You might have not heard most of these names yet, but you surely will soon. This list is designed to recognize emerging talent in the fields of data and analytics – mostly entrepreneurs and up-and-coming talent who are informing, educating and inspiring others through data. They come from different sectors and backgrounds – from data architecture to visualization. The one thing that unites them is their passion for data.
Graph Data Modeling in Four Dimensions – Outline, Differences, Artisanship, A...DATAVERSITY
Graph Data Modeling is, needless to say, good for graph databases. But it can also serve as a general conceptual/logical model. This webinar explains all aspects, starting with an overview, then moving into differences between Graph Data Modeling and “Classic” Data Modeling, best practices of graph modeling, and modeling in agile manners.
In short, graph data models are:
- Fast to deliver
- Flexible enough to allow agile schema evolution as you go
- Intuitive to read, also for business users
- Richer in semantics than ERD diagrams
- Easily mappable to many contemporary types of platforms, not only graph
- Derivable from many legacy models such as UML, etc.
- Well suited for knowledge graphs, of course
Do not miss the train! Get started on Graph Data Modeling by participating in this webinar!
How Do You Improve Data Skills and Data Literacy in your Business?Bernard Marr
Data literacy should be a priority for every organization. Investing in data skills and data literacy is critical for all companies today. Most companies have a deficit in data skills that should be addressed as quickly as possible. There are several ways to improve data skills and data literacy in your business.
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/
Sharing the story on how connected architecture came into being. The thought process that has led up to a people perspective on data architecture and what it takes to create a sustainable data landscape.
This presentation was given at the Free Frogs customer day in May 2018.
Big Data; Big Potential: How to find the talent who can harness its powerLucas Group
Big Data is in its infancy but it holds great promise. The key to success is finding and keeping the talent with the skills necessary to obtain and analyze the data, ask the right questions, and present findings in a compelling fashion that makes sense for your organization.
Graph Data Modeling in Four Dimensions – Outline, Differences, Artisanship, A...DATAVERSITY
Graph Data Modeling is, needless to say, good for graph databases. But it can also serve as a general conceptual/logical model. This webinar explains all aspects, starting with an overview, then moving into differences between Graph Data Modeling and “Classic” Data Modeling, best practices of graph modeling, and modeling in agile manners.
In short, graph data models are:
- Fast to deliver
- Flexible enough to allow agile schema evolution as you go
- Intuitive to read, also for business users
- Richer in semantics than ERD diagrams
- Easily mappable to many contemporary types of platforms, not only graph
- Derivable from many legacy models such as UML, etc.
- Well suited for knowledge graphs, of course
Do not miss the train! Get started on Graph Data Modeling by participating in this webinar!
How Do You Improve Data Skills and Data Literacy in your Business?Bernard Marr
Data literacy should be a priority for every organization. Investing in data skills and data literacy is critical for all companies today. Most companies have a deficit in data skills that should be addressed as quickly as possible. There are several ways to improve data skills and data literacy in your business.
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/
Sharing the story on how connected architecture came into being. The thought process that has led up to a people perspective on data architecture and what it takes to create a sustainable data landscape.
This presentation was given at the Free Frogs customer day in May 2018.
Big Data; Big Potential: How to find the talent who can harness its powerLucas Group
Big Data is in its infancy but it holds great promise. The key to success is finding and keeping the talent with the skills necessary to obtain and analyze the data, ask the right questions, and present findings in a compelling fashion that makes sense for your organization.
ADV Slides: Strategies for Transitioning to a Cloud-First EnterpriseDATAVERSITY
A great comfort with cloud deployment has emerged. Businesses are migrating databases to the cloud or building databases there as a result of scale challenges with the on-premises model, the cloud becoming the “center of gravity”, on-premises databases reaching capacity or emerging uses cases that are specific to the cloud. But not all organizations! And some struggle mightily with the move!
Learn about the factors that impact organizations when shifting data and applications to the cloud. What must you consider as you move significant applications and data to the cloud? This webinar will cover the major decision points that management needs to consider when moving to the cloud.
