Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Data Marketplace: Speed to Value with MicroStrategy & Flexible ArchitecturesSteve Grover, CBIP,CSM
Description: Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Data Analytics has become a powerful tool to drive corporates and businesses. check out this 6 Reasons to Use Data Analytics. Visit: https://www.raybiztech.com/blog/data-analytics/6-reasons-to-use-data-analytics
Dark Data Revelation and its Potential BenefitsPromptCloud
This presentation covers benefits, use cases, practical examples, potential issues and the approach that needs to be taken when it comes to harnessing the power of dark data (a largely untapped strategic play in the big data realm).
Data Marketplace: Speed to Value with MicroStrategy & Flexible ArchitecturesSteve Grover, CBIP,CSM
Description: Join us to explore the vital need to rapidly unlock the value of data, and the major challenges companies face that are forcing this change. We’ll share several examples of the innovative ways companies are embracing this opportunity. By leveraging MicroStrategy with Hadoop, data storytelling, and rapid prototyping, and big data, we can exploit our data for immediate value and transform our business.
Data Analytics has become a powerful tool to drive corporates and businesses. check out this 6 Reasons to Use Data Analytics. Visit: https://www.raybiztech.com/blog/data-analytics/6-reasons-to-use-data-analytics
Dark Data Revelation and its Potential BenefitsPromptCloud
This presentation covers benefits, use cases, practical examples, potential issues and the approach that needs to be taken when it comes to harnessing the power of dark data (a largely untapped strategic play in the big data realm).
Big Data, Trends,opportunities and some case studies( Mahmoud Khosravi)Mahmood Khosravi
Humans have been generating data for thousands of years. More recently we have seen
an amazing progression in the amount of data produced from the advent of mainframes
to client server to ERP and now everything digital. For years the overwhelming amount
of data produced was deemed useless
How AI and blockchain can help you earn a passive income Blockchain Council
The past decade has been abuzz with speculation about both Artificial Intelligence and Blockchain Technology. Both hold enormous potential for human society as it stands and has both taken a long time to produce fruitful products. Highly developed AI modules are already entering the real world in products such as spam filtration, AI-based chess engines, and even self-driving cars. The true genius of such inventions is that they can produce code independently to solve problems in real time without any need for intervention from human beings. So let’s look at ways in which these strengths can be combined with blockchains to produce passive income investors.
In:Confidence 2019 - A foundation for Insight in a data-rich worldPrivitar
Jason Perkins, Head of Data & Analytics Architecture, BT, talks about the BT data strategy on the In:Confidence 2019 main stage (April 4th at Printworks, London).
Blockchain Patents for Innovation Data 3Q 2018 is a custom research of TechIPm, LLC (http://www.techipm.com) based on blockchain patents search in the USPTO database as of 3Q 2018. Total of 1246 patents (published patent applications & issued patents) are identified as blockchain patents indicating blockchain technology innovation activities.
Top 10 assignees/applications are IBM, Bank of America, Mastercard, Wal-Mart, TD Bank, Intel, American Express, Accenture, Cognitive Scale, Inc., and Coinbase.
The identified blockchain patents are further classified by key technologies for blockchain applications: security, transaction, cryptocurrency, database, smart contract, blockchain network, consensus, decentralized application, and AI.
INFOGRAPHIC: The Internet of Things: Are Organizations Ready For A Multi-Tril...Capgemini
The Internet is expanding. And this is not just in terms of getting accessible to more people; it is expanding beyond humans. Machines are becoming connected. Machines are talking to humans, but increasingly, they are also talking to one another. And this interconnectedness of machines, or the Internet of Things (IoT), is a potential multi-trillion dollar market that organizations can now tap into.
Abstract della presentazione di Fabio Rizzotto, IT Research & Consulting Director di IDC Italia, tenuta all’IDC Big Data Conference II, a Bologna il 19 novembre 2013
How Artificial Intelligence Is Revolutionizing Logistics Management?Maruti Techlabs
The rise of Artificial Intelligence has fundamentally altered many sectors of the supply chain industry. Whether it is customer support, inventory management or handling of logistics, the contribution of new age, AI-based solutions is undeniable.
