US$ 2.01B Possibilidade de aumento anual de receita se a média de negócios da Fortune 1.000 aumentar a usabilidade de seus dados em apenas 10%
1.000% retorno sobre o investimento para cada US$ 1 gasto em Analytics
Nucleus Research, Gartner, Fortune Magazine
As empresas estão perdendo novos sinais
Moderador
Notas de la presentación
Because today most companies are missing new signals that is hidden in this data and they are still looking in the rear view mirror at historical financial information to make key decisions (if any thing at all), like the Income Statement and Balance Sheet are at best rear-view measures of the top line and bottom line. They provide a snapshot in time of all that has happened, but very little, if any, indication of what is happening in the enterprise For example, an online retailer with a subscription model experiences a massive drop in stock price because of poor Income Statement results. Further analysis indicates that there was a dramatic drop in subscribers (Churn) in one of their most profitable segments. It would stand to reason that a pre-emptive pulse-check on the churn could have helped stem the bleeding and perhaps prevented the reaction on Wall Street. This churn is an example of a new signal that could have helped this one enterprise run its business more proactively rather than look for explanations with a rear-view perspective. IN addition, . The people who have information is a finite set of people in the organization – according to Gartner only 10% of the organizations are using analytics to make decisions…. This means 90% of your organization are making off the cuff decisions. According ot Gartner 75% of people will need analytics on a daily basis by 2020 If companies could make their information even 10% more meaningful – they could have an annual increase benefits of over $ 2b. And if that does not convince you to invest in getting real-time information to all decision makers in your organization – According to Nucleus Research, For every 1$ spent on analytics, can bring a 1000% return on investment – so you have the stats to know it is absolutely essential to make this investment.
E se você pudesse transformar novos sinais em valor de negócio?
:-) Brand Sentiment
360O Customer View
Product Recommendation
Propensity to Churn Real-time Demand/ Supply Forecast
Predictive Maintenance
Fraud Detection
Network Optimization
Insider Threats
Risk Mitigation, Real-time
Asset Tracking Personalized Care
Moderador
Notas de la presentación
Brand sentiment – By capturing and analyzing customer comments on Facebook, Twitter, and LinkedIn in order to improve customer experience and optimize campaign performance. Predictive maintenance – By analyzing a continuous stream of machine data diagnostics, you can predict when the performance of machinery is degrading or even worse potentially about to break down. Insider threats – By looking for anomalies hidden in data about user behavior, you identify suspicious behavior and pinpoint potentially high-risk employees Network optimization – By understanding usage patterns, and predicting customer trends, you can optimize your distribution network Propensity to churn – Maybe your business suffers from a customer turnover in a highly competitive market. How can you determine a customer’s propensity to churn, or in other words, a likelihood they will leave you as a customer so that you can offer new services or deals in order to keep them. Fraud detection – Identify purchases or insurance claims that may have a high probability of being fraudulent by analyzing not only the transactional information, but also electronic documents. Asset tracking – Track high value assets and identify abnormal behavior that may put assets at risk of loss, or identify inefficient usage that is costing your business money. Personalized care – Use advanced analytics to create personalized treatments for patients, such as how Mitsui Knowledge Industry offers personalized cancer treatment based on genome analysis
Entregar Aplicações de Sinais & Respostas para Internet das Coisas?
