GoData Analytics

278 visualizaciones

Publicado el

PowerBI, Advanced Analytics

Publicado en: Datos y análisis
0 comentarios
1 recomendación
Estadísticas
Notas
  • Sé el primero en comentar

Sin descargas
Visualizaciones
Visualizaciones totales
278
En SlideShare
0
De insertados
0
Número de insertados
4
Acciones
Compartido
0
Descargas
7
Comentarios
0
Recomendaciones
1
Insertados 0
No insertados

No hay notas en la diapositiva.
  • Key goal of slide: Demonstrate the difference between 1854 and today. Acknowledge the challenges presented by today’s era of big data – but demystify it at the same time – it’s simply driving us to a tipping point.
     
    Slide talk track:
    Now, you may say, that's great, that's a story from the 1850s. The amount of data that Dr. Snow had to process would fit in a notebook.
    We’ve got a whole new set of challenges with data being created faster than ever in human history – real-time data creation.
    Add to that the kinds of data we have to manage. It's not just sort of classic structured relational data in a nice column or a rectangular format, it's actually a blend of multiple types of data.
    That all means the volume of data is growing immensely. We’ve got a big data problem.
    Now, there's been some great market forces to help us deal with this along the way, such as the rise of the cloud and cheaper hardware that lets us store significantly more data than in the past so we can reason over much larger volumes.
    Add in user expectations – which are putting a lot of pressure on IT to deliver analytics on all data, and you’re really reaching a point – pressure point or tipping point depending on your perspective.
    All this momentum is gathering – data, economics, user readiness to consume and work with data. Users want to be able to get to an answer to their work questions as easily as they search the Web. And the good news is that YOU, IT, is going to be able to enable that in the not too distant future.
    Microsoft is investing heavily to simplify the world of data – dealing with the deluge to find the signal in the noise – and not just for specialists – but for everyone from marketing managers to IT professionals.
  • CLICK 1: For the first step along the data science process – or journey we’ll go on today – what’s key in your success here is getting EASY access to data, big and small, to drive the best business decisions. And we would assert that’s not just about IT’s access to data – it’s also very much about empowering end-users.
    CLICK 2: Now, the second stop on our journey -- how do you make it easier for the people closest to YOUR business to create a theory, model that theory, refine it and reveal those invaluable business insights? That's all about engaging more people at this second stage, again the people closest to your business, with powerful tools that they're familiar with – so there’s no learning curve. It’s just users and data – and if you can unlock this – you get to that magical point where insights are revealed.
    CLICK 3: And then finally, at the last stage of the data science process -- you need to be able to create repeatable business process that delivers insights automatically by deploying your “data science process” across a complete data platform. It can't just be about storing relational data, or it can't just be about storing unstructured data in a Hadoop cluster. It really does have to be about thinking about a more complete solution. You want that ROI on your data, and by operationalizing your data science process – you’re going to see those returns.
  • Ultimately – from end-users, business analysts, to BI pros, and data scientists – you want to enable them all – not just one. Because when you enable all of these people – you engage more people in analytics – you accelerate the time from raw data to insight across your company.
    You need to drive adoption of the right tools to all users, not just BI experts or Data Scientists in a collaborative way and on any device. Through familiar tools like Excel and SharePoint, we enable all users to analyze and make collaborative decisions on structured and unstructured data. Through the Hive ODBC Driver, there is now easy and direct access from the end user tools to Hadoop data from traditional services like SQL Server Analysis Services.
    Let’s dig in a little… stop for a minute – and picture Excel in your minds. What image comes into your head? Probably Excel from years past – spreadsheets with tables? If that’s the image in your head, then think back to the demo we just walked through. That’s Excel today. With the BI add-ins for Excel and SharePoint, powerful analytics and collaboration tools for everyone are ready and waiting.
    In fact, Power View and Power Pivot both represent our investments in putting our best BI technology in Excel to make it accessible to everyone. And it allows you to do amazing visualizations that make it possible for you to look at your data in new ways – that makes insights and data analysis accessible to all users -- from the least sophisticated to the most.
    One of the most common pain points we hear from IT and end users about BI is the classic problem – a repeating loop that never ends. The business asks IT for data. IT produces the data and gives it to the business. The business asks for more cuts, and the request goes back into the queue. IT has to pull together a new cube and another analysis. A week later, the business gets it, but says it’s almost right, but it’s missing these three things. The whole process starts over again. How many people have been on that cycle?
    Power View and Power Pivot are all about bringing that full, self-service BI power into Excel so users can do that analysis, and they can cut and slice and dice rather than constantly coming to IT for that service.
    Power View (an interactive data exploration, visualization, and presentation experience that encourages intuitive ad-hoc reporting) is available in Microsoft Excel 2013, but it’s also a feature of SharePoint Server 2010 and 2013 as part of the SQL Server Reporting Services.
    Power Pivot is a powerful data mashup and data exploration tool. Again, thinking about the notion of accelerating time to insight, we’ve continued to integrate in-memory technologies right into our products. Power Pivot has in-memory built in so it delivers super-fast analytical performance – processing billions of rows in seconds.
    Once users complete their analysis, they can publish the results to SharePoint or a Power BI site so that the data can be shared by everyone. Just having the finance director know the data and see the analysis is not enough for most companies. You want to push it out to your organization, and then refine that with external data.
  • SUGGESTED DEMO:
    Demo featuring Power Query in Excel 2013. Demonstrate finding, and combining data from various sources – big and small. Also recommend pulling external data from Windows Azure Marketplace.