As per executives and experts within the field, the prediction is clear – AI is here to stay and further transform these fields over the upcoming years.
Computers can handle huge sets of data at a time, which would otherwise be impossible to humanely take into a single decision-making process. This is why Artificial Intelligence is a boon to Supply Chain Management.
Using numerous data sets and applying intelligent algorithms, a machine can analyse endless possibilities that lead to effective strategizing.
AI minimizes the risks of human error. In short, with the help of AI, operational efficiency can be maximized and costs can be minimized.
A #research study by @Accenture shows that AI has the potential to boost profitability rates by an average of 38% by 2035 & lead to an economic boost of US$14 trillion across 16 industries by 2035.
#Training & updating AI models over time with the right expertise can pave the path to determining superiority in the domain of supply chain #management.
Some leading companies that use AI in Logistics:
@Rolls-Royce
@UPS
@Lineage Logistics
Link to the complete article in the comments below ⬇️
#AI #supplychain
How media agencies solve the big data revolutionThe_IPA
George Maynard, Group Head of DataScience at Annalect, shares his thoughts on how media agencies are coping with the big data revolution at an IPA 44 Club event in London. To learn more about The IPA visit www.ipa.co.uk and The 44 Club here www.ipa.co.uk/groups/44-club-2
VIETNAM ICT COMM CONFERENCE 2016 | ICT COMM VIETNAM - IT, Mobile, Hightech exhibition
Xu hướng ứng dụng và triển khai Big Data cho doanh nghiệp Việt Nam và Thế Giới.
Giải pháp & kiến trúc Hydrid - vừa tự làm + vừa outsourcing là chiến lược hiệu quả nhất trong năm 2016 cho phần lớn doanh nghiệp SME toàn cầu.
Cloud-Based IT Outsourcing:
The cloud benefits of scale, cost, and storage will alter big data initiatives by transforming IT departments.
The new paradigm for this organizational function will involve a hybridized architecture in which all but the most vital and longstanding systems are outsourced to complement existing infrastructure.
http://ants.vn
Top 20 artificial intelligence companies to watch out in 2022Kavika Roy
Artificial intelligence is fast becoming an intrinsic part of every industry.
It’s estimated that the global AI market will grow at a rate of 40.2% CAGR (Compound Annual Growth Rate) from the year 2021 to 2028. While the top names spend on research, the smaller organizations rely on offshore AI companies to embrace artificial intelligence and machine learning technology and integrate them into their business processes.
Working with the right AI company can help streamline the business operations, optimize the resources, and increase returns by changing the way management and employees perform their day-to-day activities at work.
Here are the top 20 artificial intelligence companies to watch out for in 2022:-
https://www.datatobiz.com/blog/top-artificial-intelligence-companies/
Identity Fraud Protection Using Big Data Analytics - StampedeCon 2015StampedeCon
Presented at StampedeCon 2015: As technology evolves, consumers are able to do more and more things in a remote setting—banking, shopping, communication, you name it. The more enabled we are, the more fraud is possible. As individuals use their identities to apply for goods and services – credit, loans, wireless phones, mortgages, etc. – certain patterns emerge. ID Analytics, a LifeLock company, quantitatively evaluates billions of data points, in real time, to understand identity risk. The algorithms behind our analysis come from the state-of-the-art machine learning community.
In this talk, we’ll describe the modes of identity fraud with examples of some fraud rings that we have observed along with details of the data structures and big data algorithms we use to catch identity fraud.
Data Analytics is ubiquitous. Some organisations like Netflix and Amazon are proficient in extracting significant Competitive Advantage from their while other like HP and IBM have extended this model to derive Corporate Advantage by aggregating the data layer across business units and portfolio companied. What if organisations across the sector combined their data to the elusive Sector Advantage?
TechConnex Big Data Series - Big Data in BankingAndre Langevin
TechConnex is an industry forum for Canadian IT executives. This presentation from the fall of 2015 provides a survey of Hadoop adoption in the Canadian banking industry. Most adoption is driven by BCBS-239 implementation projects. The talk provides a broader risk systems perspective on Hadoop and discusses challenges and opportunities around the technology.
