Ibm ofa ottawa_analytics_in_gov _campbell_robertsondawnrk
Opportunity for Analytics Ottawa event. Presentation by Campbell Robertson, Analytics in Government. Results based outcomes with IBM Predictive Analysis for Cost Avoidance and Beyond.
Mohanbir Sawhney, Robert R. McCormick Tribune Foundation Clinical Professor of Technology Kellogg School of Management, Northwestern University presents at the 2012 Big Analytics Roadshow.
Companies are drinking from a fire hydrant of data that is too big, moving too fast and is too diverse to be analyzed by conventional database systems. Big Data is like a giant gold mine with large quantities of ore that is difficult to extract. To get value out of Big Data, enterprises need a new mindset and a new set of tools. They also need to know how to extract actionable insights from Big Data that can lead to competitive advantage. The Big Story of Big Data is not what Big Data is, but what it means for business value and competitive advantage.... read more: http://www.biganalytics2012.com/sessions.html#mohan_sawhney
AI powered Decision Making in Banks - How Banks today are using Advanced analytics in credit Decisioning, enhancing customer life time value, lower operating costs and stronger customer acquisition
Big Data: Real-life examples of Business Value Generation with ClouderaCapgemini
Capgemini has helped multiple organizations to put Big Data to work and create value for their business and their clients.
This prsentation looks at real-world cases of how organizations are using, or planning to use, big data technology. It will look at the different ways in which the technology is being used in a business context.
Examples are drawn from Retail, Telco, Financial Services, Public Sector and Consumer goods.
It will look at a range of business scenarios from simple cost reduction through to new business models looking at how the business case has been built and what value has been realized.
It will also look at some of the practical challenges and approaches taken and specifically the application of Enterprise Data Hubs in collaboration with its prime partner Cloudera.
Written by Richard Brown, Global Programme Leader, Big Data & Analytics, Capgemini
The Currency of Trust: Why Banks and Insurers Must Make Customer Data Safer a...Capgemini
Are banks and insurers a safe pair of hands when it comes to customer data? Our global survey of more than 180 senior data privacy and security professionals – as well as 7,600 consumers – found that less than a third (29%) of these organizations offer both strong data privacy practices and a sound security strategy. Just one in five (21%) are highly confident that they can detect a cybersecurity breach.
This picture has so far not unduly affected consumers’ perceptions of the industry. We found that 83% of consumers trust banks and insurers when it comes to data. And while one in four institutions have reported being victim of a hack, just 3% of consumers believe their own bank or insurer has ever been breached. However, with the pending General Data Protection Regulation (GDPR) regulations, this trust factor is likely to change as transparency increases. Financial organizations have to reveal a data breach 72 hours after the incident.
Banks and insurance firms have a clear incentive therefore to fortify their defences. As well as avoiding the prohibitive fines and penalties that will result from compromised data, protecting privacy offers a strategic business advantage. Addressing security concerns will drive greater adoption of low-cost digital channels. We found that security concerns deter nearly half of consumers (47%) from using digital channels. It will also reduce churn and attract competitors’ customers – 74% of consumers would switch their bank or insurer in the event of a data breach.
Preparing to be a trusted data steward is no easy task, however. It means raising the bar on multiple dimensions:
• Aligning data practices with consumers’ expectations
• Finding innovative ways of providing non-intrusive security to consumers
• Building the capabilities required to monitor cyber risks on a real-time basis
• Revisiting the data governance model.
Building your reputation for data privacy and robust security is definitely challenging. But, those who strike the right chord with consumers will enjoy a competitive advantage over their peers. The winners will be those who triumph in the trust game.
Ibm ofa ottawa_analytics_in_gov _campbell_robertsondawnrk
Opportunity for Analytics Ottawa event. Presentation by Campbell Robertson, Analytics in Government. Results based outcomes with IBM Predictive Analysis for Cost Avoidance and Beyond.