These include changes to the software model, development and quality assurance, recovery outage, and disaster recovery as well as new concerns about query performance and service levels, data interchange in the cloud, safe harbor and cross-border restrictions, and security and privacy.
We’ll also cover the new models for capacity planning and growth and staff responsibilities, the need for increased organizational change management, and how to pick targets for the journey.
DAS Slides: Graph Databases — Practical Use CasesDATAVERSITY
Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?
Was Big Data worth it? We were promised a data revolution when Big Data and Hadoop exploded onto the scene – but those technologies brought with them ungoverned, underexploited, complex environments that didn’t solve the analytical problems they were supposed to. All is not lost, however. This webcast explores three important things we’ve learned from Big Data that can be applied to every kind of data environment: modern approaches to data that exploit the flexibility and power of Big Data without losing the governance and management our businesses need.
Leave IT Alone – The Vast Value of Self-ServiceDATAVERSITY
As more and more business roles are expected to be data-driven, the demand for data is growing exponentially. The only way businesses can scale data-driven decision-making is with self-service. But ungoverned self-service access to data doesn't necessarily lead to better decisions. So the critical question for businesses is how to enable analysts and casual business users to self-serve data in a meaningful and trustworthy way. Check out this episode of Deep Dive to find out! Host Eric Kavanagh will share insights about best practices and great ideas in the field of self-service BI. He'll be joined by Kenny Cunanan of Looker, who will explain how practical guard rails can keep users on track, while enabling them to explore data in ways that spark ideas and lead to better decisions.
DAS Slides: Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Big Challenges in Data Modeling Webinar: Data Security, Data Breaches – Data ...DATAVERSITY
We invite you to join us in this monthly DATAVERSITY webinar series, “Big Challenges with Data Modeling” hosted by Karen Lopez. Join Karen and guest expert panelists each month to discuss their experiences in breaking through these specific data modeling challenges. Hear from experts in the field on how and where they came across these challenges and what resolution they found. Join them in the end for the Q&A portion to ask your own questions on the challenge topic of the month.
Social media and relationship development for salesEconsultancy
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
Data-Ed Online Webinar: Monetizing Data ManagementDATAVERSITY
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Takeaways:
Learn to think about data differently, in terms of how it can drive organizational needs. Data is not an IT solution but an information solution.
Take a broad view to ensure data sharing across organizational silos
Start small and go for quick wins: Build momentum and support
Global Data Management: Governance, Security and Usefulness in a Hybrid WorldNeil Raden
With Global Data Management methodology and tools, all of your data can be accessed and used no matter where it is or where it is from: on-premises, private cloud, public cloud(s), hybrid cloud, open source, third-party data and any combination of the these, with security, privacy and governance applied as if they were a single entity. Ingenious software products and the economics of computing make it economical to do this. Not free, but feasible.
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleVasu S
Real-world data science practitioners offer perspectives and advice on six common Machine Learning problems
https://www.qubole.com/resources/ebooks/oreilly-ebook-machine-learning-at-enterprise-scale
ADV Slides: Modern Analytic Data Architecture Maturity ModelingDATAVERSITY
Maturity frameworks have varying levels of Data Management maturity. Each level corresponds to not only increased data maturity, but also increased organizational maturity and bottom-line ROI. There are recommended targets to achieve an effective information management program. The speaker’s maturity framework sequences the information management activities for your consideration. It is based on real client roadmaps. This webinar promises to offer a wealth of ideas for key quick wins to benefit the organization’s information management program.
Attendees can self-assess their current information management capabilities as we go through data strategy, organization, architecture, and technology, yielding an overall view of the current level of information management maturity.
This webinar provides a foundation for enhancing current data and analytic capabilities and updating the strategy and plans for achievement of improved information management maturity, aligned with major initiatives.
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Speed Matters - Intelligent Strategies to Accelerate Data-Driven DecisionsDATAVERSITY
COVID-19 has shown us the importance of data in being able to quickly make decisions when market variables are out of our control. In order to accelerate and harness the process, an organization needs an agile approach to data integration and analytics that avoids the limitations of predefined schemas and data models.