  • Key goal of slide: Transition to deeper into the first stage of the data science process – FIND, COMBINE & MANAGE
  • Let’s think about that first stage of the data science process – Find, Combine & Manage data with a more current story about data – and one that addresses much bigger data volumes.
  • One of the components, and we’ll show this in a few minutes, that was recently released for Excel is called Power Query. And what Power Query allows you to do is search and find data, both internally and externally - all within Excel. We think this is really powerful because it allows those end users then to find the data they need to do analysis.
    And that's one of the hardest problems frankly with starting a data analytics project is finding the data that's interesting to the problem or question you have. And it's not only the data internally, but it's also the data externally. So that's an important investment area for us is bringing together internal and external data.
    Of course, I may want to combine what is say structured data today in my CRM system with unstructured data that I might be managing or processing in say a Hadoop cluster.
    Microsoft has made very big investments in Hadoop, and their partnership with Hortonworks delivers and ensures that their Hadoop distribution is always 100% Apache moving forward. What this means for us is that it helps future-proof any investments that you might make in this area.
    SQL Server has historically been very strong around data management. Data management needs have evolved from traditional relational storage to both relational and non-relational storage. You need an information management platform that supports ALL types of data.
    To deliver insight on any data, you need a platform that provides a complete set of capabilities for data management across relational, non-relational and streaming data while being able to seamlessly move data from one type to another and being able to monitor and manage all your data regardless of the type of data or data structure.
    There is also new technology coming called PolyBase, which allows you to query over both structured and unstructured data, seamlessly & very quickly, thanks in part to built-in, in-memory innovations.
    As we see all of this moving forward, it's not just about the data that you have today within your environment – which of course is really, really important data, it's probably the most valuable data you have -- but combining that with external data or unstructured data is really the where magic happens and things become very interesting.

    OPTIONAL TRANSITION: And it’s by leveraging all this advanced technology from Microsoft, building on their platforms/services, that we can extend innovative data solutions tailored to the specific needs of our customers.
  • Moving on to the second stage of the data science process – where you form theories, analyze & refine them – this time, I want to focus on a story from the financial services industry.
  • Power Pivot da el empoderamiento a los usuarios para crear modelos de datos BI en Excel; maneja eficientemente grandes volúmenes de datos a través de un algoritmo de compresión de datos en memoria que permite cargar millones de registros y garantizar tiempos de acceso y consulta a la información casi inmediato. Se trata de una ventana nueva asociada con el libro de Excel en el cual el usuario analítico puede modelar sus datos, crear relaciones, crear jerarquías, crear nuevos campos calculados; se considera como la versión de SSAS en el lado del cliente.

    Adicionalmente existe la versión de powerpivot para Sharepoint 2013 el cual añade a las características anteriormente descritas las funciones de colaboración y gestión documental; en sharepoint existe una librería denominada powerpivot gallery la cual permite cargar y publicar los libros de powerpivot
  • OPTIONAL SLIDE: Screen shots of Excel 2013 featuring Power View and Power Pivot for visual representation of solutions if demo isn’t possible, or if needed to address specific points.
  • Power View es un herramienta que permite realizar análisis asociatativos visuales y que enriquece la experiencia de presentación de los reports a través de elementos de información habilitados para interactividad y diseñados con con un alta calidad de diseño visual. Entre estos elementos podemos citar mapas bing, graficos burbujas en el tiempo, pie charts,
  • OPTIONAL SLIDE: Screen shots of Excel 2013 featuring Power View and Power Pivot for visual representation of solutions if demo isn’t possible, or if needed to address specific points.
  • Utilizar mapas en Bing y visualizarlos en diferentes capas al mismo tiempo.
    Incorporar graficos de colunas , burbujas, mapas de calor en 3 dimensiones
    Ver los datos en el tiempo
    Hacer comparaciones directas con mapas en 2 dimensiones
    Capturar escenas como slides shows

