The document summarizes key points from a 2013 analytics symposium. It discusses trends in big data discovery, mobility, real-time decisions, and predictive analytics. Big data allows tapping diverse data sets to find unknown relationships and make data-driven decisions. It impacts many industries. Real-time data and decisions are important as over 80% of executives say critical information is delivered too late. Predictive analytics and visualization help add meaning to data. Mobility increases access and analytical collaboration anywhere.
Big Data: Expectations, Obstacles, and The Road to Greater ValueSAP Technology
What can Big Data do for you? A recent report by The Economist Intelligence
Unit sponsored by SAP Services explores these issues and more. Learn more at www.sap.com/bigdata
The requirements of data management systems are becoming ever more demanding and many companies are struggling to keep up with the data deluge. Over 56% of respondents in ComputerWorld’s latest survey say overwhelming data volumes are compelling them to look at new data management solutions and are looking for ways to efficiently manage the data explosion. See how they are planning to tackle new data management challenges.
Data science involves using automated methods to analyze massive amounts of data from various structured and unstructured sources to extract knowledge and insights. It is an interdisciplinary field that incorporates computer science, modeling, statistics, analytics, and mathematics. There is a growing demand and shortage of data scientists across many industries as organizations face challenges in organizing large amounts of data but most companies are not seeing significant value from their data science efforts yet.
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
The world around us is changing. Data is embedded in everything, and users from all lines of business want to leverage this data to influence decisions. The trick is to create a culture for pervasive analytics and empower the business to use data everywhere.
The core enabling technology to make this happen is Apache Hadoop. By leveraging Hadoop, organizations of all sizes and across all industries are making business models more predictable, and creating significant competitive advantages using big data.
Join Cloudera and Forrester to learn:
- What we mean by pervasive analytics, how it impacts your organization, and how to get started
- How leading organizations are using pervasive analytics for competitive advantage
- How Cloudera’s extensive partner ecosystem complements your strategy, helping deliver results faster
The document discusses how cognitive computing and artificial intelligence are disrupting various industries by enabling non-traditional business models. It provides examples of the world's largest taxi, accommodation, retailer, and media companies that own no vehicles, real estate, inventory, or create content, respectively. The document advocates that companies leverage cognitive computing to gain insights from vast amounts of new data through predictive, descriptive, and cognitive capabilities. It outlines steps to become a cognitive business through developing a strategy, extending analytics with cognitive, moving to cognitive cloud services, building cognitive infrastructure, and adopting cognitive security.
Conviction, Alignment, Agility: Three Keys to Getting & Staying on the Right ...Apigee | Google Cloud
Conviction, Alignment, Agility are the three keys to staying on the right side of the digital divide. As the world becomes more programmable, digital leaders are turning conviction into a case for change and plan of action through alignment and agility. Digital leaders achieve alignment by making digital experiences a priority for all teams and connecting digital investments to key performance indicators. They demonstrate agility through an options-based approach to ROI using criteria like satisfaction, efficiency and revenue to evaluate digital investments over multiple scenarios. A programmable world means every sector is now in a race to build digital ecosystems, and alignment and agility are critical for organizations to scale their digital assets and stay ahead of competitors.
Intel, Cloudera and guest speaker Forrester Research, Inc. discuss the strategy of pervasive analytics and real life examples of how analytics have already been embedded into applications and workflows.
Big Data: Expectations, Obstacles, and The Road to Greater ValueSAP Technology
What can Big Data do for you? A recent report by The Economist Intelligence
Unit sponsored by SAP Services explores these issues and more. Learn more at www.sap.com/bigdata
The requirements of data management systems are becoming ever more demanding and many companies are struggling to keep up with the data deluge. Over 56% of respondents in ComputerWorld’s latest survey say overwhelming data volumes are compelling them to look at new data management solutions and are looking for ways to efficiently manage the data explosion. See how they are planning to tackle new data management challenges.
Data science involves using automated methods to analyze massive amounts of data from various structured and unstructured sources to extract knowledge and insights. It is an interdisciplinary field that incorporates computer science, modeling, statistics, analytics, and mathematics. There is a growing demand and shortage of data scientists across many industries as organizations face challenges in organizing large amounts of data but most companies are not seeing significant value from their data science efforts yet.
How to Ruin your Business with Data Science & Machine Learning by Ingo MierswaData Con LA
Abstract:- Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it's surprisingly simple to draw completely wrong conclusions from statistical models, and correlation does not imply causation is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. This session will discuss. How highly-correlated features can overshadow the patterns your machine learning model is supposed to find this leads to models which will perform worse in production than during model building. How incorrect cross-validation lead to over-optimistic estimations of your model accuracy, especially we will discuss the impact of data preprocessing on the accuracy of machine learning models. How feature engineering can lift simple models like linear regression to the accuracy of deep learning but comes with the advantages of understandability & robustness.
The world around us is changing. Data is embedded in everything, and users from all lines of business want to leverage this data to influence decisions. The trick is to create a culture for pervasive analytics and empower the business to use data everywhere.
The core enabling technology to make this happen is Apache Hadoop. By leveraging Hadoop, organizations of all sizes and across all industries are making business models more predictable, and creating significant competitive advantages using big data.
Join Cloudera and Forrester to learn:
- What we mean by pervasive analytics, how it impacts your organization, and how to get started
- How leading organizations are using pervasive analytics for competitive advantage
- How Cloudera’s extensive partner ecosystem complements your strategy, helping deliver results faster
The document discusses how cognitive computing and artificial intelligence are disrupting various industries by enabling non-traditional business models. It provides examples of the world's largest taxi, accommodation, retailer, and media companies that own no vehicles, real estate, inventory, or create content, respectively. The document advocates that companies leverage cognitive computing to gain insights from vast amounts of new data through predictive, descriptive, and cognitive capabilities. It outlines steps to become a cognitive business through developing a strategy, extending analytics with cognitive, moving to cognitive cloud services, building cognitive infrastructure, and adopting cognitive security.
Conviction, Alignment, Agility: Three Keys to Getting & Staying on the Right ...Apigee | Google Cloud
Conviction, Alignment, Agility are the three keys to staying on the right side of the digital divide. As the world becomes more programmable, digital leaders are turning conviction into a case for change and plan of action through alignment and agility. Digital leaders achieve alignment by making digital experiences a priority for all teams and connecting digital investments to key performance indicators. They demonstrate agility through an options-based approach to ROI using criteria like satisfaction, efficiency and revenue to evaluate digital investments over multiple scenarios. A programmable world means every sector is now in a race to build digital ecosystems, and alignment and agility are critical for organizations to scale their digital assets and stay ahead of competitors.
Intel, Cloudera and guest speaker Forrester Research, Inc. discuss the strategy of pervasive analytics and real life examples of how analytics have already been embedded into applications and workflows.