Mohanbir Sawhney, Robert R. McCormick Tribune Foundation Clinical Professor of Technology Kellogg School of Management, Northwestern University presents at the 2012 Big Analytics Roadshow.
Companies are drinking from a fire hydrant of data that is too big, moving too fast and is too diverse to be analyzed by conventional database systems. Big Data is like a giant gold mine with large quantities of ore that is difficult to extract. To get value out of Big Data, enterprises need a new mindset and a new set of tools. They also need to know how to extract actionable insights from Big Data that can lead to competitive advantage. The Big Story of Big Data is not what Big Data is, but what it means for business value and competitive advantage.... read more: http://www.biganalytics2012.com/sessions.html#mohan_sawhney
AI powered Decision Making in Banks - How Banks today are using Advanced analytics in credit Decisioning, enhancing customer life time value, lower operating costs and stronger customer acquisition
Big Data: Real-life examples of Business Value Generation with ClouderaCapgemini
Capgemini has helped multiple organizations to put Big Data to work and create value for their business and their clients.
This prsentation looks at real-world cases of how organizations are using, or planning to use, big data technology. It will look at the different ways in which the technology is being used in a business context.
Examples are drawn from Retail, Telco, Financial Services, Public Sector and Consumer goods.
It will look at a range of business scenarios from simple cost reduction through to new business models looking at how the business case has been built and what value has been realized.
It will also look at some of the practical challenges and approaches taken and specifically the application of Enterprise Data Hubs in collaboration with its prime partner Cloudera.
Written by Richard Brown, Global Programme Leader, Big Data & Analytics, Capgemini
The Currency of Trust: Why Banks and Insurers Must Make Customer Data Safer a...Capgemini
Are banks and insurers a safe pair of hands when it comes to customer data? Our global survey of more than 180 senior data privacy and security professionals – as well as 7,600 consumers – found that less than a third (29%) of these organizations offer both strong data privacy practices and a sound security strategy. Just one in five (21%) are highly confident that they can detect a cybersecurity breach.
This picture has so far not unduly affected consumers’ perceptions of the industry. We found that 83% of consumers trust banks and insurers when it comes to data. And while one in four institutions have reported being victim of a hack, just 3% of consumers believe their own bank or insurer has ever been breached. However, with the pending General Data Protection Regulation (GDPR) regulations, this trust factor is likely to change as transparency increases. Financial organizations have to reveal a data breach 72 hours after the incident.
Banks and insurance firms have a clear incentive therefore to fortify their defences. As well as avoiding the prohibitive fines and penalties that will result from compromised data, protecting privacy offers a strategic business advantage. Addressing security concerns will drive greater adoption of low-cost digital channels. We found that security concerns deter nearly half of consumers (47%) from using digital channels. It will also reduce churn and attract competitors’ customers – 74% of consumers would switch their bank or insurer in the event of a data breach.
Preparing to be a trusted data steward is no easy task, however. It means raising the bar on multiple dimensions:
• Aligning data practices with consumers’ expectations
• Finding innovative ways of providing non-intrusive security to consumers
• Building the capabilities required to monitor cyber risks on a real-time basis
• Revisiting the data governance model.
Building your reputation for data privacy and robust security is definitely challenging. But, those who strike the right chord with consumers will enjoy a competitive advantage over their peers. The winners will be those who triumph in the trust game.
Welsh Consultants publishes- Big data has affected the way that organisations do business in every industry across the world, and real estate is no exception. Understanding the term ‘big data’ will help give context to how it helps in real estate analysis. Gartner’s explanation, circa 2001, is still considered the go-to definition: ‘Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insights, superior decision-making, and effective process automation.’ This is often referred to as the ‘three Vs’ of big data. Essentially, big data is processing of large amounts of data, be it historic or real-time, and to which algorithms are applied to discover trends in user behaviour, predict future outcomes, or gain other business insights. The data sets can be structured or unstructured, and can be analysed to make precise and accurate business decisions. This paper reflects upon this in detail.