Learn from 451 Research, now part of S&P Global Market Intelligence, a leading global IT research and advisory firm, and Qlik about best practices that can help you accelerate the data to decision path with agility. You’ll understand how to:
-Rethink traditional assumptions about data management and analytic roles and technologies
-Recognize trends that drive the demand to reduce the time required to investigate, analyze and take action on business data.
See a new state of business intelligence, where the data pipeline is optimized to enable organizations to make decisions and act in real-time. Seeking alternatives to the traditional approaches to become more agile in today’s evolving market and economy? Then don’t miss this presentation!
Join us as we launch our 2015 webinar series, ‘Metadata Matters’, with Martin Garland, President of Concept Searching, and expert guest speaker Doug Miles, Director of Market Intelligence at AIIM, as they explore the state of the market for unstructured content. Find out what your peers are doing, what’s on the horizon, and how other organizations are tackling and solving many of the same metadata challenges that you face.
Unstructured data is both a liability and an opportunity. With the uncontrollable rate of unstructured content growth, organizations are beginning to realize that the time has come to proactively manage content from inception to disposal. The real problem that disruptively impacts the management of unstructured data is metadata. This informative webinar will discuss the factors that prevent and enable organizations to leverage metadata to improve the bottom line.
Topics to be discussed include:
• Are organizations living with or fixing the problem of metadata, and what is Business Critical Metadata?
• What are the biggest challenges your peers are facing in applications such as enterprise search, records management, security, migration, content management, collaboration, social tagging, and text analytics?
• Has the cloud become a debilitating factor when managing metadata?
• How is Microsoft changing the role of SharePoint, and what’s the impact of Office 365, OneDrive for Business, and Delve in managing content as an integrated enterprise asset?
• What are sound strategies that successful organizations use?
• Why adding structure and application functionality with metadata assists in identifying and achieving business value
• When evaluating vendors and tools, what are some of the questions you should ask?
• Hear case studies on how organizations have solved their challenges from an enterprise and a departmental level
ADV Slides: Strategies for Transitioning to a Cloud-First EnterpriseDATAVERSITY
A great comfort with cloud deployment has emerged. Businesses are migrating databases to the cloud or building databases there as a result of scale challenges with the on-premises model, the cloud becoming the “center of gravity”, on-premises databases reaching capacity or emerging uses cases that are specific to the cloud. But not all organizations! And some struggle mightily with the move!
Learn about the factors that impact organizations when shifting data and applications to the cloud. What must you consider as you move significant applications and data to the cloud? This webinar will cover the major decision points that management needs to consider when moving to the cloud.
These include changes to the software model, development and quality assurance, recovery outage, and disaster recovery as well as new concerns about query performance and service levels, data interchange in the cloud, safe harbor and cross-border restrictions, and security and privacy.
We’ll also cover the new models for capacity planning and growth and staff responsibilities, the need for increased organizational change management, and how to pick targets for the journey.
DAS Slides: Graph Databases — Practical Use CasesDATAVERSITY
Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?
Was Big Data worth it? We were promised a data revolution when Big Data and Hadoop exploded onto the scene – but those technologies brought with them ungoverned, underexploited, complex environments that didn’t solve the analytical problems they were supposed to. All is not lost, however. This webcast explores three important things we’ve learned from Big Data that can be applied to every kind of data environment: modern approaches to data that exploit the flexibility and power of Big Data without losing the governance and management our businesses need.
Leave IT Alone – The Vast Value of Self-ServiceDATAVERSITY
As more and more business roles are expected to be data-driven, the demand for data is growing exponentially. The only way businesses can scale data-driven decision-making is with self-service. But ungoverned self-service access to data doesn't necessarily lead to better decisions. So the critical question for businesses is how to enable analysts and casual business users to self-serve data in a meaningful and trustworthy way. Check out this episode of Deep Dive to find out! Host Eric Kavanagh will share insights about best practices and great ideas in the field of self-service BI. He'll be joined by Kenny Cunanan of Looker, who will explain how practical guard rails can keep users on track, while enabling them to explore data in ways that spark ideas and lead to better decisions.
