How to identify the Return on Investment of Big Data / CIO (Infographic)
•
1 like•121 views
The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information
Report
Share
Report
Share
Download to read offline
Recommended
Top Ten Big Data Trends in Finance
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
Using Big Data in Finance by Jonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Pres_Big Data for Finance_vsaini
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
Banker 20 page 38 (BS)
The document discusses how banks can leverage big data and analytics to gain a competitive advantage. It notes that banks have large volumes of untapped customer data that, if analyzed ethically and legally, can be used to increase trust, retain customers, gain more business, and build loyalty. The chief data officer of Nedbank says banks need to create foundations to securely and effectively leverage customer data to empower teams. This includes strategies for data governance, technology, and developing a data-driven culture. The chief technology officer of Absa believes big data can be used to deeply personalize services for each customer based on their individual needs using artificial intelligence.
Data Monetization Framework
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
Big data it’s impact on the finance function
An introduction to Big Data for Finance Managers given at the Budgeting Solutions Finance Forum June 2013
BIG Data & Hadoop Applications in Finance
Explore the applications of BIG Data & Hadoop in Finance via Skillspeed.
BIG Data & Hadoop in Finance is a key differentiator, especially in terms of generating greater investment insights. They are used by companies & professionals for risk assessment, fraud detection & forecasting trends in financial markets.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
Định Hướng Dữ Liệu Trong Nền Kinh Tế Chia Sẻ: Uber, GrabTaxi, AirBnB
The document discusses data-driven marketing in the sharing economy. It defines data-driven marketing as acquiring, analyzing, and applying customer data to understand wants, needs, behavior, and motivations. Classical businesses miss opportunities by not utilizing data to provide customized experiences. Data can be used to achieve customer intimacy, design simple experiences, and actively listen to and respond to customers. The document provides examples of how mobility company ANTS uses real-time data from drivers and users to optimize operations, scheduling, predictions, and experiences.
Recommended
Top Ten Big Data Trends in Finance
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
Using Big Data in Finance by Jonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Pres_Big Data for Finance_vsaini
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
Banker 20 page 38 (BS)
The document discusses how banks can leverage big data and analytics to gain a competitive advantage. It notes that banks have large volumes of untapped customer data that, if analyzed ethically and legally, can be used to increase trust, retain customers, gain more business, and build loyalty. The chief data officer of Nedbank says banks need to create foundations to securely and effectively leverage customer data to empower teams. This includes strategies for data governance, technology, and developing a data-driven culture. The chief technology officer of Absa believes big data can be used to deeply personalize services for each customer based on their individual needs using artificial intelligence.
Data Monetization Framework
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
Big data it’s impact on the finance function
An introduction to Big Data for Finance Managers given at the Budgeting Solutions Finance Forum June 2013
BIG Data & Hadoop Applications in Finance
Explore the applications of BIG Data & Hadoop in Finance via Skillspeed.
BIG Data & Hadoop in Finance is a key differentiator, especially in terms of generating greater investment insights. They are used by companies & professionals for risk assessment, fraud detection & forecasting trends in financial markets.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
Định Hướng Dữ Liệu Trong Nền Kinh Tế Chia Sẻ: Uber, GrabTaxi, AirBnB
The document discusses data-driven marketing in the sharing economy. It defines data-driven marketing as acquiring, analyzing, and applying customer data to understand wants, needs, behavior, and motivations. Classical businesses miss opportunities by not utilizing data to provide customized experiences. Data can be used to achieve customer intimacy, design simple experiences, and actively listen to and respond to customers. The document provides examples of how mobility company ANTS uses real-time data from drivers and users to optimize operations, scheduling, predictions, and experiences.
Global data monetization market
Global data monetization Market is expected to reach US$ 4.9 Bn by 2026 from US$ 1.3 Bn in 2017 at a CAGR of 18.04%.
ANTS and BIG DATA - The it outsourcing trend - ICTCom 2016
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
The latest top 10 strategic technology trends
The document outlines Gartner's top 10 strategic technology trends for the year according to their latest report, including trends like mobile devices and apps, personal cloud, the internet of things, hybrid IT and cloud computing, strategic big data and actionable analytics, integrated ecosystems, and enterprise app stores. Big data is expected to drive $232 billion in IT spending through 2016 according to Gartner's analysis.
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCS
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCSTata Consultancy Services
In this opening key note, Ananth shared insights on technologies and trends that are changing the way we view atoms, people, materials, things and data, and how we can prepare ourselves to exploit these new opportunities.Data monetization webinar
This document discusses strategies for effective data monetization. It outlines challenges in data monetization like the increasing volume of data and the need for AI. It presents a data monetization maturity model and describes the top 5 best practices for successful data monetization as: getting the foundation right by infusing AI/data science; focusing on people like data engineers and scientists; constructing a robust business model; and ensuring trust and ethics. The document recommends using case generation and prioritization and provides industry examples. It promotes IBM Cloud Private for Data as an integrated analytics platform to overcome challenges and realize the benefits of data monetization.
10 Keynotes in STRATA and HADOOP World Conference
Strata and Hadoop is where data science and new business fundamentals merge. And, in Strata and Hadoop World Conference, there were many famous personalities who have given their views on Hadoop and Big data. In this PPT, you will get to know about speakers who have spoken on this topic.