  • Key goal of slide: Transition to deeper into the first stage of the data science process – FIND, COMBINE & MANAGE
  • OPTIONAL SLIDE: Share insights about your data, find answers, and stay connected from anywhere with the web-based and mobile capabilities of Power BI for Office 365.

    Quickly create collaborative BI-optimized workspaces in Office 365 to share BI worksheets with colleagues, collaborate over insights and results, and quickly find the data you’re looking for.

    Access your BI from any device, anywhere using an HTML5-compatible browser, or through mobile BI apps.
  • GoData Analytics

    1. 1. Big data no esta conduciendo a un punto de inflexión
    2. 2. Las soluciones construidas con tecnología Microsoft
    3. 3. Brinde a sus usuarios poderosas y familiares herramientas de BI
    4. 4. Power BI, Sql Server y Sharepoint Analizar Visualizar Compartir Responder Q&A MovilidadDescubrir Escalable | Administrable | Confiable
    5. 5. Nuestra Visión
    6. 6. Nuestra Visión
    7. 7. Customer Intelligence Gestionar el Valor del Cliente en su ciclo de vida Identificar y Adquirir los Clientes Correctos1 Desarrollar y Rentabilizar los clientes actuales2 Crear Lealtad y evitar deserción de los clientes 3
    8. 8. Customer Intelligence Gestionar el Valor del Cliente en su ciclo de vida
    9. 9. Customer Intelligence Customer Intelligence Gestionar el Valor del Cliente a través de Modelos Analíticos
    10. 10. Customer Intelligence las soluciones
    11. 11. Valor Actual del Cliente Customer Intelligence Deserción de Clientes Cross Sell y Up Sell Adquirir Clientes Correcto Valor Potencial del Cliente Segmentación Deserción Marketing Operacional Visual Analytics Customer Intelligence Soluciones de Inteligencia de Negocios
    12. 12. Valor Actual del Cliente Customer Intelligence Deserción de Clientes Cross Sell y Up Sell Adquisición Valor Potencial del Cliente Segmentación Abandono Campaign Management Visual Analytics Advanced Analytics
    13. 13. Power Query
    14. 14. Fácil Acceso a los Datos
    15. 15. Fácil Acceso a los Datos
    16. 16. S Conexión a las siguientes fuentes Windows Azure Marketplace Windows Active Directory Azure SQL Database Azure HDInsight
    17. 17. PowerPivot
    18. 18. Poderosos “Insights” utilizando herramientas familiares
    19. 19. Poderosos “Insights” utilizando herramientas familiares
    20. 20. Power View
    21. 21. Powerful self-service BI with Excel 2013
    22. 22. Clean, transform, model, mash-up
    23. 23. Power Map
    24. 24. Powerful self-service BI with Excel 2013
    25. 25. Power Map es una add in Microsoft Excel que habilita a los trabajadores de la información a descubrir y compartir insights desde datos geoográficos a través de un historia en tres dimensiones Que es el Power Map?
    26. 26. Map Data • Datos en Excel • Geo codificación • Visualización 3D Descubrir Insights • Ver datos en el tiempo • Anotar puntos • Capturar escenas Contar Historias • Efectos Cinemáticos • Tours Interactivos • Compartir el libro Power Map: Pasos para realizer insights en 3D
    27. 27. Power BI Site
    28. 28. Colabore y permanezca conectado Q&A
    29. 29. Q & A
    30. 30. Colabore y permanezca conectado Q&A
    31. 31. Mobile BI
    32. 32. Colabore y permanezca conectado Q&A
    33. 33. Colabore y permanezca conectado
    34. 34. Capacidades disponibles para Mobile BI Soluciones de BI solutions en iOS, Android and Windows: • SharePoint Mobile enhancements • PerformancePoint Services • Excel Services • SQL Server Reporting Services “Ultimately, the new Microsoft mobile BI solution leads to more revenue for Recall and gives us deeper customer insight, helping us stay ahead of our competitors.” –Recall Records Management Company Gets Real-Time BI, Boosts Sales with Mobile Solution case study. Full Case study.

    ×