Project 3 – Hollywood and IT· Find 10 incidents of Hollywood p.docxstilliegeorgiana
Project 3 – Hollywood and IT
· Find 10 incidents of Hollywood portraying IT security incorrectly
· You can use movies or TV episodes
· Write 2-5 paragraphs for each incident. Use supporting citations for each part.
· What has Hollywood portrayed wrong? Describe the scene and what is being shown. Make sure to state whether it is partially wrong or totally fictitious.
· How would you protect/secure against what they show (answers might include install firewall, load Antivirus etc.)
· Use APA formatting for your sources on everything.
· Make sure to put your name on assignment.
Big Data and Social Media
Colgate Palmolive
Agenda Of socail media use
Buisness intellegence and Social media concenpts
Intellegent organization
Data Anaylysis and Data trustworthiness
Conclusion
Buisness intellegence and Social media concenpts
No-Hassle Documentation
Gain Trusted Followers
Spy on Competition
Learn Customer Demographics
Research and Analyze Events
Advertise More Accurately
Intellegent organization
They consistently use (big) data proactively
They know exactly where they want to go: all-round vision
They continuously discuss business matters: alignment
They talk to each other regarding positive and negative performance
They know their customers through and through
They think and work in an agile way
Data Anaylysis and Data trustworthiness
Data completeness and accuracy
Data credibility
Data consistency
Data processing and algorithms
Data Validity
Conclusion
How Colgate benefit from Big Data and Social Media
Social media increases sales and customers
Big data shows popular trends and popular companies
All around they are both beneficial
Big Data can find trends that can benefit you greatly
Criteria
Title Page:
Name, Contact info, title of Presentation
Slide 1
Adenda : Topic you going to cover in order
Slide 2
Discuss how big data, social media concepts and knowledge to successfully create business intellegence (Support your bullets points with data, analysis, charts)
Slide 3
Describe how big data can be used to build an intelligent organization
Slide 4
Discuss the importance of data source trustworthiness and data analysis
Slide 5
Conclusion
Slide 6
Big Data And Business Intelligence
Business Value With Big Data
For business to survive in a competitive environment, organizational change requires improved governance, sponsorship, processes, and controls, in addition to new skill sets and technology all work in harmony to deliver the benefits of big data. See Fig. 13.2
Data science has taken the business world by storm. Every field of study and area of business has been affected as companies realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de fac to programming language for data science. Its flexibility, power, sophistication, and expressiveness have ma ...
Keeping pace with technology and big data.pdfClaire D'Costa
How IT companies can bridge the gap between ever-increasing talent needs and ever-changing technology?
In this pdf, you will get to know:
1- The technology's part in the play
2- The widening skills gap
3- Ways to fill up the void
4- Future of Big Data
5- Other useful insights
Big Data, Trends,opportunities and some case studies( Mahmoud Khosravi)Mahmood Khosravi
Humans have been generating data for thousands of years. More recently we have seen
an amazing progression in the amount of data produced from the advent of mainframes
to client server to ERP and now everything digital. For years the overwhelming amount
of data produced was deemed useless
How AI and blockchain can help you earn a passive income Blockchain Council
The past decade has been abuzz with speculation about both Artificial Intelligence and Blockchain Technology. Both hold enormous potential for human society as it stands and has both taken a long time to produce fruitful products. Highly developed AI modules are already entering the real world in products such as spam filtration, AI-based chess engines, and even self-driving cars. The true genius of such inventions is that they can produce code independently to solve problems in real time without any need for intervention from human beings. So let’s look at ways in which these strengths can be combined with blockchains to produce passive income investors.
In:Confidence 2019 - A foundation for Insight in a data-rich worldPrivitar
Jason Perkins, Head of Data & Analytics Architecture, BT, talks about the BT data strategy on the In:Confidence 2019 main stage (April 4th at Printworks, London).
Blockchain Patents for Innovation Data 3Q 2018 is a custom research of TechIPm, LLC (http://www.techipm.com) based on blockchain patents search in the USPTO database as of 3Q 2018. Total of 1246 patents (published patent applications & issued patents) are identified as blockchain patents indicating blockchain technology innovation activities.
Top 10 assignees/applications are IBM, Bank of America, Mastercard, Wal-Mart, TD Bank, Intel, American Express, Accenture, Cognitive Scale, Inc., and Coinbase.