This document contains information about several companies and the work they do with data. It discusses Tala, a company that collects mobile Android data like SMS, payments, and utilities to classify and model user data for credit decisioning. Their goal is to provide financial access to underserved people globally using alternative mobile data instead of traditional credit checks. The document also briefly mentions the work of Brown University, DRI/McGraw-Hill, OneSource Information Services, Compete/WPP, and Dstillery/EveryScreen Media which involves tasks like data cleansing, modeling, forecasting, and measuring online behaviors.
KEY CHALLENGES FOR MONETIZING BIG DATA POWERED AI: AN OVERVIEWTyrone Systems
YOU’RE NOT THE ONLY ONE FACING THIS PROBLEM
according to recent articles in the Harvard Business Review and McKinsey. But don’t blame big data for that. It’s all your fault
Ai design sprint - Finance - Wealth managementChinmay Patel
Chinmay Patel presented an AI design sprint methodology. The methodology involves identifying a business problem, gathering and preparing relevant data, training and deploying a model, and maintaining/improving the model over time. As an example, Chinmay discussed how this process was used to build an automated claim resolution bot that can resolve claims within 3 seconds with no paperwork. The methodology was also proposed for a wealth management use case to perform user segmentation using clustering algorithms.
Transforming Business with Intelligent Dataashbhatia
This document discusses trends in data science and analytics. It describes a shift from data scarcity to data abundance, operational to observational data, rigid schemas to flexible exploration. Analytics are moving from reporting to insights, predictions, and automated actions. Examples show how machine learning and intelligent apps can help prevent hospital readmissions, detect lies using brain waves, and create value from connecting machines in areas like healthcare, transportation and manufacturing.
10 Enterprise Analytics Trends to Watch in 2020MicroStrategy
As businesses face a 2020 reality check and use this year to hone their strategy for the next decade, MicroStrategy has compiled insights on the top enterprise analytics trends to watch from leading BI, analytics and digital transformation influencers including analysts from Forrester, IDC, Constellation Research, Ventana Research and more.
From artificial intelligence and mobile intelligence, to the explosion of data and data sources, to some very human factors, we hope you’ll find this gathering of insights (plus the patterns and themes that have emerged here) a valuable resource for taking action now, but also looking and planning ahead to become an Intelligent Enterprise.
Social Data Week SF: Integrating Social and Enterprise Data for Competitive A...Social Data Week
This document discusses social data intelligence and the challenges of integrating social data across organizations. It defines social data intelligence as insight derived from social data that can be used confidently and at scale alongside other data sources to make strategic decisions. The challenges of integrating social data include dealing with multiple internal interests, requiring new analytical approaches, and social data initially lacking credibility. The document provides an example of how Symantec harvests social data and routes it to the appropriate business functions. It discusses the results Symantec has seen across marketing, customer support, engineering, and other areas. The document also presents a maturity model for social data and trends organizations should consider when using social data.
This document provides a roadmap for establishing a successful data excellence program. It recommends starting with the right cross-functional team to define goals and prioritize use cases. It then advises performing a data assessment to understand existing data sources before implementing a simple but high-impact use case as a first step. Subsequent steps include managing the program, adding additional use cases, training personnel, and dealing with potential resistance, with an emphasis on continual improvement and evolving a data-driven culture.
10 Enterprise Analytics Trends to Watch in 2019 MicroStrategy
View insights from Forrester analyst Mike Gualtieri, Constellation Research’s Ray Wang and Doug Henschen, Ventana Research’s Mark Smith and David Menninger, IDC’s Chandana Gopal, Marcus Borba, Ronald van Loon and other top analytics and business intelligence thought leaders.
NUS-ISS Learning Day 2018- Sentiment analysis in financeNUS-ISS
This document discusses using sentiment analysis in finance. It introduces sentiment analysis and how it can be used to analyze social media and news texts to gauge public sentiment about financial markets. Natural language processing techniques are used to classify texts as positive or negative sentiment and aggregate these classifications into sentiment indices. The document demonstrates how sentiment analysis was used in Chinese equity markets, showing a heatmap of sentiment scores for different stocks. Sentiment analysis can potentially inform trading strategies but requires backtesting and an understanding of behavioral finance concepts.
CIO’s 17th annual “State of the CIO” survey was conducted with the goal of understanding how the CIO role continues to evolve in today’s business climate and to help define the CIO agenda for 2018.
Data quality - The True Big Data ChallengeStefan Kühn
The document discusses data quality challenges, especially with big data. It notes that data quality starts at data creation and production, and that both data producers and consumers play a role. With big data, quality issues like redundancy, lack of resolution, and noise are exacerbated due to diverse sources of data, lack of documentation and standards, and increasing volumes of data. The document recommends treating data as a product and implementing quality standards, detection of problems, and root cause analysis to improve quality rather than just collecting more raw data. A shared responsibility approach between business and IT is needed to develop a common understanding of data.
Network World’s State of the Network research is conducted annually to gain a deeper understanding of the network environments within today’s organizations.
This document summarizes the results of a survey of 186 IT leaders about their technology priorities and budgets for 2018. It found that security-related projects, like business continuity and disaster recovery, were the most important initiatives. Most respondents expected their overall IT budgets to increase in the next year. Emerging technologies like analytics, cloud computing, and IoT were areas where organizations were most open to partnering with newer vendors. The document provides details on the survey methodology and breakdown of responses by industry, job role, and technology category.
The 2018 IDG Digital Business research was conducted to gain a better understanding of how organizations are evolving to a digital business model in terms of revising technology strategies, changing organizational structures and processes, and innovating to provide a unique customer experience.
2017 Role & Influence of the Technology Decision-MakerIDG
The 2017 IDG Role & Influence of the Technology Decision-Maker survey examines the evolving role of IT decision-makers (ITDMs) in today’s corporations, specifically as organizations move towards a more digital-focused business.
AI, machine learning, robotic processing, and automation introduce risk and bias that may have profound and specific impacts on customers and users. We need to invest in data and tools to facilitate the ethical use and management of automated prediction applications. We need to fill data gaps and build AI Ops, Privacy, Security, and Life Cycle Management.
PublicRelay Media Measurement: Turning Media into IntelligencePublicRelay
Overview of PublicRelay's trusted media analytics solution for communications and marketing professionals. Our clients confidently use our human-curated content analysis and measurement to plan and measure influencer engagement, reputation management, competitive landscape, and message pull through. Our innovative product offers superior data quality and actionable insights to deliver accurate answers to your strategic business questions.