DAS Slides: Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Big Challenges in Data Modeling Webinar: Data Security, Data Breaches – Data ...DATAVERSITY
We invite you to join us in this monthly DATAVERSITY webinar series, “Big Challenges with Data Modeling” hosted by Karen Lopez. Join Karen and guest expert panelists each month to discuss their experiences in breaking through these specific data modeling challenges. Hear from experts in the field on how and where they came across these challenges and what resolution they found. Join them in the end for the Q&A portion to ask your own questions on the challenge topic of the month.
Social media and relationship development for salesEconsultancy
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
Data-Ed Online Webinar: Monetizing Data ManagementDATAVERSITY
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Takeaways:
Learn to think about data differently, in terms of how it can drive organizational needs. Data is not an IT solution but an information solution.
Take a broad view to ensure data sharing across organizational silos
Start small and go for quick wins: Build momentum and support
Global Data Management: Governance, Security and Usefulness in a Hybrid WorldNeil Raden
With Global Data Management methodology and tools, all of your data can be accessed and used no matter where it is or where it is from: on-premises, private cloud, public cloud(s), hybrid cloud, open source, third-party data and any combination of the these, with security, privacy and governance applied as if they were a single entity. Ingenious software products and the economics of computing make it economical to do this. Not free, but feasible.
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleVasu S
Real-world data science practitioners offer perspectives and advice on six common Machine Learning problems
https://www.qubole.com/resources/ebooks/oreilly-ebook-machine-learning-at-enterprise-scale
ADV Slides: Modern Analytic Data Architecture Maturity ModelingDATAVERSITY
Maturity frameworks have varying levels of Data Management maturity. Each level corresponds to not only increased data maturity, but also increased organizational maturity and bottom-line ROI. There are recommended targets to achieve an effective information management program. The speaker’s maturity framework sequences the information management activities for your consideration. It is based on real client roadmaps. This webinar promises to offer a wealth of ideas for key quick wins to benefit the organization’s information management program.
Attendees can self-assess their current information management capabilities as we go through data strategy, organization, architecture, and technology, yielding an overall view of the current level of information management maturity.
This webinar provides a foundation for enhancing current data and analytic capabilities and updating the strategy and plans for achievement of improved information management maturity, aligned with major initiatives.
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Speed Matters - Intelligent Strategies to Accelerate Data-Driven DecisionsDATAVERSITY
COVID-19 has shown us the importance of data in being able to quickly make decisions when market variables are out of our control. In order to accelerate and harness the process, an organization needs an agile approach to data integration and analytics that avoids the limitations of predefined schemas and data models.
Learn from 451 Research, now part of S&P Global Market Intelligence, a leading global IT research and advisory firm, and Qlik about best practices that can help you accelerate the data to decision path with agility. You’ll understand how to:
-Rethink traditional assumptions about data management and analytic roles and technologies
-Recognize trends that drive the demand to reduce the time required to investigate, analyze and take action on business data.
See a new state of business intelligence, where the data pipeline is optimized to enable organizations to make decisions and act in real-time. Seeking alternatives to the traditional approaches to become more agile in today’s evolving market and economy? Then don’t miss this presentation!
Join us as we launch our 2015 webinar series, ‘Metadata Matters’, with Martin Garland, President of Concept Searching, and expert guest speaker Doug Miles, Director of Market Intelligence at AIIM, as they explore the state of the market for unstructured content. Find out what your peers are doing, what’s on the horizon, and how other organizations are tackling and solving many of the same metadata challenges that you face.
Unstructured data is both a liability and an opportunity. With the uncontrollable rate of unstructured content growth, organizations are beginning to realize that the time has come to proactively manage content from inception to disposal. The real problem that disruptively impacts the management of unstructured data is metadata. This informative webinar will discuss the factors that prevent and enable organizations to leverage metadata to improve the bottom line.
Topics to be discussed include:
• Are organizations living with or fixing the problem of metadata, and what is Business Critical Metadata?
• What are the biggest challenges your peers are facing in applications such as enterprise search, records management, security, migration, content management, collaboration, social tagging, and text analytics?