The identified blockchain patents are further classified by key technologies for blockchain applications: security, transaction, cryptocurrency, database, smart contract, blockchain network, consensus, decentralized application, and AI.
INFOGRAPHIC: The Internet of Things: Are Organizations Ready For A Multi-Tril...Capgemini
The Internet is expanding. And this is not just in terms of getting accessible to more people; it is expanding beyond humans. Machines are becoming connected. Machines are talking to humans, but increasingly, they are also talking to one another. And this interconnectedness of machines, or the Internet of Things (IoT), is a potential multi-trillion dollar market that organizations can now tap into.
Abstract della presentazione di Fabio Rizzotto, IT Research & Consulting Director di IDC Italia, tenuta all’IDC Big Data Conference II, a Bologna il 19 novembre 2013
How Artificial Intelligence Is Revolutionizing Logistics Management?Maruti Techlabs
The rise of Artificial Intelligence has fundamentally altered many sectors of the supply chain industry. Whether it is customer support, inventory management or handling of logistics, the contribution of new age, AI-based solutions is undeniable.
As per executives and experts within the field, the prediction is clear – AI is here to stay and further transform these fields over the upcoming years.
Computers can handle huge sets of data at a time, which would otherwise be impossible to humanely take into a single decision-making process. This is why Artificial Intelligence is a boon to Supply Chain Management.
Using numerous data sets and applying intelligent algorithms, a machine can analyse endless possibilities that lead to effective strategizing.
AI minimizes the risks of human error. In short, with the help of AI, operational efficiency can be maximized and costs can be minimized.
A #research study by @Accenture shows that AI has the potential to boost profitability rates by an average of 38% by 2035 & lead to an economic boost of US$14 trillion across 16 industries by 2035.
#Training & updating AI models over time with the right expertise can pave the path to determining superiority in the domain of supply chain #management.
Some leading companies that use AI in Logistics:
@Rolls-Royce
@UPS
@Lineage Logistics
Link to the complete article in the comments below ⬇️
#AI #supplychain
How media agencies solve the big data revolutionThe_IPA
George Maynard, Group Head of DataScience at Annalect, shares his thoughts on how media agencies are coping with the big data revolution at an IPA 44 Club event in London. To learn more about The IPA visit www.ipa.co.uk and The 44 Club here www.ipa.co.uk/groups/44-club-2
VIETNAM ICT COMM CONFERENCE 2016 | ICT COMM VIETNAM - IT, Mobile, Hightech exhibition
Xu hướng ứng dụng và triển khai Big Data cho doanh nghiệp Việt Nam và Thế Giới.
Giải pháp & kiến trúc Hydrid - vừa tự làm + vừa outsourcing là chiến lược hiệu quả nhất trong năm 2016 cho phần lớn doanh nghiệp SME toàn cầu.
Cloud-Based IT Outsourcing:
The cloud benefits of scale, cost, and storage will alter big data initiatives by transforming IT departments.
The new paradigm for this organizational function will involve a hybridized architecture in which all but the most vital and longstanding systems are outsourced to complement existing infrastructure.
http://ants.vn
Top 20 artificial intelligence companies to watch out in 2022Kavika Roy
Artificial intelligence is fast becoming an intrinsic part of every industry.
It’s estimated that the global AI market will grow at a rate of 40.2% CAGR (Compound Annual Growth Rate) from the year 2021 to 2028. While the top names spend on research, the smaller organizations rely on offshore AI companies to embrace artificial intelligence and machine learning technology and integrate them into their business processes.
Working with the right AI company can help streamline the business operations, optimize the resources, and increase returns by changing the way management and employees perform their day-to-day activities at work.
Here are the top 20 artificial intelligence companies to watch out for in 2022:-
https://www.datatobiz.com/blog/top-artificial-intelligence-companies/
Identity Fraud Protection Using Big Data Analytics - StampedeCon 2015StampedeCon
Presented at StampedeCon 2015: As technology evolves, consumers are able to do more and more things in a remote setting—banking, shopping, communication, you name it. The more enabled we are, the more fraud is possible. As individuals use their identities to apply for goods and services – credit, loans, wireless phones, mortgages, etc. – certain patterns emerge. ID Analytics, a LifeLock company, quantitatively evaluates billions of data points, in real time, to understand identity risk. The algorithms behind our analysis come from the state-of-the-art machine learning community.