AI today and its power to transform healthcareBonnie Cheuk
This document summarizes a presentation by Dr. Bonnie Cheuk on how AI can transform businesses. In 3 sentences:
Dr. Cheuk discusses how AI can help gain a better understanding of diseases, identify new drug targets, speed up drug design and development, improve clinical trial design, and enable personalized medicine. Examples are presented where AI and machine learning have been used at AstraZeneca to classify tablets, identify likely prescribers of new drugs, and review patents. In conclusion, Dr. Cheuk emphasizes that AI should be applied carefully with consideration for ethics and unintended consequences, and that humans will continue to play an important role in applying judgment.
The document discusses key topics from IBM's Business Analytics Summit in Toronto in 2013. It outlines the four dimensions of big data: volume, velocity, variety, and veracity. It also discusses challenges organizations face in managing big data and key shifts driving the need for smarter analytics. Additionally, it provides examples of how leading organizations are using analytics to gain insights from data and outperform competitors. Finally, it briefly describes several IBM products for big data analytics.
Big Data & Business Analytics: Understanding the MarketspaceBala Iyer
This document provides an overview of big data and business analytics. It discusses the growth of data and importance of analytics to businesses. The key topics covered include defining big data and data science, analyzing the analytics ecosystem and key players, examining use cases of analytics at companies like Target and Whirlpool, and providing recommendations for building an analytics capability and working with analytics vendors. The presentation emphasizes how data-driven decisions can improve business performance but also notes challenges to overcome like skills shortages and changing organizational culture.
This document contains information about several companies and the work they do with data. It discusses Tala, a company that collects mobile Android data like SMS, payments, and utilities to classify and model user data for credit decisioning. Their goal is to provide financial access to underserved people globally using alternative mobile data instead of traditional credit checks. The document also briefly mentions the work of Brown University, DRI/McGraw-Hill, OneSource Information Services, Compete/WPP, and Dstillery/EveryScreen Media which involves tasks like data cleansing, modeling, forecasting, and measuring online behaviors.
KEY CHALLENGES FOR MONETIZING BIG DATA POWERED AI: AN OVERVIEWTyrone Systems
YOU’RE NOT THE ONLY ONE FACING THIS PROBLEM
according to recent articles in the Harvard Business Review and McKinsey. But don’t blame big data for that. It’s all your fault
Ai design sprint - Finance - Wealth managementChinmay Patel
Chinmay Patel presented an AI design sprint methodology. The methodology involves identifying a business problem, gathering and preparing relevant data, training and deploying a model, and maintaining/improving the model over time. As an example, Chinmay discussed how this process was used to build an automated claim resolution bot that can resolve claims within 3 seconds with no paperwork. The methodology was also proposed for a wealth management use case to perform user segmentation using clustering algorithms.
Transforming Business with Intelligent Dataashbhatia
This document discusses trends in data science and analytics. It describes a shift from data scarcity to data abundance, operational to observational data, rigid schemas to flexible exploration. Analytics are moving from reporting to insights, predictions, and automated actions. Examples show how machine learning and intelligent apps can help prevent hospital readmissions, detect lies using brain waves, and create value from connecting machines in areas like healthcare, transportation and manufacturing.
10 Enterprise Analytics Trends to Watch in 2020MicroStrategy
As businesses face a 2020 reality check and use this year to hone their strategy for the next decade, MicroStrategy has compiled insights on the top enterprise analytics trends to watch from leading BI, analytics and digital transformation influencers including analysts from Forrester, IDC, Constellation Research, Ventana Research and more.
From artificial intelligence and mobile intelligence, to the explosion of data and data sources, to some very human factors, we hope you’ll find this gathering of insights (plus the patterns and themes that have emerged here) a valuable resource for taking action now, but also looking and planning ahead to become an Intelligent Enterprise.
Social Data Week SF: Integrating Social and Enterprise Data for Competitive A...Social Data Week
This document discusses social data intelligence and the challenges of integrating social data across organizations. It defines social data intelligence as insight derived from social data that can be used confidently and at scale alongside other data sources to make strategic decisions. The challenges of integrating social data include dealing with multiple internal interests, requiring new analytical approaches, and social data initially lacking credibility. The document provides an example of how Symantec harvests social data and routes it to the appropriate business functions. It discusses the results Symantec has seen across marketing, customer support, engineering, and other areas. The document also presents a maturity model for social data and trends organizations should consider when using social data.
This document provides a roadmap for establishing a successful data excellence program. It recommends starting with the right cross-functional team to define goals and prioritize use cases. It then advises performing a data assessment to understand existing data sources before implementing a simple but high-impact use case as a first step. Subsequent steps include managing the program, adding additional use cases, training personnel, and dealing with potential resistance, with an emphasis on continual improvement and evolving a data-driven culture.
10 Enterprise Analytics Trends to Watch in 2019 MicroStrategy
View insights from Forrester analyst Mike Gualtieri, Constellation Research’s Ray Wang and Doug Henschen, Ventana Research’s Mark Smith and David Menninger, IDC’s Chandana Gopal, Marcus Borba, Ronald van Loon and other top analytics and business intelligence thought leaders.
NUS-ISS Learning Day 2018- Sentiment analysis in financeNUS-ISS
This document discusses using sentiment analysis in finance. It introduces sentiment analysis and how it can be used to analyze social media and news texts to gauge public sentiment about financial markets. Natural language processing techniques are used to classify texts as positive or negative sentiment and aggregate these classifications into sentiment indices. The document demonstrates how sentiment analysis was used in Chinese equity markets, showing a heatmap of sentiment scores for different stocks. Sentiment analysis can potentially inform trading strategies but requires backtesting and an understanding of behavioral finance concepts.
CIO’s 17th annual “State of the CIO” survey was conducted with the goal of understanding how the CIO role continues to evolve in today’s business climate and to help define the CIO agenda for 2018.
Data quality - The True Big Data ChallengeStefan Kühn
The document discusses data quality challenges, especially with big data. It notes that data quality starts at data creation and production, and that both data producers and consumers play a role. With big data, quality issues like redundancy, lack of resolution, and noise are exacerbated due to diverse sources of data, lack of documentation and standards, and increasing volumes of data. The document recommends treating data as a product and implementing quality standards, detection of problems, and root cause analysis to improve quality rather than just collecting more raw data. A shared responsibility approach between business and IT is needed to develop a common understanding of data.
Network World’s State of the Network research is conducted annually to gain a deeper understanding of the network environments within today’s organizations.
This document summarizes the results of a survey of 186 IT leaders about their technology priorities and budgets for 2018. It found that security-related projects, like business continuity and disaster recovery, were the most important initiatives. Most respondents expected their overall IT budgets to increase in the next year. Emerging technologies like analytics, cloud computing, and IoT were areas where organizations were most open to partnering with newer vendors. The document provides details on the survey methodology and breakdown of responses by industry, job role, and technology category.
The 2018 IDG Digital Business research was conducted to gain a better understanding of how organizations are evolving to a digital business model in terms of revising technology strategies, changing organizational structures and processes, and innovating to provide a unique customer experience.