Detectar e analisar tendências de dados através da agregação de dados de sensores
Beneficiar de logística mais eficientes, transformando a distribuição de varejo
Aumentar a qualidade de vida através de edifícios, robôs, carros e cidades inteligentes
Smart Cities
Smart Automobile
Smart Equipment
Smart Logistics
Smart House
Smart Vending
Connected Cars
Moderador
Notas de la presentación
Brand sentiment – By capturing and analyzing customer comments on Facebook, Twitter, and LinkedIn in order to improve customer experience and optimize campaign performance. Predictive maintenance – By analyzing a continuous stream of machine data diagnostics, you can predict when the performance of machinery is degrading or even worse potentially about to break down. Insider threats – By looking for anomalies hidden in data about user behavior, you identify suspicious behavior and pinpoint potentially high-risk employees Network optimization – By understanding usage patterns, and predicting customer trends, you can optimize your distribution network Propensity to churn – Maybe your business suffers from a customer turnover in a highly competitive market. How can you determine a customer’s propensity to churn, or in other words, a likelihood they will leave you as a customer so that you can offer new services or deals in order to keep them. Fraud detection – Identify purchases or insurance claims that may have a high probability of being fraudulent by analyzing not only the transactional information, but also electronic documents. Asset tracking – Track high value assets and identify abnormal behavior that may put assets at risk of loss, or identify inefficient usage that is costing your business money. Personalized care – Use advanced analytics to create personalized treatments for patients, such as how Mitsui Knowledge Industry offers personalized cancer treatment based on genome analysis
Big Data Exemplos
Instantaneamente prever tendências de mercado e as necessidades dos clientes
Prever como volatilidade dos preços de mercado irá impactar seus planos de produção
Ver mudanças na demanda ou oferta em toda sua cadeia de fornecimento imediatamente
Monitorar e analisar todos os desvios e problemas de qualidade no seu processo de produção
Fornecer exatamente as ofertas e os níveis de serviço a todos os clientes
Ter uma janela continuamente atualizada em vendas futuras, mostrando alterações em tempo real
Entenda o que os seus clientes e potenciais clientes estão dizendo sobre você, agora
Predizer fluxos de caixa para gerenciar coleções, risco e empréstimos de curto prazo em tempo real
Moderador
Notas de la presentación
Responding to the signals of change from dynamic global marketplace is a necessity. Variety, velocity and volume of data within businesses now double roughly every 18 months. With exploding mass of mobile enabled population, information required for servicing their needs has to be available at fingertips. Becoming a real-time business requires not only managing daily business transactions of your core business processes (e.g. finance, sales, production) in real-time but also being able to capture new data from sources like social media to enable one-to-one customer engagement or connecting directly to machines through sensors for getting reliable information on what’s really happening on the ground at each moment. It also means being able to analyze all this data in real-time - leveraging advanced models like predictive - for more relevant business decisions, and finally accessing real-time business insights on any device for immediate action. The SAP Business Suite is now powered by SAP HANA, the next generation platform. With SAP HANA, SAP provides the most modern suite of applications unifying analytics and transactions into a single in-memory platform. The result? The suite now allows real-time planning, execution, reporting and analysis across your end-to-end business processes. Business users can also get a unified – at finger tip – 360° views of real-time information - on any device - across all SAP Business Suite applications and even beyond like information from sensors and social medias. And you can leverage the suite to rethink your business processes as needed or simply invent new business models not possible before. The SAP HANA platform provides the basis to dramatically increase the performance of SAP Business Suite applications and innovate without disruption by also having the opportunity to leverage a new generation of real-time solutions from SAP and partners natively built on an open platform. With the SAP Business Suite now powered by SAP HANA, SAP is simply combining together the best suite of applications (SAP Business Suite) and the next generation platform (SAP HANA), for driving your entire business in real-time.
Mas arquiteturas tradicionais de TI são pressionadas ... direcionando para novas soluções
2,8 ZB em 2012 85% de novos Tipos de Dados 15x Dados de Máquina até 2020 40 ZB até 2020 Novas Fontes (Sentiment, Clickstream, Geo, Sensor)
Reduzir o desperdício e fraude no fundo do governo <2 min para a detecção de 100.000 nomes sobre base de 90 milhões de registros
Identificar variantes de DNA para o tratamento de câncer Resultados 216X mais rápidos: 3 dias 20 minutos
Melhorar o diagnóstico por meio de detecção de padrões 300M registros; análise em 2-10 segundos
Prever compra por sentimento do cliente Análise de sazonalidade em 5 segundos
Melhorar a utilização do trabalho Tempos de relatórios 1131x mais rápido
Experiência "perfeita " insights em tempo real 60x mais rápidos
Maior eficácia do marketing Relatórios 56x mais rápidos: ofertas para os clientes alvo
Acelerar fechamento mensal Redução de 75% na consulta CRM ~ 23 para 6 segundos
Lançamento de novos produtos ou mercados 400x mais rápida a execução do relatório. Previsão: vendas-tendências em tempo real
Diagnósticos em tempo real Analisar 15 anos 1 TB de dados em segundos
Relacionamento com os clientes Visão 360 do cliente e experiência abrangente
Sucesso em Big Data demanda cobertura total
Veracidade
Valor
Variedade Velocidade
Volume
Responder perguntas complexas sobre dados granulares Prever o melhor na próxima ação
Acessível em qualquer dispositivo ou para qualquer usuário Self service e interações intuitivas
Muitos tipos de dados Dados estruturados e não estruturados (redes sociais, RFID, Log, dados de cliente, preditivo, ...)