In this talk, we’ll describe the modes of identity fraud with examples of some fraud rings that we have observed along with details of the data structures and big data algorithms we use to catch identity fraud.
Data Analytics is ubiquitous. Some organisations like Netflix and Amazon are proficient in extracting significant Competitive Advantage from their while other like HP and IBM have extended this model to derive Corporate Advantage by aggregating the data layer across business units and portfolio companied. What if organisations across the sector combined their data to the elusive Sector Advantage?
TechConnex Big Data Series - Big Data in BankingAndre Langevin
TechConnex is an industry forum for Canadian IT executives. This presentation from the fall of 2015 provides a survey of Hadoop adoption in the Canadian banking industry. Most adoption is driven by BCBS-239 implementation projects. The talk provides a broader risk systems perspective on Hadoop and discusses challenges and opportunities around the technology.
Project 3 – Hollywood and IT· Find 10 incidents of Hollywood p.docxstilliegeorgiana
Project 3 – Hollywood and IT
· Find 10 incidents of Hollywood portraying IT security incorrectly
· You can use movies or TV episodes
· Write 2-5 paragraphs for each incident. Use supporting citations for each part.
· What has Hollywood portrayed wrong? Describe the scene and what is being shown. Make sure to state whether it is partially wrong or totally fictitious.
· How would you protect/secure against what they show (answers might include install firewall, load Antivirus etc.)
· Use APA formatting for your sources on everything.
· Make sure to put your name on assignment.
Big Data and Social Media
Colgate Palmolive
Agenda Of socail media use
Buisness intellegence and Social media concenpts
Intellegent organization
Data Anaylysis and Data trustworthiness
Conclusion
Buisness intellegence and Social media concenpts
No-Hassle Documentation
Gain Trusted Followers
Spy on Competition
Learn Customer Demographics
Research and Analyze Events
Advertise More Accurately
Intellegent organization
They consistently use (big) data proactively
They know exactly where they want to go: all-round vision
They continuously discuss business matters: alignment
They talk to each other regarding positive and negative performance
They know their customers through and through
They think and work in an agile way
Data Anaylysis and Data trustworthiness
Data completeness and accuracy
Data credibility
Data consistency
Data processing and algorithms
Data Validity
Conclusion
How Colgate benefit from Big Data and Social Media
Social media increases sales and customers
Big data shows popular trends and popular companies
All around they are both beneficial
Big Data can find trends that can benefit you greatly
Criteria
Title Page:
Name, Contact info, title of Presentation
Slide 1
Adenda : Topic you going to cover in order
Slide 2
Discuss how big data, social media concepts and knowledge to successfully create business intellegence (Support your bullets points with data, analysis, charts)
Slide 3
Describe how big data can be used to build an intelligent organization
Slide 4
Discuss the importance of data source trustworthiness and data analysis
Slide 5
Conclusion
Slide 6
Big Data And Business Intelligence
Business Value With Big Data
For business to survive in a competitive environment, organizational change requires improved governance, sponsorship, processes, and controls, in addition to new skill sets and technology all work in harmony to deliver the benefits of big data. See Fig. 13.2
Data science has taken the business world by storm. Every field of study and area of business has been affected as companies realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de fac to programming language for data science. Its flexibility, power, sophistication, and expressiveness have ma ...
Keeping pace with technology and big data.pdfClaire D'Costa
How IT companies can bridge the gap between ever-increasing talent needs and ever-changing technology?
In this pdf, you will get to know:
1- The technology's part in the play
2- The widening skills gap
3- Ways to fill up the void
4- Future of Big Data
5- Other useful insights
Are you struggling to keep up with the evolving digital marketing landscape?
That’s where marketing technology – or MarTech – comes in. The right MarTech tools can help you automate tasks and streamline your workflow for better performance.
But how do you upgrade your MarTech stack to ensure you’re maximizing campaign effectiveness?
In this webinar, we’ll walk you through some of the leading tools and solutions you should consider including in your MarTech stack for 2023 and beyond.