2017 Role & Influence of the Technology Decision-MakerIDG
The 2017 IDG Role & Influence of the Technology Decision-Maker survey examines the evolving role of IT decision-makers (ITDMs) in today’s corporations, specifically as organizations move towards a more digital-focused business.
AI, machine learning, robotic processing, and automation introduce risk and bias that may have profound and specific impacts on customers and users. We need to invest in data and tools to facilitate the ethical use and management of automated prediction applications. We need to fill data gaps and build AI Ops, Privacy, Security, and Life Cycle Management.
PublicRelay Media Measurement: Turning Media into IntelligencePublicRelay
Overview of PublicRelay's trusted media analytics solution for communications and marketing professionals. Our clients confidently use our human-curated content analysis and measurement to plan and measure influencer engagement, reputation management, competitive landscape, and message pull through. Our innovative product offers superior data quality and actionable insights to deliver accurate answers to your strategic business questions.
AI today and its power to transform healthcareBonnie Cheuk
This document summarizes a presentation by Dr. Bonnie Cheuk on how AI can transform businesses. In 3 sentences:
Dr. Cheuk discusses how AI can help gain a better understanding of diseases, identify new drug targets, speed up drug design and development, improve clinical trial design, and enable personalized medicine. Examples are presented where AI and machine learning have been used at AstraZeneca to classify tablets, identify likely prescribers of new drugs, and review patents. In conclusion, Dr. Cheuk emphasizes that AI should be applied carefully with consideration for ethics and unintended consequences, and that humans will continue to play an important role in applying judgment.
The document discusses key topics from IBM's Business Analytics Summit in Toronto in 2013. It outlines the four dimensions of big data: volume, velocity, variety, and veracity. It also discusses challenges organizations face in managing big data and key shifts driving the need for smarter analytics. Additionally, it provides examples of how leading organizations are using analytics to gain insights from data and outperform competitors. Finally, it briefly describes several IBM products for big data analytics.
Big Data & Business Analytics: Understanding the MarketspaceBala Iyer
This document provides an overview of big data and business analytics. It discusses the growth of data and importance of analytics to businesses. The key topics covered include defining big data and data science, analyzing the analytics ecosystem and key players, examining use cases of analytics at companies like Target and Whirlpool, and providing recommendations for building an analytics capability and working with analytics vendors. The presentation emphasizes how data-driven decisions can improve business performance but also notes challenges to overcome like skills shortages and changing organizational culture.
This document discusses how data and analytics can create or destroy shareholder value for companies through decision making. It finds that while most executives recognize the importance of data-driven decisions, only a third of organizations are highly data-driven. Highly data-driven companies are 3 times more likely to improve decision making. The technologies for advanced analytics like machine learning, IoT/sensors, simulation, and visualization are advancing rapidly but organizations must focus on developing the right operating model and skills to realize benefits. The operating model chosen can determine whether shareholder value is created or destroyed through analytics.
Big data is delivering significant value to organizations that complete projects according to a survey. The vast majority (92%) of users are satisfied with business outcomes and feel their implementation meets needs. Larger companies see big data as more important and are more likely to benefit from initial implementations. While talent shortage poses challenges, successful users leverage external resources. Users see big data as disruptive and potentially transformational, with 89% believing it will revolutionize business as the internet did.
Views From The C-Suite: Who's Big on Big DataPlatfora
The document summarizes the key findings of a survey of 395 C-level executives on their views and priorities regarding big data. The survey found that executives have an overwhelmingly positive view of big data and its potential, but lack understanding of how to apply it within their own roles and functions. While customer insights are currently the top priority for big data analytics, executives believe that within three years it will be applied more broadly across business processes. The optimal approach is seen as taking an enterprise-wide approach through cross-functional teams rather than leaving big data efforts to individual departments or functions.
The survey of 395 C-level executives from various industries found:
1) Executives have overwhelmingly positive views of big data and its potential, especially for increasing sales, improving efficiency and building customer loyalty.
2) While recognizing big data's potential, three-quarters want a deeper understanding of the underlying technologies. Customer insights and targeting are currently seen as top priorities for big data applications.
3) Lack of understanding of how to apply big data to specific business functions is cited as the top internal obstacle to greater use of big data.
This document provides an overview and agenda for building an analytics capability. It discusses key topics such as:
- The importance of big data and analytics for business decisions
- Building an analytics capability requires the right people, processes, and technology
- Companies can build capabilities internally, outsource work, or use a hybrid approach
- When outsourcing analytics work, firms need to consider issues like vendor skills, data protection, and intellectual property ownership
Data Trends for 2019: Extracting Value from DataPrecisely
To get the most business value from data, you need to keep up with the latest tech trends – or do you?
View this webinar on-demand as we share the results from our 2019 Data Trends Survey! We'll reveal what organizations around the world are really up to at the intersection of technology, big data and business.
Key topics include:
• Business initiatives getting the most IT support in 2019
• Highest-priority IT initiatives
• Tech adoption rates, benefits and challenges
"Big data in western europe today" Forrester / Xerox 2015yann le gigan
The document summarizes the findings of a survey conducted by Forrester Consulting on behalf of Xerox regarding big data usage in Western Europe. The key findings are:
1) Senior decision-makers see big data as a top priority and have extensive plans to implement big data initiatives across a wide range of use cases in 2015.
2) Companies expect to see returns on their big data investments within 12 months and are using big data to improve efficiency and manage risk.
3) While big data offers opportunities, respondents acknowledge challenges such as ensuring data quality and integrating big data into decision-making.
This document summarizes key findings from a survey of 200 IT professionals about big data analytics. The main findings are:
- Big data and data center infrastructure updates are the top strategic priorities for most respondents. Big data is the number one priority for 21% of respondents.
- Most respondents have a formal big data analytics strategy in place or plan to have one within the next six months. The majority will have a strategy within a year.
- Three quarters of respondents are currently processing both structured and unstructured data or plan to within six months.
- Adoption of tools like Apache Hadoop continues to rise, with over half of respondents having deployed or implementing a Hadoop distribution, half of which use
This document summarizes key findings from a survey of 200 IT professionals about big data analytics. The main findings are:
- Big data and data center infrastructure updates are the top strategic priorities for IT managers. Big data is the number one priority for 21% of respondents.
- Most organizations already have a formal big data analytics strategy in place or plan to have one within the next six months. The majority will have a strategy within a year.
- Over half of respondents have already deployed or are currently implementing the Apache Hadoop framework. Half of those use an internal private cloud.
- The leading current uses of big data relate to understanding staffing levels and productivity, and generating competitive intelligence. Future uses
This presentation was given at the festival of marketing 2014. How grown up is your analytics? This slide deck will help you understand what you need to achieve optimum business benefit from your data analytics.