Streams em tempo real de dados Faça uma pergunta, obtenha uma resposta imediata
Escala maciça de dados (Mobile, sensor, clickstream, PoS Data, transactions...) Sem preparação de dados Nenhum pré-agregados
Moderador
Notas de la presentación
Leveraging new technologies to capture and manage all of the data coming at us (Big Data) gives us the opportunity to run our business using signals that are relevant today. These signals can measure performance, provide critical indicators about the business, identify customer issues and complaints, help us market more effectively and accurately, and all in real-time.
SAP Big Data
Explosão de dados digitais Novas arquiteturas
Hardware mais baratos
“Big data é um termo abrangente para qualquer coleção de conjuntos de dados tão grande e complexa que se torna difícil para processar usando aplicações de processamento de dados tradicionais” – Wikipedia
Only SAP has the unique set of innovations across 5 key areas that together can have a profound impact on the future of your business. Across key areas – applications, mobile, cloud, database and technology, and analytics – SAP can help you: Enable the real-time enterprise Deliver new compelling experiences to your customers and employees Unwire your business – enabling anything to be possible from anywhere We also want to make it as easy as possible for you to consume across our technology in a way that focuses on helping you to be an industry leader or driving a specific line of business to the highest level of productivity and success.
Big Data Plataforma para desencadear o valor do negócio em tempo real
Consumir
Guardar & Processar
Ingerir
Big Data Plataforma - provisionamento com SAP
SAP IQ
Trigger Based, Real Time
ETL, Batch
Log Based
ODBC
DB Connection
ODBC
Event Streams
ECH
ODBC Data Synchronization
ODBC/ JDBC/ OData
SAP HANA smart data access Data Virtualization
Non SAP Data Sources Trading & Order
Management Systems
Network Devices- Wired/Wireless
SAP BW
SAP Sybase IQ /ASE
SAP Business Suite
SAP Data Services
SAP LT Replication Server
SAP Sybase Event Stream Processor
SAP Sybase SQL Anywhere
Your Own Applications
SAP HANA SAP Sybase
Replication Server
Origens de Dados
15
Moderador
Notas de la presentación
Because today most companies are missing new signals that is hidden in this data and they are still looking in the rear view mirror at historical financial information to make key decisions (if any thing at all), like the Income Statement and Balance Sheet are at best rear-view measures of the top line and bottom line. They provide a snapshot in time of all that has happened, but very little, if any, indication of what is happening in the enterprise For example, an online retailer with a subscription model experiences a massive drop in stock price because of poor Income Statement results. Further analysis indicates that there was a dramatic drop in subscribers (Churn) in one of their most profitable segments. It would stand to reason that a pre-emptive pulse-check on the churn could have helped stem the bleeding and perhaps prevented the reaction on Wall Street. This churn is an example of a new signal that could have helped this one enterprise run its business more proactively rather than look for explanations with a rear-view perspective. IN addition, . The people who have information is a finite set of people in the organization – according to Gartner only 10% of the organizations are using analytics to make decisions…. This means 90% of your organization are making off the cuff decisions. According ot Gartner 75% of people will need analytics on a daily basis by 2020 If companies could make their information even 10% more meaningful – they could have an annual increase benefits of over $ 2b. And if that does not convince you to invest in getting real-time information to all decision makers in your organization – According to Nucleus Research, For every 1$ spent on analytics, can bring a 1000% return on investment – so you have the stats to know it is absolutely essential to make this investment.