Join iQuanti’s Vishal Maru, VP of Digital Solutions and Shaubhik Ray, Senior Director of Digital Analytics, as well as Tealium’s Josh Wolf, Director of Partner Solutions Consulting, as they discuss the implications, pros, and cons of the leading MarTech platforms.
Key Takeaways:
- How the MarTech landscape has evolved.
- Key considerations while selecting tools for your MarTech stack.
- Framework to assess your MarTech maturity.
The market is changing faster than ever, so make sure you don’t get left behind.
Not only is Artificial Intelligence and Machine Learning (AI/ML) becoming more mainstream in marketing, but new media such as over-the-top (OTT) and short-form video are also gaining traction – not to mention new privacy regulations, third-party cookie departure, Apple’s App Tracking Transparency (ATT) feature, and the launch of Google Analytics 4 (GA4).
Watch now and get the latest insights to inform your marketing strategy.
-Enrichment - Unlocking the value of data for digital transformation - Big Da...webwinkelvakdag
As pressure for digital transformation increases, companies must harness big data more effectively. But the well-known V’s of data—volume, variety, velocity—represent both opportunities and challenges. Data enrichment enables organizations to take full advantage of the benefits while addressing these typical problems. In this session, we look at what an enrichment workflow might look like and how it enhances data’s value across different use cases.
Empowering your Enterprise with a Self-Service Data Marketplace (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uqcAN0
Self-service is a major goal of modern data strategists. A successfully implemented self-service initiative means that business users have access to holistic and consistent views of data regardless of its location, source or type. As data unification and data collaboration become key critical success factors for organizations, data catalogs play a key role as the perfect companion for a virtual layer to fully empower those self-service initiatives and build a self-service data marketplace requiring minimal IT intervention.
Denodo’s Data Catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It provides business users with the tool to generate their own insights with proper security, governance, and guardrails.
In this session we will cover:
- The role of a virtual semantic layer in self-service initiatives
- Key ingredients of a successful self-service data marketplace Self-service (consumption) vs. inventory catalogs
- Best practices and advanced tips for successful deployment
- A Demonstration: Product Demo
- Examples of customers using Denodo’s Data Catalog to enable self-service initiatives
The use of new forms of data is not an evolution. Instead, powering big data supply chains, and innovating through new forms of analytics, is a step change.
New forms of data do not fit traditional architectures. Traditional supply chains were architected to use structured data with software using relational databases. The big data era will make many of the investments from the last decade obsolete.
Big data offers the opportunity to redefine supply chain processes from the outside-in (from the channel back) and define the customer-centric supply chain. This is in stark contrast to the inflexible IT investments installed over the last decade to respond inside-out based on order shipments. These traditional investments in Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and traditional Business Intelligence (BI) for reporting, improved the supply chain response, but did not allow the organization to sense, shape or orchestrate outside-in. New forms of data (e.g., images, social data, sensor transmission, input from global positioning systems (GPS), the Internet of Things, and unstructured text from email, blogs and ratings and reviews) offer new opportunities. They also require new techniques and technologies.
Big data offers new opportunities for the corporation to listen, test and learn, and respond faster. In this study, companies see the greatest opportunity to use big data for “demand” (to better know the customer and improve the response); however, actual investments are in “supply” not “demand.” Respondents view supply-centric projects like product traceability (involving product serialization and traceability), supply chain visibility and temperature controlled handling as important.
Is big data a problem or a new market opportunity? Like the respondents of this survey, we believe that big data represents an opportunity for all. In the study, one-fourth of respondents currently have a big data initiative. However, interest is growing. Sixty-five percent have or plan to have a big data initiative in the future. Despite the hype, and the intensity of marketing rhetoric in the market, in our year-over-year studies on big data we see very little change in activity.
Despite the fact that the IT group is more likely to see big data as a problem, 49% of those with a big data initiative report that it is headed by an IT leader.
Big data represents a new opportunity, but seizing it requires a new form of leadership. It can ignite new business models and drive channel opportunities. However, it cannot be big data for big data itself. Instead, the initiatives need to be aligned to business objectives with a focus on small and iterative projects. It requires innovation. To move forward, companies need to embrace new technologies and redesign processes. It is not the case of stuffing new forms of data into old processes.