D2 d turning information into a competive asset - 23 jan 2014Henk van Roekel
Understanding the evolution of Business Intelligence and Analytics and the challenges and opportunities that come with it. Exploring CGI's Data2Diamonds™ approach ensuring financial sound, technical viable and socially desirable Big Data initiatives.
This presentation was made for a hypothetical telecom company, to be presented to the management, persuading them to adopt big data/analytics in company.
Looks at the different AI approaches and provides some practical categorisation and case studies. Then talks about the data fabric you need to put in place to improve model accuracy and deployment. Covers: supervised, unsupervised, machine learning, deep learning, RPA, etc. Finishes with how to create successful AI projects.
#IBMInsight session presentation "Mitigate Risk, Combat Fraud and Financial Crimes"
The Issue of fraud, challenges, fighting fraud as an enterprise endeavor, IBM Smarter counter fraud framework and IBM Counter Fraud business services
More at ibm.biz/BdEPRH
We studied impact of the Big Data phenomenon on SMBs.
We conducted interviews among 30 SMBs to check:
- Big Data understanding by SMBs
- Adoption level of Big Data services
- Value creation and go-to-market channels
- Pain points in adopting Big Data
Big Data in Financial Services: How to Improve Performance with Data-Driven D...Perficient, Inc.
Most banking and financial services organizations have only scratched the surface of leveraging customer data to transform their business, realize new revenue opportunities, manage risk and address customer loyalty. Yet a business’s digital footprint continues to evolve as automated payments, location-based purchases, and unstructured customer communications continue to influence the technology landscape for financial services.
OpenText Presents: Mastering the Digital Economy through Big Data and Custome...OpenText
IDC’s Helena Schwenk joins OpenText to discuss how big data can help overcome the barriers faced by Executives aiming to redefine their businesses to compete in the Digital Economy. The era of self-service analysis has exposed data to more people within a business, but this in itself creates challenges for IT, who retain responsibility for the health and hygiene of data, as well as security. View the webinar here: http://ow.ly/bImR307Ptue
Welsh Consultants publishes- Big data has affected the way that organisations do business in every industry across the world, and real estate is no exception. Understanding the term ‘big data’ will help give context to how it helps in real estate analysis. Gartner’s explanation, circa 2001, is still considered the go-to definition: ‘Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insights, superior decision-making, and effective process automation.’ This is often referred to as the ‘three Vs’ of big data. Essentially, big data is processing of large amounts of data, be it historic or real-time, and to which algorithms are applied to discover trends in user behaviour, predict future outcomes, or gain other business insights. The data sets can be structured or unstructured, and can be analysed to make precise and accurate business decisions. This paper reflects upon this in detail.
D2 d turning information into a competive asset - 23 jan 2014Henk van Roekel
Understanding the evolution of Business Intelligence and Analytics and the challenges and opportunities that come with it. Exploring CGI's Data2Diamonds™ approach ensuring financial sound, technical viable and socially desirable Big Data initiatives.
This presentation was made for a hypothetical telecom company, to be presented to the management, persuading them to adopt big data/analytics in company.
Looks at the different AI approaches and provides some practical categorisation and case studies. Then talks about the data fabric you need to put in place to improve model accuracy and deployment. Covers: supervised, unsupervised, machine learning, deep learning, RPA, etc. Finishes with how to create successful AI projects.
#IBMInsight session presentation "Mitigate Risk, Combat Fraud and Financial Crimes"
The Issue of fraud, challenges, fighting fraud as an enterprise endeavor, IBM Smarter counter fraud framework and IBM Counter Fraud business services
More at ibm.biz/BdEPRH
We studied impact of the Big Data phenomenon on SMBs.
We conducted interviews among 30 SMBs to check:
- Big Data understanding by SMBs
- Adoption level of Big Data services
- Value creation and go-to-market channels
- Pain points in adopting Big Data
Big Data in Financial Services: How to Improve Performance with Data-Driven D...Perficient, Inc.