• Has the cloud become a debilitating factor when managing metadata?
• How is Microsoft changing the role of SharePoint, and what’s the impact of Office 365, OneDrive for Business, and Delve in managing content as an integrated enterprise asset?
• What are sound strategies that successful organizations use?
• Why adding structure and application functionality with metadata assists in identifying and achieving business value
• When evaluating vendors and tools, what are some of the questions you should ask?
• Hear case studies on how organizations have solved their challenges from an enterprise and a departmental level
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...DATAVERSITY
A robust data architecture is at the core what’s driving today’s innovative, data-driven organizations. From AI to machine learning to Big Data – a strong data architecture is needed in order to be successful, and core fundamentals such as data quality, metadata management, and efficient data storage are more critical than ever.
With the vast array of new technologies available to support these trends, how do you make sense of it all? Our panel of experts will offer their perspectives on how the latest trends in data architecture can support your organization’s data-driven goals.
Data Modeling Best Practices - Business & Technical ApproachesDATAVERSITY
Data Modeling is hotter than ever, according to a number of recent surveys. Part of the appeal of data models lies in their ability to translate complex data concepts in an intuitive, visual way to both business and technical stakeholders. This webinar provides real-world best practices in using Data Modeling for both business and technical teams.
Big Data Trends and Challenges Report - WhitepaperVasu S
In this whitepaper read How companies address common big data trends & challenges to gain greater value from their data.
https://www.qubole.com/resources/report/big-data-trends-and-challenges-report
Key Lessons from 15 Data Leaders & Industry ExpertsBernard Marr
A new collaborative book project from the makers of leading semantic layer platform, AtScale, offers collective advice from a host of specialists from data science and business intelligence.
Similar to 20 Emerging influencers in 2020 for big data (20)
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.
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.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
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.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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.
1. You might have not heard most of these names yet, but you surely
will soon. This list is designed to recognize emerging talent in the
fields of data and analytics – mostly entrepreneurs and up-and-
coming talent who are informing, educating and inspiring others
through data. They come from different sectors and backgrounds –
from data architecture to visualization. The one thing that unites
them is their passion for data.
Emerging Influencers in 2020 For
Big Data, Data Science, &
Analytics
2. Big Data, Data Science, &
Analytics
1. Jordan Morrow, Global Head of Data Literacy at Qlik
Jordan is on a mission to close the data literacy skills gap and establish a data-
centric culture, dispelling the myth that only data scientists are qualified to work
on data analytics. As the Global Head of Data Literacy at Qlik, he helps
individuals and organizations realize their data and analytical potential by
strengthening their data literacy. In addition, Jordan is co-host of
the Transformation Nation Podcast, where you will find inspiring stories, lessons,
strategies, and tactics to maximize your potential.
2. Kimberly M Herrington, Data Journalist & Creator of WifiWarriors
Kimberly believes that anyone can work with data & analytics if they have
passion, limitless curiosity, and are not afraid to fail. She is a data journalist for
BlueCross BlueShield of Western New York, a division of HealthNow New York
Inc., one of New York’s leading health care companies. During this recent
healthcare crisis, Kimberly created WifiWarriors, an NGO connecting people and
resources to increase internet access. Their goal is to help facilitate free, no-
strings-attached access to WiFi during this public health crisis.
3. Big Data, Data Science, &
Analytics
3. Kate Stachnyi, Data Visualization Specialist & Founder of DATAcated
Kate is a true data visualization leader and an active voice in the community.
She founded the DATAcated Academy, a product agnostic resource focused on
delivering training on data visualization best practices. In addition, she is
currently building over a dozen Data to Dashboard courses that can take you
from looking at ‘data’ to designing a ‘dashboard’ using several tools.
4. Mico Yuk, CEO of BI Brainz Group and Host of Analytics on Fire Podcast
Mico is a BI powerhouse. Her BI & Analytics consulting company, BI
Brainz makes it easier for CIO, CDOs, and Business Intelligence leaders to work
with their users to create data visualizations that are story driven, have high user
adoption and use SMART KPIs. She’s on a mission to make BI applications more
visually appealing and easier to use. In addition, she is the host of Analytics on
Fire Podcast, a forum to learn all about analytics, design, data visualization,
mobility, cloud, internet of things and much more.