Safeguarding customer and financial data in analytics and machine learningUlf Mattsson
Digital Transformation and the opportunities to use data in Analytics and Machine Learning are growing exponentially, but so too are the business and financial risks in Data Privacy. The increasing number of privacy incidents and data breaches are destroying brands and customer trust, and we will discuss how business prioritization can be benefit from a finance-based data risk assessment (FinDRA).
More than 60 countries have introduced privacy laws and by 2023, 65% of the world’s population will have its personal information covered under modern privacy regulations. We will discuss use cases in financial services that are finding a balance between new technology impact, regulatory compliance, and commercial business opportunity. Several privacy-preserving and privacy-enhanced techniques can provide practical security for data in use and data sharing, but none universally cover all use cases. We will discuss what tools can we use mitigate business risks caused by security threats, data residency and privacy issues. We will discuss how technologies like pseudonymization, anonymization, tokenization, encryption, masking and privacy preservation in analytics and business intelligence are used in Analytics and Machine Learning.
Organizations are increasingly concerned about data security in processing personal information in external environments, such as the cloud; and information sharing. Data is spreading across hybrid IT infrastructure on-premises and multi-cloud services and we will discuss how to enforce consistent and holistic data security and privacy policies. Increasing numbers of data security, privacy and identity access management products are in use, but they do not integrate, do not share common policies, and we will discuss use cases in financial services of different techniques to protect and manage data security and privacy.
Privacy preserving computing and secure multi-party computation ISACA AtlantaUlf Mattsson
A major challenge that many organizations faces, is how to address data privacy regulations such as CCPA, GDPR and other emerging regulations around the world, including data residency controls as well as enable data sharing in a secure and private fashion. We will present solutions that can reduce and remove the legal, risk and compliance processes normally associated with data sharing projects by allowing organizations to collaborate across divisions, with other organizations and across jurisdictions where data cannot be relocated or shared.
We will discuss secure multi-party computation where organizations want to securely share sensitive data without revealing their private inputs. We will review solutions that are driving faster time to insight by the use of different techniques for privacy-preserving computing including homomorphic encryption, k-anonymity and differential privacy. We will present best practices and how to control privacy and security throughout the data life cycle. We will also review industry standards, implementations, policy management and case studies for hybrid cloud and on-premises.
Big data refers to the vast amount of structured and unstructured data that inundates organizations on a daily basis. This data comes from various sources such as social media, sensors, digital transactions, mobile devices, and more.
Protecting data privacy in analytics and machine learning ISACA London UKUlf Mattsson
ISACA London Chapter webinar, Feb 16th 2021
Topic: “Protecting Data Privacy in Analytics and Machine Learning”
Abstract:
In this session, we will discuss a range of new emerging technologies for privacy and confidentiality in machine learning and data analytics. We will discuss how to put these technologies to work for databases and other data sources.
When we think about developing AI responsibly, there’s many different activities that we need to think about.
This session also discusses international standards and emerging privacy-enhanced computation techniques, secure multiparty computation, zero trust, cloud and trusted execution environments. We will discuss the “why, what, and how” of techniques for privacy preserving computing.
We will review how different industries are taking opportunity of these privacy preserving techniques. A retail company used secure multi-party computation to be able to respect user privacy and specific regulations and allow the retailer to gain insights while protecting the organization’s IP. Secure data-sharing is used by a healthcare organization to protect the privacy of individuals and they also store and search on encrypted medical data in cloud.
We will also review the benefits of secure data-sharing for financial institutions including a large bank that wanted to broaden access to its data lake without compromising data privacy but preserving the data’s analytical quality for machine learning purposes.
Big Data LDN 2018: THE NEXT WAVE: DATA, AI AND ANALYTICS IN 2019 AND BEYONDMatt Stubbs
Date: 14th November 2018
Location: Keynote Theatre
Time: 13:10 - 13:40
Speaker: Matt Aslett
Organisation: 451 Research
About: As 2018 draws to a close, Matt Aslett, Research VP, 451 Research looks ahead to 2019 and the key trends the research company’s Data, AI and Analytics team is anticipating for the year ahead, including the continued rise of DataOps; the increased importance of data science operationalisation; mainstream adoption of AI and machine learning; data platforms evolution; and the confluence of distributed database and blockchain technology in supporting the move towards planetary-scale data processing and analytics.