Most banking and financial services organizations have only scratched the surface of leveraging customer data to transform their business, realize new revenue opportunities, manage risk and address customer loyalty. Yet a business’s digital footprint continues to evolve as automated payments, location-based purchases, and unstructured customer communications continue to influence the technology landscape for financial services.
OpenText Presents: Mastering the Digital Economy through Big Data and Custome...OpenText
IDC’s Helena Schwenk joins OpenText to discuss how big data can help overcome the barriers faced by Executives aiming to redefine their businesses to compete in the Digital Economy. The era of self-service analysis has exposed data to more people within a business, but this in itself creates challenges for IT, who retain responsibility for the health and hygiene of data, as well as security. View the webinar here: http://ow.ly/bImR307Ptue
Presentation from the Markedsføringsdagen 2013 conference, june 12 2013 in Copenhagen. Contains an overview of trends, uses, challenges for the CMO and innovation aspects of big data.
Technology tech trends 2022 and beyond Brian Pichman
It's that time of year again, where we get to look ahead and finally have some good news. Tech enthusiast Brian Pichman of the Evolve Project will showcase the latest technology trends and how that impact our learning spaces and spaces at home. It is guaranteed to make you forget about all of 2020 and 2021....well maybe that's a new technology about to be released, the MIB memory eraser. Join this exciting webinar and leave with some high hopes of new technology to explore!
Fast Data for Competitive Advantage: 4 Steps to Expand your Window of Opportu...VoltDB
In this webinar, you’ll hear VoltDB CEO, Bruce Reading, outline 4 steps to expand your window of opportunity while avoiding risky options that can destroy your business. Technology innovator and CEO of Emagine International, David Peters, will also share key lessons learned from establishing his company’s ability to use fast data to crush competitors and execute on Emagine’s ability to open new markets. To view the webinar in its entirety, click here: http://learn.voltdb.com/WRExecSeries1.html
Unlocking Value of Data in a Digital AgeRuud Brink
InfoGraphic about Intelligence Hubs as accelerator of the Digital organisation. Five steps how you could think big, and act small to unlock value of Data in your organisation. Contact me for the office A0 poster.
Financial Markets Data & Analytics Led TransformationGianpaolo Zampol
How big data, advanced analytics and cognitive computing is disrupting traditional business and operating models in financial markets? New competitors, powered by social, mobile, analytics, and cloud computing, are making new business models emerging rapidly. Wealth Management, Corporate Banking and Transaction Banking & Payments are significant sources of growth in Financial Markets. How take advantage from those new technologies to face this new scenario?
Big Data - Accountability Solutions for Public Sector ProgramsGaurav "GP" Pal
Enhancing Program Oversight and Integrity through Agile Systems Development and Advanced Analytics requires the application of advanced algorithms and technologies for proactive oversight.
The Recovery Operations Center (ROC) deployed advanced analytics and data analytics staff to help identity and prevent waste, fraud and abuse in the $840 billion ARRA 2009 program.
Foster Moore® prepared a white paper for the recent meeting of the National Association of Secretaries of State (NASS). It looks at the reasons that Secretaries of State might consider when going digital.
CGI's Steve Starace, SVP & BU Leader, U.S. Northeast explains how CGI’s solutions and services are addressing clients’ top priorities in the banking industry.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
23. IBM | SPARK
Power of data. Simplicity of design. Speed of innovation.
24. IBM Spark
Why Spark matters to a business?
2. Spark lets you develop line-of-business
applications faster
3. Spark learns from data and delivers in real time
With Hadoop, you ask a question and get back a batch of data. With
Spark, you may say, “continue to give me answers to this
question”…and when new data comes, the user is smarter.
1. Spark makes it easier to access and work with
all data
- Enables new data-based use cases
- All data: Internal/External, Structured/Unstructured
- Real-time insights, from all data sources
- Automates analytics with Machine Learning
- Clients that lead in data, lead their industry
Design Development
Data Science
25. IBM Spark
Spark processes and analyzes data from ANY data
source
Hadoop Database Mainframe
Data-
warehouse
Business Applications and Business
Intelligence