Moving Beyond Batch: Transactional Databases for Real-time DataVoltDB
Join guest Forrester speaker, Principal Analyst Mike Gualtieri, and Dennis Duckworth Director of Product Marketing from VoltDB to learn how enterprises can create a real-time, “origin-zero” data architecture within transactional databases to become a real-time enterprise.
It’s been three years since the General Data Protection Regulation shook up how organizations manage data security and privacy, ushering in a new focus on Data Governance. But what is the state of Data Governance today?
How has it evolved? What’s its role now? Building on prior research, erwin by Quest and ESG have partnered on a new study about what’s driving the practice of Data Governance, program maturity and current challenges. It also examines the connections to data operations and data protection, which is interesting given the fact that improving data security is now the No. 1 driver of Data Governance, according to this year’s survey respondents.
So please join us for this webinar to learn about the:
Other primary drivers for enterprise Data Governance programs
Most common bottlenecks to program maturity and sustainability
Advantages of aligning Data Governance with the other data disciplines
In a post-COVID world, data has the power to be even more transformative, and 84% of business and technology professionals say it represents the best opportunity to develop a competitive advantage during the next 12 to 24 months. Let’s make sure your organization has the intelligence it needs about both data and data systems to empower stakeholders in the front and back office to do what they need to do.
This document describes a platform called Iyka dataSpryng that provides comprehensive analytics capabilities. It removes the need for complex and siloed analytic processes by allowing direct access and analysis of disparate data sources. Key features include a unified view of all data, knowledge portability to leverage ontologies and dictionaries, and self-service analytics. This empowers users and provides 2x more productivity and faster results compared to traditional analytic methods.
A study on web analytics with reference to select sports websitesBhanu Prakash
This document is a project report submitted by Y. Bhanu Prakash to GITAM Institute of Management in partial fulfillment of the degree of Bachelor of Business Administration in Business Analytics. The report is on the topic of web analytics with reference to select sports websites. It includes declarations by the student and certification by the guide, as well as acknowledgements. The report will consist of 5 chapters - an introduction to analytics, a profile of Alexa.com, methodology, analysis and interpretation of data, and observations and conclusions.
Paradigm4 Research Report: Leaving Data on the tableParadigm4
While Big Data enjoys widespread media coverage, not enough attention has been paid to what practitioners think — data scientists who manage and analyze massive volumes of data. We wanted to know, so Paradigm4 teamed up with Innovation Enterprise to ask over 100 data scientists for their help separating Big Data hype from reality. What we learned is that data scientists face multiple challenges achieving their company’s analytical aspirations. The upshot is that businesses are leaving data — and money — on the table.
This document discusses how data and analytics can enable better decision making across businesses. It notes that while data-driven companies are more likely to report improved decision making, only 1 in 3 executives say their organization is highly data-driven. It also discusses challenges such as barriers related to skills and understanding data, and how most companies have not matured in their data analytics capabilities. The document advocates combining data science with business experience and judgment to make the best decisions.
(BDT207) Use Streaming Analytics to Exploit Perishable Insights | AWS re:Inve...Amazon Web Services
Streaming analytics is about knowing and acting on what's happening in your business and with your customers right this second. Forrester calls these perishable insights because they occur at a moment's notice and you must act on them fast. The high velocity, whitewater flow of data from innumerable real-time data sources such as market data, internet of things, mobile, sensors, clickstream, and even transactions remain largely un-navigated by most firms. The opportunity to leverage streaming analytics has never been greater. In this session, Forrester analyst Mike Gualtieri explains the opportunity, use cases, and how to use cloud-based streaming solutions in your application architecture.
This document discusses big data and the importance of data quality for big data initiatives. It defines big data as large, diverse digital data sets that require new techniques to enable capture, storage, analysis and visualization. The key challenges of big data include integrating diverse structured and unstructured data sources and ensuring high quality data. The document emphasizes that poor data quality can undermine big data analytics efforts and lead to wrong insights. It promotes establishing a data quality framework including profiling, standardization, matching and enrichment to enable valid big data analytics.
Similar to Analytic Transformation | 2013 Loras College Business Analytics Symposium (20)
Opening the Window to Data: Pella’s Journey - Creating Value with InformationCartegraph
Rick Hassman of Pella Corporation shared his organization's business analytics journey during the Loras College Business Analytics Symposium's breakout sessions.
As one of the leading manufacturers of windows and doors, Pella Corporation has had to undergo many transformations to compete with today’s fast-paced market. In keeping up with the competition, Pella struggled to create a comprehensive picture of their customer and actionable analytics for the business.
In 2000, Pella began their journey by replacing their legacy systems with integrated enterprise applications. The transformation enabled Pella to create a 360° view of the customer and capture tremendous amounts of information. Throughout this journey, Pella had to continuously adjust their approach to data as they expanded their applications to their customers. Learn how Pella changed their development methodology to ensure the data they were capturing could add value and transform their business to be a leader in their industry. Individuals who attend this session will learn why data analytic requirements have to be incorporated into application and process planning.
The Quest for the Best: Not All Data is Created EqualCartegraph
Paul Kongshaug, founder and CEO of BlendCard, presented The Quest for the Best: Not All Data is Created Equal during the breakout sessions of the Loras College Business Analytics Symposium.
There is little doubt that data has changed everything. But not all data is created equal. This is the story of one startup’s journey to innovate by collecting and connecting the best possible data available in the local marketplace. Through this session, entrepreneurs or anyone considering a career in data analytics gained perspective about the importance and challenges of collecting the right data.
The Analytics CoE: Positioning your Business Analytics Program for SuccessCartegraph
This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE).
A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).
The Journey to Exceptional Customer ExperienceCartegraph
This Loras College Business Analytics Symposium breakout session presented by Cathy Carlson and Bruce Barchus of Vizability LLC described the journey on the way to exceptional customer experience. What does that have to do with analytics? Everything. Data-driven decisions are critical to optimizing the way your organization delights (or not) your customers. Challenging your organization to be great on an end-to-end basis is never ending. Welcome to the journey.
Participants received a guide for getting real world results, including a list of tools to help along the way.
Implementation of EPM for Improved Multi-Business Budgeting and Financial Rep...Cartegraph
Andy Wickham of A.Y. McDonald Mfg. Co presented on enterprise performance management (EPM) for improved multi-business budgeting and financial reporting during the Loras College Business Analytics Symposium breakout sessions.
Enterprise Performance Management (EPM) is the process of monitoring performance across your organization with the goal of improving business performance. From strategy formulation and business planning/forecasting to financial management and supply chain, EPM is the convergence of better data, better tools and better processes to empower people at all levels of the organization to help improve performance. This session helped participants explore the budgeting and financial reporting side of EPM and how its implementation can improve their business.