Big Data Aplicações
Fazer Percepções de Big Data acionáveis via aplicações de negócios por indústria da SAP
+25 Indústrias
+11 LoBs
Customer Value Intelligence (CEI)
:-) Audience
Discovery (CEI) Account
Intelligence (CEI)
Fraud Management
Demand Signal Management
Social Contact Intelligence (CEI)
Sentiment Intelligence (RDS)
Manufacturing (Operational Intelligence)
Manufacturing (Responsive
Manufacturing)
Moderador
Notas de la presentación
SAP is building this today and we are intimately familiar with the key persona that will define success for organizations that are embarking on building their Network of truth. We see three types of user persona: Decision Makers Analysts Designers And for each one we must consider what is important for them, what are their intentions. For example. Decision Makers are not the most active BI users but we must consider that their time and their focus is on their decision and their key activities they need help with are EXPLORING FOR ANSWERS to questions and MONITORING their business to understand impact For analysts, it’s about explaining unique insights and often time it requires enriching data For Designers, it’s about the process of designing content and apps and the model of governance. Author: Pierre Leroux Copyright SAP <OPTIONAL> Decision Makers. For a long time we have not differentiated our end users, but we need to be aware. The key user of BI are not the most active or the most often logged on. Instead they are the people that leverage the information to make actual decisions within the organization. At times we all act as decision makers, no matter if our job title is CEO or Housewife; and we all want to make decisions that have the least risk with the highest return. Business Intelligence exists to enable that to happen. When we serve the decision maker we must consider that their time and their focus is on their decision, and we must fit within these constraints or be ignored. And the key activities these users need help with are EXPLORING for answers to questions and MONITORING their business to understand impact – these processes happen every day and need to be fast, simple and immediate for every decision maker. Analysts. Most of the people watching this session will have often played the role of Analyst. Supporting ourselves and decision makers, or as often others. Performing analysis and enabling complex views of information. Analysts spent lots of time with information and vary from business managers analyzing small collections of key data, to Data Scientist performing complex calculations on vast seas of unstructured data. We need to enable all these people to ENRICH information in new ways, and share that with every other analysts. We also need to help them EXPLAIN the unique insights they have gained in the process so that effort can have real impact and real value to the organizations. But we must also consider the Designer. Those technology specialists that produce the targeted experiences and applications for our employees or more and more our customers. We must also let them design new experiences and applications that connect and leverage our STANDARD of TRUTH as part of the new NETWORK of TRUTH. Finally, we must make the process GOVERNABLE. We must have governance to ensure that the entire NETWORK is practical, reliable and safe. Wikipedia is not a wild-west of dangerous data, the open collaboration that creates it is only possible with a solid and well understood model of GOVERNANCE. So as we build out the NETWORK it is these people we need to consider and their key intentions. And we need to not just enable them to consume the NETWORK, we need each of these people to be able to contribute to that NETWORK, in the form of Opinions (like or dislike, trust or don’t trust), enrichment (relationships, associations, computations, descriptions) and design (templates, applications, actions) That is the goal SAP has with Visual Intelligence and Predictive Analysis, the first BI Components designed to operate in concert with a true Real Time Data Platform. Visualize and Act on Big Data Connect people with the right experience at the right time to get their questions answered Monetize insights directly in business processes with Big Data applications Deliver big data apps that optimize organizational performance in real-time Analytic tools industry apps start ups
Big Data Aplicações (ex: CEI)
Account Intelligence
Real Time Customer
Insights
Personalized Treatment
Strategic and Effective
Selling
Customer Engagement Intelligence Customer Value
Intelligence
Moderador
Notas de la presentación
SAP is building this today and we are intimately familiar with the key persona that will define success for organizations that are embarking on building their Network of truth. We see three types of user persona: Decision Makers Analysts Designers And for each one we must consider what is important for them, what are their intentions. For example. Decision Makers are not the most active BI users but we must consider that their time and their focus is on their decision and their key activities they need help with are EXPLORING FOR ANSWERS to questions and MONITORING their business to understand impact For analysts, it’s about explaining unique insights and often time it requires enriching data For Designers, it’s about the process of designing content and apps and the model of governance. Author: Pierre Leroux Copyright SAP <OPTIONAL> Decision Makers. For a long time we have not differentiated our end users, but we need to be aware. The key user of BI are not the most active or the most often logged on. Instead they are the people that leverage the information to make actual decisions within the organization. At times we all act as decision makers, no matter if our job title is CEO