Impact of AI in Transforming Growing BusinessAndrew Leo
AI-powered data processing is creatively disrupting businesses across a diverse range of industries. It is reshaping businesses, boosting efficiency, and unlocking unprecedented levels of accuracy and uncovering new opportunities. Let's discuss the transformative power of AI together.
- Discover how AI streamlines operations
- Uncover insights faster with AI-driven analytics
- Enhance decision-making with predictive algorithms
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
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From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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/
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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Data Marketplace:
Speed to Value with MicroStrategy
& Flexible Architectures
2. Information, data, and graphics/drawings embodied in this document are strictly confidential and are supplied on the understanding that they will be held confidential and not disclosed to third parties without prior written consent of ICC.
Everyone is being disrupted
by the digital economy
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3. Information, data, and graphics/drawings embodied in this document are strictly confidential and are supplied on the understanding that they will be held confidential and not disclosed to third parties without prior written consent of ICC.
There will be winners and losers
3
Huge chunks of many markets are being devoured by smart nimble organizations.
Half the Fortune 500 companies that existed in 2000 have disappeared.
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Peter Senge
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“The only sustainable
competitive
advantage is an
organization’s ability
to learn faster than
the competition.”
Is this true?
Who invented digital photography and when?
• Steve Sasson – in the 70’s
Who did he work for and what division?
Were any patents filed and when did they expire?
What else happened that year?
Does the Peter Senge quote need a corollary?
How about: “using change-driven learning”
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Characteristics of change-driven learning
5
Focus Speed Business-driven Involvement
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What kind of data environment supports change-driven learning?
6
NEW
FIT
EASY
REPOSITORY
FIND
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What does it take to win in analytics and data? Make it easy.
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8. Information, data, and graphics/drawings embodied in this document are strictly confidential and are supplied on the understanding that they will be held confidential and not disclosed to third parties without prior written consent of ICC.
What is a Data Marketplace and why do you want one?
8
A Data Marketplace is a partnership
between IT and the business where:
• Business units and IT maintain data assets together
• Access to information is easy and intuitive
• Business people learn from each other
• Adding additional information is simple
Benefits of a Data Marketplace:
• Crowd sourcing improves data quality
• Better speed to market and lower costs
• Data Catalog improves ease of use
ShoppersPublishing
Data Scientists
Business Analysts
Data Analysts
Semantics
Views
Govern
Communicate
Catalog
STORE FRONT CUSTOMERS
Tools
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Acquisition
and Tagging
CurationPreparation and
Cataloging
Data Marketplace Architecture
9
Data Sources
Application Systems
Spreadsheets
Core Data
Warehouse
Data Marts &
User Specific
Objects
External
Data Sources
Data Lake
Metadata Services
ShoppersPublishing
Semantics
Views
Govern
Communicate
Catalog
STORE FRONT CUSTOMERSINVENTORYSUPPLY
Tools
Data Scientists
Business Analysts
Data Analysts
Virtuous Cycle
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Use case: Store operations
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Details to dashboards:
• HDFS to Hive tables
• Data Story Telling for requirements
• Files loaded into HDFS
• MicroStrategy Project defined on Hive tables
• MicroStrategy Intelligent Cubes
• MicroStrategy Dashboard
STORE FRONT CUSTOMERSINVENTORYSUPPLY
Semantics
Views
Govern
Communicate
Catalog
Tools
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Use case: Inventory flow
11
KPIs and metrics to dashboards:
• New sources added HDFS and to Hive tables
• Requirements and Prototype (RAP)
• KPIs and metric sources identified
• MicroStrategy Project created across sources
• MicroStrategy Intelligent Cubes
• MicroStrategy Dashboard
STORE FRONT CUSTOMERSINVENTORYSUPPLY
Semantics
Views
Govern
Communicate
Catalog
Tools
12. Information, data, and graphics/drawings embodied in this document are strictly confidential and are supplied on the understanding that they will be held confidential and not disclosed to third parties without prior written consent of ICC.
Questions?