This document discusses the importance of goals and goal management in achieving operational excellence. It outlines some key challenges companies face in goal alignment and engagement. It then provides a 7 step approach to operational excellence through accountability, clarity, alignment, engagement, execution, agility and aspiration. High performing companies are described as having goals that are open, transparent, aspirational, involve frequent check-ins and progress-based. The concept of "Goal Science" and tools for connected, supported, progress-based and adaptable goals are presented.
Leveraging Financial Planning for Operational AnalyticsCartegraph
The document summarizes a presentation by Scott Stevenson and Mike Jelen of eCapital Advisors on leveraging financial planning for operational analytics. eCapital Advisors is a consulting firm that provides business analytics and performance management consulting. They discussed how financial planning can be improved by making it more efficient, analytic-driven, and flexible. A case study of Children's Hospitals and Clinics of Minnesota was presented, where they implemented Hyperion Planning and Oracle BI to improve their disjointed and manual planning processes. This provided interactive dashboards and reporting for budgeting, labor analytics, and capital project analysis.
Opportunities for you, your company and your worldCartegraph
The 2015 Loras College Business Analytics Symposium kicked off with a morning keynote by Tim Suther, managing director at JP Morgan Chase that took a look at the enormous business analytics opportunities available to you, your company and your world.
Attendees left this presentation with an idea of how to:
-Identify these opportunities
-Position themselves and their company for these opportunities
-Prioritize among the many opportunities that will inevitably be identified
-Be a world citizen while pursuing these opportunities.
Loras College 2014 Business Analytics Symposium | Steve Whinnery and Scott St...Cartegraph
This presentation will walk you through an explanation of planning, industry leading practices for planning, executive leading practices for planning and finally analytics and planning.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Ron Dimon: EPM Done RightCartegraph
EPM is the convergence, finally, of better data, better tools, and better processes to empower people at all levels of the organization to answer those basic questions and help improve performance.
Based on his 2013 book (published by John Wiley & Sons), Ron Dimon will show how EPM helps your organization:
-Tap in to all this data for competitive advantage: from new insight to novel action
-Keep people engaged in their work and aligned with strategy
-Conduct "enlightened debates"
-Treat performance improvement as a management process
Ron will share better practices and what some of the leading organizations who have embraced EPM are doing in this interactive and inspiring session.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Margie Flynn: Measuring Sus...Cartegraph
Through this presentation, Margie Flynn will walk you through measuring sustainability (trends in sustainability data, ratings and frameworks) and sustainability reporting benefits, global reporting initiative and best practices.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Daniel Rebella, Phil Pillsb...Cartegraph
Learn about monetizing big data financials, performance insights and performance management in the cloud.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Greg Hedges: Social Risk or...Cartegraph
Preventing headline news of social business antics is one reason executives hire Protiviti. The focus to prevent bad things from happening with social, however, often obscures hidden gems of Upside opportunity. The irony? Walking past the Upside is likely an even greater risk.
We rethink downside risk to invent "The Reveal," that ppint in the consulting episode where a marvelous makeover is unveiled to delight the client. In this talk, we share a few cases of "Consulting: Impossible" where we reveal Upside opportunity side by side with that reduction in social business risk.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Gebhard Rainer: Building a ...Cartegraph
We are data rich and information poor--many companies have lived through the same challenges. We used to look at data in standard form and try to justify why things did not go the way they were planned and forecasted. We performed "autopsies on dead bodies but never brought them back to life, instead of finding a remedy for cure to deal with the future!"
Now we analyze data from multiple sources, establish patterns and cross references and then work on predictable models to allow Strategic Planning with a high degree of insight and proactive priority setting.
It's a mind shift and mind-set change that has taken a hold of the company and is pervasive down to the lowest level of planning. Constant change is what challenges us to continuously question our own models and improve in order to manage our business successfully.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Dan Conway: Sports AnalyticsCartegraph
Learn how you can use sports analytics to improve and predict player performance in baseball, basketball and football.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Colleen McKenna: Measuring ...Cartegraph
With a continuously evolving and expanding landscape, we often see professionals (or even entire organizations) completely overwhelmed and intimidated by social media. Want to know a secret? The truth is that social media is not drastically different from traditional communication approaches--the tools are just changing.
This session breaks down the barrier of social media and focuses your efforts back onto strategy and measurement where they belong. After all, how will you know if your efforts are successful if you never measure anything?
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Andy Stevens: Big Data Anal...Cartegraph
This session will cover issues and and advice for implementing Big Data Analytics in a Research and Development context. In addition to the basics, it will discuss the past, present and future and touch on relevant mathematics, statistics, science, technology, economics, business, history and even some literature.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Aaron Lanzen: Creating Busi...Cartegraph
Cisco Services is providing a behind-the-scenes perspective of its decision management and smart analytics programs. Success for Cisco is more than the technology or any one project. It's a mix of art, philosophy and technology that allows analytics to keep adding value to the business. You will hear how the program has evolved over the last 6 years and will explore different levels of smart analytics. Along the way, you will hear how the team grew a simple idea into a patent-pending resource allocation model.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Loras College 2014 Business Analytics Symposium | Tim Suther: New Opportuniti...Cartegraph
We live in the age of information, an era presenting enormous transformational opportunities for business, community and individuals alike. This session will highlight how organizations of all sizes and people from all walks of life can prioritize and pursue opportunities to perform better and to live life more richly.
For more information on the Loras College 2014 Business Analytics Symposium, the Loras College MBA in Business Analytics or the Loras College Business Analytics Certificate visit www.loras.edu/mba or www.loras.edu/bigdata.
Executive Panel | 2013 Loras College Business Analytics SymposiumCartegraph
Loras College is proud to present our annual Business Analytics Symposium on March 27, 2014 at the Grand River Center in Dubuque, IA. Industry experts will share their insights about the evolving field of business analytics opportunities. Learn about everything from best practices when analyzing data to the importance and benefits of building a culture of analytics within your organization.
To learn more, secure your seat or to take advantage of group discounts visit www.loras.edu/bigdata.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Top mailing list providers in the USA.pptxJeremyPeirce1
Discover the top mailing list providers in the USA, offering targeted lists, segmentation, and analytics to optimize your marketing campaigns and drive engagement.
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...my Pandit
Explore the fascinating world of the Gemini Zodiac Sign. Discover the unique personality traits, key dates, and horoscope insights of Gemini individuals. Learn how their sociable, communicative nature and boundless curiosity make them the dynamic explorers of the zodiac. Dive into the duality of the Gemini sign and understand their intellectual and adventurous spirit.
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
buy old yahoo accounts buy yahoo accountsSusan Laney
As a business owner, I understand the importance of having a strong online presence and leveraging various digital platforms to reach and engage with your target audience. One often overlooked yet highly valuable asset in this regard is the humble Yahoo account. While many may perceive Yahoo as a relic of the past, the truth is that these accounts still hold immense potential for businesses of all sizes.
