our partners fall into 3 categories: standards organizations, e.g. AMPLab, R Consortium, Apache open source software projects, e.g. Spark, Python, Docker, OpenStack software and service providers, e.g. DataBricks, WanDISCO, Lightbend, Galvanize As we go forward, we are looking to extend the next wave of partners with our DataFirst Method.
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