or Housewife; and we all want to make decisions that have the least risk with the highest return. Business Intelligence exists to enable that to happen. When we serve the decision maker we must consider that their time and their focus is on their decision, and we must fit within these constraints or be ignored. And the key activities these users need help with are EXPLORING for answers to questions and MONITORING their business to understand impact – these processes happen every day and need to be fast, simple and immediate for every decision maker. Analysts. Most of the people watching this session will have often played the role of Analyst. Supporting ourselves and decision makers, or as often others. Performing analysis and enabling complex views of information. Analysts spent lots of time with information and vary from business managers analyzing small collections of key data, to Data Scientist performing complex calculations on vast seas of unstructured data. We need to enable all these people to ENRICH information in new ways, and share that with every other analysts. We also need to help them EXPLAIN the unique insights they have gained in the process so that effort can have real impact and real value to the organizations. But we must also consider the Designer. Those technology specialists that produce the targeted experiences and applications for our employees or more and more our customers. We must also let them design new experiences and applications that connect and leverage our STANDARD of TRUTH as part of the new NETWORK of TRUTH. Finally, we must make the process GOVERNABLE. We must have governance to ensure that the entire NETWORK is practical, reliable and safe. Wikipedia is not a wild-west of dangerous data, the open collaboration that creates it is only possible with a solid and well understood model of GOVERNANCE. So as we build out the NETWORK it is these people we need to consider and their key intentions. And we need to not just enable them to consume the NETWORK, we need each of these people to be able to contribute to that NETWORK, in the form of Opinions (like or dislike, trust or don’t trust), enrichment (relationships, associations, computations, descriptions) and design (templates, applications, actions) That is the goal SAP has with Visual Intelligence and Predictive Analysis, the first BI Components designed to operate in concert with a true Real Time Data Platform. Visualize and Act on Big Data Connect people with the right experience at the right time to get their questions answered Monetize insights directly in business processes with Big Data applications Deliver big data apps that optimize organizational performance in real-time Analytic tools industry apps start ups
Big Data Aplicações (ex: DSIM)
SAP Demand Signal Management é a plataforma da empresa para integrar todos os sinais de demanda relevantes (internos e externos) a uma única fonte da verdade.
.
Moderador
Notas de la presentación
SAP is building this today and we are intimately familiar with the key persona that will define success for organizations that are embarking on building their Network of truth. We see three types of user persona: Decision Makers Analysts Designers And for each one we must consider what is important for them, what are their intentions. For example. Decision Makers are not the most active BI users but we must consider that their time and their focus is on their decision and their key activities they need help with are EXPLORING FOR ANSWERS to questions and MONITORING their business to understand impact For analysts, it’s about explaining unique insights and often time it requires enriching data For Designers, it’s about the process of designing content and apps and the model of governance. Author: Pierre Leroux Copyright SAP <OPTIONAL> Decision Makers. For a long time we have not differentiated our end users, but we need to be aware. The key user of BI are not the most active or the most often logged on. Instead they are the people that leverage the information to make actual decisions within the organization. At times we all act as decision makers, no matter if our job title is CEO or Housewife; and we all want to make decisions that have the least risk with the highest return. Business Intelligence exists to enable that to happen. When we serve the decision maker we must consider that their time and their focus is on their decision, and we must fit within these constraints or be ignored. And the key activities these users need help with are EXPLORING for answers to questions and MONITORING their business to understand impact – these processes happen every day and need to be fast, simple and immediate for every decision maker. Analysts. Most of the people watching this session will have often played the role of Analyst. Supporting ourselves and decision makers, or as often others. Performing analysis and enabling complex views of information. Analysts spent lots of time with information and vary from business managers analyzing small collections of key data, to Data Scientist performing complex calculations on vast seas of unstructured data. We need to enable all these people to ENRICH information in new ways, and share that with every other analysts. We also need to help them EXPLAIN the unique insights they have gained in the process so that effort can have real impact and real value to the organizations. But we must also consider the Designer. Those technology specialists that produce the targeted experiences and applications for our employees or more and more our customers. We must also let them design new experiences and applications that connect and leverage our STANDARD of TRUTH as part of the new NETWORK of TRUTH. Finally, we must make the process GOVERNABLE. We must have governance to