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
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Analytic Transformation | 2013 Loras College Business Analytics Symposium
1.
2. 2013 ANALYTICS SYMPOSIUM
February 12, 2013
Grand River Center
Dubuque, Iowa
Analytic Technology Trends
Amy Mayer
Vice President
Capgemini
Rich Clayton
Vice President of Business Analytics
Oracle Corporation
4. 4
Why & How
Visualize the
Best Course
of Action?
Analyze & Act
in Real-Time
What-if
Analysis
Update Forecasts
Daily or Hourly
BETTER
DECISIONS,
FASTER
ACTION
5. Agenda
5
• Big Data Discovery
• Mobility
• Real Time Decisions
• Predictive Analytics
9. 9
Big Data Is About…
Tapping into diverse data sets
Finding and monetizing
unknown relationships
Creating data driven business
decisions
9
10. 10
MEDIA/
ENTERTAINMENT
Viewers / advertising
effectiveness
COMMUNICATIONS
Location-based
advertising
EDUCATION &
RESEARCH
Experiment
sensor analysis
CONSUMER
PACKAGED
GOODS
Sentiment analysis
of what’s hot,
problems
HEALTH CARE
Patient sensors,
monitoring, EHRs
Quality of care
LIFE
SCIENCES
Clinical trials
Genomics
HIGH TECHNOLOGY /
INDUSTRIAL MFG.
Mfg quality
Warranty analysis
OIL & GAS
Reserve
Capacity
estimation,
Drilling
exploration
sensor analysis
FINANCIAL
SERVICES
Risk & portfolio
analysis
AUTOMOTIVE
Auto sensors
reporting
location,
problems
RETAIL
Consumer
sentiment
Optimized sales
& marketing
LAW
ENFORCEMENT
& DEFENSE
Threat analysis -
social media
monitoring, photo
analysis
TRAVEL &
TRANSPORTATION
Sensor analysis for
optimal traffic flows
Customer sentiment
UTILITIES
Smart Meter
analysis
Big Data Impacts Every Industry
ON-LINE SERVICES
/ SOCIAL MEDIA
People & career
matching
Web-site
optimization
11. 11
Four Dimensions of Big Data
• Exponential growth in data volumes demand a different approachVolume
• Exploring real-time dataVelocity
• All types and forms of data leveraged to enrich & create additional valueVariety
• The (value) density of the data also has to be consideredValue
14. 14
Big Data Discovery
Easily EXPLORE all the different
paths to find the root cause
Easily EVOLVE the application to
keep pace with the changing
investigation
Easily COMBINE information to
swiftly start the investigation
16. 16
“The verdict is in. There is
no electronic-based cause
for unintended high-
speed acceleration in
Toyotas. Period.”
Ray LaHood
Transportation Secretary
February 9, 2011
16
17. 17
Data Driven: Achieve the Impossible
VARIABLES / SEC40k
SENSORS250
MORE DATA40x
DRIVE DECISIONS
DEEP ANALYTICS
REAL TIMEBig
Data
AMERICAS CUP#1
18. 18
Where is Your Big Data Opportunity?
“In a big data world, a competitor that fails to sufficiently
develop its capabilities will be left behind.”
McKinsey Global Institute
INNOVATE
INCREASE
REVENUE
LOWER
COSTS
25. 25
Improve Business Results
TraneMap: iPad Order Management app
with interactive modules and analytics
Business Impact:
• Increase sales close rate from 35 to
65%
• Increase product mix by 3%
• Increase average revenue by 22%
Source: Forrester Research
34. 35
t r e n d
The Deciding Factor:
Big Data and Decision Making
35. 36
The Market View
Capgemini commissioned the Economist Intelligence Unit to survey
over 600 business leaders, across the globe and industry sector, about
the use of Big Data in their organizations. Specifically looking at:
Their use of big data today and planned in the next 3 years
The advantages they have seen
The issues they have in using it
of participants are C-level
and board executives43%
36. 37
The Economist Intelligence Unit Survey: (1 of 2)
The Deciding Factor: Big Data and Decision Making
What we found:
85% Say the issue is not about volume but the ability to analyse
and act on the data in real time
62%
Believe we have a long way to go when it comes to
automating operational and tactical decisions
75% Believe their organizations to be
data-driven
42%Survey respondents say that unstructured
content is too difficult to interpret
37. 38
26% is the level of performance improvement already
seen from the application of big data analytics
41% is the level of performance improvement
expected in the next 3 years
62% Dispute the proposition that most operational / tactical
decisions that can be automated have been automated
The Economist Intelligence Unit Survey: (1 of 2)
The Deciding Factor: Big Data and Decision Making
38. 39
Shortage of skilled people to analyze the
data properly
Too Many Data Silos – Data is not pooled for the
benefit of the entire organization
Time it takes to analyze large data sets
The Economist Intelligence Unit Survey: (1 of 2)
The Deciding Factor: Big Data and Decision Making
Speaker notes:Life can be a lot easier than it is today. What if it were easier to: Explore the Why and the How behind the What?Visualize ”the best course of action?Analyze and act in real-time ?Do “what-if analysis with the slide of your finger?Update your forecasts every day or every hour? How much value could you business generate by making sure every business decision-maker could easily use the kind of advanced analytics and visualizations usually reserved for PhD statisticians to better understand the business, market and customers?
What’s the next big wave look like?
Big-Data is really just a continuation of a long standing data trend by supplementing existing information management systems with technologies and access methods more tailored to true ad-hoc business analytics and data scientists.What it also does is re-emphasise the value of information
Speaker Notes:The challenge with big data is that 80% of it is unstructured and the majority of it is “noise”. 80% of the information you need to understand why there are changes in your business or market, how you should address those changes and what else might be on the horizon is located in unstructured information—much of it outside of the organization. And the signal to noise ratio is high – not all that information is valuable. So you need to be able to sort through the noise and focus on the important nuggets.
Main Point: Combine, Explore, EvolveThey did this with our Warranty Discovery Solution, built with Oracle Endeca Information Discovery.With this solution and its underlying technology you can:Easily combine information to swiftly start the investigationEasily explore all the different paths and relationships to find the root causeEasily evolve the application to keep pace with the changing investigationLet’s look at each in turn
… found itself accused in 2010 of making cars that accelerated out of control, killing 34 people. The press had a field day. And the CEO, in the middle here, had to testify in a congressional hearing about how Toyota would fix the problem.But the real problem was they didn’t know if there actually was a problem with the cars. They just knew they were being accused.Toyota is a huge OBIEE customer. And very happy with it. But, there was no report for “all the vehicles that have a problem we never thought would happen.” So, how could they figure this out?