4. Big Data, Data Science, &
Analytics
5. Kristen Kehrer, Data Science Instructor, UC Berkley & Founder, Data
Moves Me
Kristen is not only a Data Science academic but also created Data Moves Me, a
company to help data science teams interpret their machine learning models and
fully communicate the caveats, influential variables, and paint a vivid picture of
the model in a way that their stakeholders will understand. Her expertise in
machine learning helps businesses that need to build trust and excitement
around predictive modeling work across the organization.
6. Sam Newman, Independent Technology Consultant, author of Building
Microservices
Sam is an independent consultant working worldwide, specializing in the area of
microservices, cloud, and continuous delivery. His most famous book, Building
Microservices, is already about to drop its 2nd edition. The book is aimed at data
practitioners and architects to help them understand what microservices are,
including the advantages and disadvantages, and contains lots of practical
advice to help implement microservices in your own organisation.
5. Big Data, Data Science, &
Analytics
7. Edward Beaurain, Director of Sales Operations and Programs at Tableau
Edward understands like no other the intersection between sales and data. He
has worked for over five years in multiple commercial roles for data visualization
leader Tableau, where he is currently Director of Sales Operations and
Programs. If you are a data-driven sales professional, you should definitely check
out Edward’s podcast in which he showcases ways how data can be leveraged
as the most powerful sales ally.
8. Hilary Mason, Data Scientist at Accel Partners & Co-founder Hack NY
Hilary Mason is working on something new, so watch this space! We’re looking
forward to seeing what she’s building. Her expertise in data as Accel Partners
Data Scientist as well as her past experience leading machine learning at
Cloudera makes us think whatever she does next will be worth following. In
addition, Hilary co-founded hackNY, a non-profit organization that mentors the
next generation of engineering talent for New York’s creative technology
community.
6. Big Data, Data Science, &
Analytics
9. Jason Krantz, CEO & Founder of Strategy Titan
Jason has been successful in translating data and analytical insights into
actionable business strategies and activities that drive higher revenues, greater
margins, and market/wallet share growth. With like-minded data scientists and
strategists, Jason formed Strategy Titan, a data analytics company that helps
organizations grow their top lines, bottom lines, and valuations by “weaponizing”
data and transforming it into a competitive advantage. Jason is also Co-host of
the podcast Transformation Nation, where he explores alongside Jason Morrow
(also on this list!) key tools and strategy for personal and professional
transformation.
10. Justin Butlion, Analytics Specialist and Founder of Project BI
Justin isn’t only an expert in analytics but also a true entrepreneur. He has
founded a number of businesses including Feedio (distribution tool for content
creators) and ProjectBI, an amazing resource to help analysts provide massive
value to their businesses, with videos and articles on a wide range of topics
including product analytics, data visualization, career development, and much
more. Justin is on a mission to help companies tackle their biggest data-related
challenges.
7. Big Data, Data Science, &
Analytics
11. Ilan Zaitoun, CTO & Co-Founder of Vision.bi
Ilan is a data mastermind. He Co-founded Vision.bi, a leading data company
that delivers high-scale data platforms and analytics for both enterprises and
startups – and recently developed Snowly, a tool for Snowflake users to keep
track of their cloud platform costs. Ilan has helped over 200 companies change
the way their businesses organize and treat data. His in-depth expertise in data
architecture and data pipelines includes establishing data processing
infrastructures in most of the databases in the market. As a leading force in cloud
data management, Ilan recently received the Person of The Year Award by
Snowflake in 2019.
12. Eric Weber, GM Experimentation at Yelp
Eric is the GM of experimentation and a data science leader at Yelp. He has an
impressive resume, having worked in leadership and individual contributor roles
at Yelp, LinkedIn, and CoreLogic after an academic career as an assistant
professor. Eric loves working with data, educating others about data’s value and
helping people excel in technical roles.