ensure that the entire NETWORK is practical, reliable and safe. Wikipedia is not a wild-west of dangerous data, the open collaboration that creates it is only possible with a solid and well understood model of GOVERNANCE. So as we build out the NETWORK it is these people we need to consider and their key intentions. And we need to not just enable them to consume the NETWORK, we need each of these people to be able to contribute to that NETWORK, in the form of Opinions (like or dislike, trust or don’t trust), enrichment (relationships, associations, computations, descriptions) and design (templates, applications, actions) That is the goal SAP has with Visual Intelligence and Predictive Analysis, the first BI Components designed to operate in concert with a true Real Time Data Platform. Visualize and Act on Big Data Connect people with the right experience at the right time to get their questions answered Monetize insights directly in business processes with Big Data applications Deliver big data apps that optimize organizational performance in real-time Analytic tools industry apps start ups
Filtragem de Arquivos Desbloquear texto de documentos binários Extrair e processar dados de texto não-
estruturado a partir de vários formatos de arquivo (txt, html, xml, pdf, doc, ppt, xls, Rtf, msg) Carga de binário, plano, e outros
documentos diretamente para HANA para pesquisa e análise de texto
Análise de Texto Nativo Dar estrutura para conteúdo não estruturado Classificar entidades (pessoas, empresas,
coisas, etc.) Identificar fatos de domínio (sentimentos,
tópicos, pedidos, etc.) Suporta até 31 idiomas
SAP HANA Texto & Sentiment
Análise
Pesquisa Analisar Predizer
Big Data Análises
Moderador
Notas de la presentación
SAP is building this today and we are intimately familiar with the key persona that will define success for organizations that are embarking on building their Network of truth. We see three types of user persona: Decision Makers Analysts Designers And for each one we must consider what is important for them, what are their intentions. For example. Decision Makers are not the most active BI users but we must consider that their time and their focus is on their decision and their key activities they need help with are EXPLORING FOR ANSWERS to questions and MONITORING their business to understand impact For analysts, it’s about explaining unique insights and often time it requires enriching data For Designers, it’s about the process of designing content and apps and the model of governance. Author: Pierre Leroux Copyright SAP <OPTIONAL> Decision Makers. For a long time we have not differentiated our end users, but we need to be aware. The key user of BI are not the most active or the most often logged on. Instead they are the people that leverage the information to make actual decisions within the organization. At times we all act as decision makers, no matter if our job title is CEO or Housewife; and we all want to make decisions that have the least risk with the highest return. Business Intelligence exists to enable that to happen. When we serve the decision maker we must consider that their time and their focus is on their decision, and we must fit within these constraints or be ignored. And the key activities these users need help with are EXPLORING for answers to questions and MONITORING their business to understand impact – these processes happen every day and need to be fast, simple and immediate for every decision maker. Analysts. Most of the people watching this session will have often played the role of Analyst. Supporting ourselves and decision makers, or as often others. Performing analysis and enabling complex views of information. Analysts spent lots of time with information and vary from business managers analyzing small collections of key data, to Data Scientist performing complex calculations on vast seas of unstructured data. We need to enable all these people to ENRICH information in new ways, and share that with every other analysts. We also need to help them EXPLAIN the unique insights they have gained in the process so that effort can have real impact and real value to the organizations. But we must also consider the Designer. Those technology specialists that produce the targeted experiences and applications for our employees or more and more our customers. We must also let them design new experiences and applications that connect and leverage our STANDARD of TRUTH as part of the new NETWORK of TRUTH. Finally, we must make the process GOVERNABLE. We must have governance to ensure that the entire NETWORK is practical, reliable and safe. Wikipedia is not a wild-west of dangerous data, the open collaboration that creates it is only possible with a solid and well understood model of GOVERNANCE. So as we build out the NETWORK it is these people we need to consider and their key intentions. And we need to not just enable them to consume the NETWORK, we need each of these people to be able to contribute to that NETWORK, in the form of Opinions (like or dislike, trust or don’t trust), enrichment (relationships, associations, computations, descriptions) and design (templates, applications, actions) That is the goal SAP has with Visual Intelligence and Predictive Analysis, the first BI Components designed to operate in concert with a true Real Time Data Platform. Visualize and Act on Big Data Connect people with the right experience at the right time to get their questions answered Monetize insights directly in business processes with Big Data applications Deliver big data apps that optimize organizational performance in real-time Analytic tools industry apps start ups
Big Data Análises Visualizando com SAP Lumira
Fornece a liberdade de compreender os seus dados, personalizá-lo e criar conteúdo bonito!