After a thorough investigation, Toyota was vindicated. The Transportation Secretary said, “The verdict is in. There is no electronic-based cause for unintended high-speed acceleration in Toyotas. Period.”Proving a negative – that the cars didn’t have an electronic problem – was tough. And the Big Data Discovery app played a prominent role in exonerating Toyota.As I mentioned, Toyota is a happy OBIEE customer. Still are. But they said building a discovery app with BI tools would have taken over a year. With EID it took 12 weeks.But how is this done? How is discovery technology different from traditional analytics technology? It comes down to one idea: a way to analyze data before it’s fully organized.
http://www.sail-world.com/USA/Americas-Cup:-Oracle-Data-Mining-supports-crew-and-BMW-ORACLE-Racing/68834The point of this slide is to explain the rationale behind Big Data – the fact that It is data that is now at the core of every business. If you can collect the right data, apply the right type of analysis to that data at the right time you can generate tremendous business value. Oracle used advanced analytics to control its Americas Cup trimaran. This meant that for any given wind speed the craft could travel at 3X the prevailing wind speed. Result was the Americas Cup. The use of 250 data sensors, the collection of over 40,000 data points, the use of Oracle Data Mining to analyze the data and make recommendations ensured the Americas Cup was won by Oracle-BMW.This is a great story for Oracle and a great example of Big Data at work and what can be achieved if you focus on the data.
Now we’re going to look at some use cases in more detail. Because of the variety of opportunities, we can’t show all the possible use cases. Instead, we’re going to show some representative examples. Even if your industry or company is not shown directly, we hope that you will see something relevant that’s applicable to you, or something that will give you ideas that you can use.The single biggest success factor for big data projects is having a good business case. So what we’re going to do here is offer three different sets of examples oriented around different types of business case. Some projects set out to reduce costs, others to increase revenue and others to provide some kind of new innovation with new products or programs not currently available. All these approaches have the potential to bring long term value to any organization and keep you ahead of your competition.
Smartphones and tablets are game changers for engagement because people carry them everywhere they go. The goal of pervasive analytics can be realized when deploying analytics and insights to a mobile device.
Simplify and increase the frequency of access to business information. Reach out to broader constituencies, fostering adoption by users that refrain from using, or physically can't explore (for example due to usually being away from a desk), traditional BI tools. Allow for more pervasive deployments: to more roles, embedded in more business processes, to less tech-savvy users, and in more locations. Make processes leaner by allowing on-location uninterrupted workflows.
Consistency across user experience. Scorecard for communicating goals, integration with search, Office. Generate production reports, utilize location data, run ad-hoc queries and of-course self-service dashboards…
CPG Customer started by pushing 4 reports to mobile devices over a year ago – the primary audience initially was Executives. The information was used and commonly referenced in meetings to ensure decisions were being made off from numbers that were not potentially modified prior to the meetings. The ability of having the information on mobile devices
Organization: Trane, heating and air conditioning systems manufacturerKey players: Trane sales operations and CIO organization; solution provider CynergySituation: Sales operations saw an opportunity to help dealers sell by replacing clipboards with direct engagement through tablets. Solution: Build TraneMap, an iPad order management application with rich content, interactive modules, and analytics. The app works offline and syncs when back online later. Sources of business value: selling or upselling the best solution based on real inputs of “load,” customer priorities, and house layout; capturing data and analytics at the point of customer engagement Business impact: Improve the “ring to ching” sales close rate from 35% to 65%. Increasethe product mix by 3% and average revenue by 22% for dealers using the app. Dealers using TraneMap recognized a 30% increase in revenue over the same period the previousyear. Provide analytics into future inventory requirements, which products are pitched but not selling, and what content results in the best sales. Road map: Focus on programs to increase tablet adoption by Trane dealers. Extend the app beyond the Trane “Comfort Specialist” level of dealers to include all Trane dealers.
Speaker Notes:The reality of today , is that too much crucial information is delivered too late. When this happens, your organization can miss the train – market opportunities are missed, customers are lost, revenue and profits can suffer. 53% Of executives say too much crucial information is delivered too late** **(AberdeenGroup – January 2012, survey of 247 executives - Data Management for BI – Big Data, Bigger Insight, Superior Performance)
Here’s an example of a customer who achieved a huge ROI with Oracle Real-Time Decisions.Oracle Real-Time Decisions Significantly Increases Revenue By Improving Closure Rates And Transaction ValuesForrester Total Economic Impact of Oracle Real-time Decisions, July 2011 found that one company in the financial services industry experienced the risk-adjusted ROI of 986% with a payback period of 3 months. The company has operations in 50 US states and more than 20,000 employees. It has completed several initiatives using RTD, including:1. Shopping cart abandonment rate reduction — online and call center channels. one percentage point lift in the closure rate during the original sales cycle. This equates to roughly $54.4 million in additional revenue over three years. 2. Post abandonment follow-up email campaign. This resulted in approximately a one percentage point lift in the conversion rate compared with a control group consisting of a single, static message. This totals $56.4 million over three years. 3. Optional program enrollment, i.e., electronic funds transfer (EFT), paperless statements, etc. This increase applies to all new sales, not just those attributable to the use of RTD, and is additive to the increased closure rate benefit. This results in more than $41.1 million over the life of the study. 4. Retention event identification and resolution strategies.
And of course stock prices….
Massive amounts of poll data. But few used it.When the major networks couldn’t make heads or tails of the election, New York Times’ Nate Silver called the presidential election in every state.
A lot of research has been done to explore how different visual constructs can add meaning to raw data. Stephen Few and Edward Tuft are a couple of more well known authors and practitioners of visualization techniques that can be application to BI and analytics.
Target: (this could be the story of any retailer)Colleagues from the Marketing Dept stop by and asked a statistician an odd question – “If we wanted to find out if a customer is pregnant, even if she didn’t want us to know, can you do that”?Shopping hapits are like routinesThere are, however, some brief periods in a person’s life when old routines fall apart and buying habits are suddenly in flux. One of those moments is when you are pregnant – right around the time of child birth….Most retailers collect information when we check out If you use a credit card or a coupon, or fill out a survey, or mail in a refund, or call the customer help line, or open an e-mail we’ve sent you or visit our Web site, we’ll record it and link it to your Guest ID,” Pole said. “We want to know everything we can.” Also linked to your Guest ID is demographic information like your age, whether you are married and have kids, which part of town you live in, how long it takes you to drive to the store, your estimated salary, whether you’ve moved recently…The statistician from Target used that Customer data and determined 25 things a women who is pregnant in her second tri-mester (prenatal vitamins, unscented lotions, scent free soaps, etc) and gave women in their customer database a pregnancy prediction scoreAbout a year after Pole created his pregnancy-prediction model, a man walked into a Target outside Minneapolis and demanded to see the manager. He was clutching coupons that had been sent to his daughter, and he was angry, according to an employee who participated in the conversation. “My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?” The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again. On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”