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La evolución de la analítica descriptiva

Summit
September 05, 2018

La evolución de la analítica descriptiva

Transformando reportes en historias.

Summit

September 05, 2018
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  1. IBM Business Analytics :: IBM Confidential :: © 2016 IBM

    Corporation Transformando reportes en historias Diego Aguirre Data Science & Business Analytics Client Leader, Spanish South America BIG DATA Summit, Lima. 25 de Agosto de 2018 La evolución de la analítica descriptiva
  2. 2 IBM Business Analytics :: IBM Confidential :: © 2017

    IBM Corporation Agenda Analítica Descriptiva Un poco de historia Situación actual Desafíos Qué es lo que viene?
  3. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation IBM Confidential :: © 2017 IBM Corporation Ciclo de vida de Analítico: Que es la analítica descriptiva?
  4. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 4 Un poco de historia – La Evolución
  5. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 5 Un poco de historia – La Evolución 80s. - Principios 90s Reportes a medida Código estático Lenguaje programación + Lenguaje de consulta Experiencia limitada Alto costo
  6. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 6 Un poco de historia – La Evolución BI tools Usuarios de negocio construyendo reportes Capacidades limitadas Herramientas complejas y poco flexibles 1995 - 2000
  7. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 7 Un poco de historia – La Evolución Dashboards Mejora la experiencia Se mantiene el alto costo BICC Dashboard / Scorecard: Son diferentes 2000-2010
  8. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 8 Un poco de historia – La Evolución 2010- Hoy Self Service Indepencia de IT Power users generando su propio contenido Democratización Fácil de Mantener Experiencia superior
  9. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 9 Self Service - Definición “Self-Service Analytics is a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.”
  10. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 11 #1 - No todo es self service “The irony of self-service analytics is that it requires standardization.” Business Users “Many companies that have deployed self-service analytics have become inundated by a tsunami of conflicting reports, spreadmarts, renegade reporting systems, and other data silos.” Data Scientists 2% Usuarios Casuales (Executives, managers, front-line workers) 90% Power users Su función es analizar 10% “Many companies that have deployed self-service analytics have become inundated by a tsunami of conflicting reports, spreadmarts, renegade reporting systems, and other data silos.” 11 Source: Chart data and quotes from “Eckerson Group: A Reference Architecture for Self-Service Analytics”, Wayne Eckerson, Barry Devlin, September 2016 Exploradores de Datos 30% Consumidores de datos 60% Data Analysts 8%
  11. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 12 Enterprise Reporting + Self Service Managed Reporting • Data presentation • Value add by managing the: • Security and Governance • The integrity of the output • Efficient distribution of the output Self-service (Dashboards, Stories) • Data exploration (ad-hoc) • Primary use cases • Answering questions • Brainstorming /socialization of ideas and concepts • Prototyping Platform • Enterprise architecture - security, scalability, integrity • Managed reporting and self service LOB user Skilled user (Power/IT)
  12. 13 IBM Business Analytics :: IBM Confidential :: © 2017

    IBM Corporation • Los análisis “self service se reducen” a un subconjunto del universo de datos bien conocido por el analista. • La construcción del análisis está influenciada por los conocimientos del analista (acerca del negocio) y el conocimiento de la herramienta. #2 Sesgo Data consumers
  13. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 14 1 4 Smarter Self Service • Análisis guiado • Sugerencia de visualizaciones (a demanda y proactivas) • Preguntas y respuestas • Identificación de correlaciones • Análsis diagnóstico basado en capacidades cognitivas Smarter Self Services IBM Business Analytics
  14. 15 IBM Business Analytics :: IBM Confidential :: © 2017

    IBM Corporation #3 Usar el lado derecho del cerebro
  15. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 16 La evolución del Self-Service S m a r t e r D a t a D i s c o v e r y G o b i e r n o y E n t e r p r i s e R e p o r t i n g C r e a t i v i d a d
  16. IBM Business Analytics :: IBM Confidential :: © 2017 IBM

    Corporation 17 La evolución del Self-Service: Cognos Analytics