Baixe e instale no seu computador em menos de 5 minutos
Visões de muitas fontes de dados Combinar, manipular e enriquecer os
dados para aplicá-loa a seus cenários de negócios
Visualizações de auto-atendimento e analytics para contar a sua história
Otimizado para SAP HANA em tempo real sobre os dados detalhados
Big Data Análises
Plataforma de BI
Dashboards e Visualização
Relatórios
Relatórios Interativos
Análises
Procurar e Explorar
Camada Semântica
SAP Business Objects BI
Moderador
Notas de la presentación
Because today most companies are missing new signals that is hidden in this data and they are still looking in the rear view mirror at historical financial information to make key decisions (if any thing at all), like the Income Statement and Balance Sheet are at best rear-view measures of the top line and bottom line. They provide a snapshot in time of all that has happened, but very little, if any, indication of what is happening in the enterprise For example, an online retailer with a subscription model experiences a massive drop in stock price because of poor Income Statement results. Further analysis indicates that there was a dramatic drop in subscribers (Churn) in one of their most profitable segments. It would stand to reason that a pre-emptive pulse-check on the churn could have helped stem the bleeding and perhaps prevented the reaction on Wall Street. This churn is an example of a new signal that could have helped this one enterprise run its business more proactively rather than look for explanations with a rear-view perspective. IN addition, . The people who have information is a finite set of people in the organization – according to Gartner only 10% of the organizations are using analytics to make decisions…. This means 90% of your organization are making off the cuff decisions. According ot Gartner 75% of people will need analytics on a daily basis by 2020 If companies could make their information even 10% more meaningful – they could have an annual increase benefits of over $ 2b. And if that does not convince you to invest in getting real-time information to all decision makers in your organization – According to Nucleus Research, For every 1$ spent on analytics, can bring a 1000% return on investment – so you have the stats to know it is absolutely essential to make this investment.
Big Data Análises Preditivas
Revolucionando a forma como as empresas utilizam análise preditiva para tomar melhores decisões em petabytes de dados.
Primeira camada semântica da análise preditiva
Automatiza a construção de modelos de previsão sofisticados para cada função de mineração de dados
Com cliques, não código, pode-se implantar equações de score otimizadas
Capacidades de análise fim a fim em rede social
Poderosos recursos de visualização e exploração gráficos
Próximo passo Recomendação de cenário de negócios e oficina de descoberta de valor
SAP oferece metodologia e
abordagem comprovadas para descobrir as áreas
específicas de melhoria de negócios e
quantificar o potencial valor
Oficina de Descoberta de Valor
com os seus especialistas de LOB
e TI para desenvolver uma estratégia e um
roteiro para Big Data
http://www.sapbigdata.com/
Mais Informações
Qual o nível de maturidade de Big Data da sua Organização? Faça uma auto análise em https://valuemanagement.sap.com/BigData2
Moderador
Notas de la presentación
Complete the SurveyAny Questions?Assess the strengths and weaknesses of your business processes and measure your organization’s performance. Survey: Big Data Maturity Model Assessment Survey Big Data Maturity Model Assessment