8. Big Data, Data Science, &
Analytics
13. Bruno Aziza, Group Vice President, AI & Data Analytics Cloud at Oracle
Bruno specializes in scaling businesses & turning them into global leaders. He
helped launch Alpine Data Labs (bought by Tibco), AppStream (bought by
Symantec), SiSense (bought Periscope Data) & AtScale. He specializes in high-
growth SaaS, enterprise software, everything data, analytics, data science and
artificial intelligence. In addition, Bruno has written two books on Data Analytics
and Enterprise Performance Management.
14. Andreas Kretz, CEO & Founder, Team Data Science
Andreas has been recognized by LinkedIn as a Top Voice in Data Science &
Analytics in 2018 and 2019. His company Team Data Science has courses and
tools to help people get into data engineering. His goal is to provide all the
resources needed to learn data engineering and also provide a platform for
collaboration. In addition, you should check out Andrea’s Data Engineering
Cookbook and his YouTube channel.
9. Big Data, Data Science, &
Analytics
15. Ken Jee, Content Creator and Head of Data Science at Scouts
Consulting Group
Ken is a master in sports analytics. For the past five years, he has been
analyzing sports and business problems, working with three major sports
organizations and amassing an arsenal of analytic techniques. His fast-
growing YouTube Channel explores multiple aspects of data science, from tips on
how to kickstart a career in data science, to videos with step-by-step guides to
build a data science project from scratch.
16. Matt Dancho, Founder & CEO, Business Science
In Matt’s own words, “There’s nothing better than extracting insights and
making better decisions with data.” Matt is the Founder & CEO of Business
Science, where he teaches data science. In addition, he designs and teaches
custom workshops for businesses, with past clients including S&P Global Market
Intelligence & MRM McCann. If you want to get involved, every two weeks Matt
hosts a FREE & LIVE webinar on advanced, intermediate, or cutting-edge topics
in data science, app development, or machine learning.
10. Big Data, Data Science, &
Analytics
17. Rob Silva, Sales Engineer Manager, Snowflake Computing
Rob has worked with some of the leading data management companies in the
world, including Microsoft, IBM, and currently Snowflake. He is an experienced
pre-sales leader that understands the importance of focusing on value. His
efforts and success were recently awarded as he was named Sales Engineer
Manager of The Year in 2019 by Snowflake.
18. Sarah Nooravi, Snr Financial Analyst, Snap Inc.
Sarah is a data junkie. In her own words “Question Everything. Answer with
data.” You should definitely follow Sarah on LinkedIn, where she frequently posts
insightful tips and advice on data science, productivity, and business excellence.
Prior to Snap, Sarah has worked as a data scientist across multiple industries
and companies including Fox, Operam, and MobilityWire. Her advice and insight
is always refreshing and smart.
11. Big Data, Data Science, &
Analytics
19. Sebastian Elkan, Data Scientist and Founder of Innovadomains
Sebastian is an interdisciplinary engineer, experienced in data analytics,
business intelligence, project management, process improvement, and teaching.
In addition, he is the founder of Innovadomains (new site launching soon!). He is
passionate about data science and helping people build their domain portfolio –
understanding domains as strategic digital assets to manage online reputation
and positioning. In addition, Sebastian is a seasoned speaker and trainer in data
science and analytics.
20. Favio Vazquez, Professor in Data Science & CEO of Closter
Favio is one of Mexico’s finest data advocates and a leader, with over 100k
followers on LinkedIn, where he consistently shares knowledge and ideas. In
addition to providing marketing and business consulting, Favio recently
founded Closter, an e-learning platform for Data Science. His live sessions on
LinkedIn are a great way to learn how to discover valuable insights from data
through Data Science.
12. Big Data, Data Science, &
Analytics
A Little About Us
Rivery helps you take control of your data and gives teams the freedom
they need to produce valuable insights and unlock new possibilities.
Our fully managed, cloud-based data integration platform
consolidates, orchestrates, and manages all of your internal and
external data sources with ease and efficiency. By offering
comprehensive data solutions and partnering with complementary
technology providers, Rivery enables you to build the perfect
infrastructure and ecosystem for your data processes.