Impact of big data on DCMI market
The key research findings how Big Data and Analytics are re-shaping the Data Center Infrastructure Management
Big Data LDN 2017: Pervasive Intelligence: the Future of Big Data, Machine Le...
Date: 16th November 2017
Location: Keynote Theatre
Time: 13:10 - 13:40
Speaker: Matt Aslett
Organisation: 451 Research
Future of Business Intelligence keynote
The document discusses the future of business intelligence. It provides a brief history of business intelligence, noting it was coined in 1989 to describe how end users could access and analyze company information. It then discusses how the term has been marketed differently over time by vendors. The document also examines emerging technologies like analytics, big data, artificial intelligence, and natural language processing that are shaping the future of business intelligence. It analyzes their position on Gartner's Hype Cycle and provides examples of how these technologies are being applied.
GraphTour - Opening Keynote
This document discusses graphs and graph databases. It provides examples of how organizations like eBay, NASA, and pharmaceutical companies use graph databases to connect disparate data sources and gain insights. Graph databases are becoming increasingly popular due to growth in connected data and can be used for applications like fraud prevention, product recommendations, and knowledge discovery. The document promotes Neo4j as the leading graph database and mentions its adoption by many large enterprises and upcoming cloud services.
Data monetization pov
Data monetization is generating revenue from data sources by capturing, analyzing, and disseminating data. It allows companies to sell data generated from customer interactions. To successfully monetize data, companies must understand their data assets, potential consumers, and how to add value through insights. A framework is needed to move raw data to solutions by assessing the data value stages from transactions to analytics. Various sectors can monetize data through use cases like banks providing merchant insights or telecom location data enabling targeted offers. Privacy and strategy are important considerations to effectively monetize data in the new digital economy.
Delivering data you can trust for data privacy
This document discusses delivering data privacy and compliance through establishing a data privacy hub. It outlines three key steps: 1) Know your data by capturing and tracking personal data through data cataloging. 2) Reconcile data using customer 360 degree views. 3) Take control of personal data through data stewardship and protecting data using techniques like data masking. It then provides examples of how major companies in hospitality, transportation, banking, and charities are using these approaches to gain control over personal data flows, enable personalization while respecting privacy, and streamline access rights fulfillment.
Top 15 Predictions about Data Analytics and AI for Decision Makers
Data Analytics and Artificial Intelligence are transforming businesses and societies in general. Know about how valuable they are for CXOs and other Decision Makers.
How to identify the Return on Investment of Big Data
OpenText is a leader in enterprise information management and analytics. It provides solutions for social and web data, ERP systems, databases, CRM, advanced analytics including risk management, fraud detection, and sales forecasting. OpenText offers analytics, data auditing and enrichment using big data sources. It also provides embedded analytics, visualization tools, and secure and scalable reporting capabilities.
Big Data Retail Banking
Nicolas has a vision of opening a French restaurant using his grandmother's recipes. He is discussing a loan with his banker. The banker not only offers the loan but also provides valuable business insights using data analytics. The banker examines demographic and spending data to recommend the best locations and price points for Nicolas's restaurant. This illustrates how banks can leverage big data to generate new revenue streams by providing business insights to customers.
ANTS - EXPLORE THE POWER OF BI & ANALYTICS | BIG DATA INDUSTRY INSIGHT 2015
Dr. Dinh Le Dat from ANTS Co-founder & CEO presented on big data industry insights from a global to Vietnam perspective. The presentation covered trends in big data usage, priority business problems in different industries, where to focus efforts, and case studies comparing approaches worldwide to those in Vietnam. The presentation provided an overview of big data applications and opportunities across various sectors drawing from analysis by Gartner.
Big Data Analytics in light of Financial Industry
Big data and analytics have the potential to transform economies and competition by delivering new productivity growth. Effective use of big data can increase operating margins over 60% for retailers and save $300 billion in US healthcare and $250 billion in European public sector. Companies that improve decision making through big data have seen a 26% performance improvement over 3 years on average. Emerging technologies like self-driving cars will rely heavily on analyzing vast amounts of real-time sensor data.
Data Monetization in a Corona Era
On behalf of SBI Consulting I’ve made a webinar on September 25th about Data Monetization.
In the post covid-19 era, transformation of businesses to govern their data more as an asset will become of huge importance. Becoming more data driven and digital will only increase at an unseen pace.
The essence of this transformation and the emphasis will be on Data Monetization. Monetizing your data assets will be of vital importance if you’d want to remain competitive and survive & thrive in the new normal.
In this webinar “Data Monetization in a post-Covid era”, I cover topics such as:
What does Data Monetization entails
Why Data Monetization is important for your business
How does the post-Covid era impacts this monetization process
What do we mean with Infonomics and Data Debt
The 5 key takeaways to get started with Data Monetization
The outcome? A good understanding of Data Monetization and practical insights to get going immediately!
Big data analytics in banking sector
The document discusses big data and big data analytics in banking. It defines big data as large, complex datasets that are difficult to process and store using traditional databases. Sources of big data include social media, sensors, transportation services, online shopping, and mobile apps. Characteristics of big data include volume, velocity, and variety. Hadoop is presented as an open source framework for analyzing big data using HDFS for storage and MapReduce for processing. The benefits of big data analytics in banking include fraud detection, risk management, customer segmentation, churn analysis, and sentiment analysis to improve customer experience.
Chief Data Officer: Customer Analytics Innovation
The document discusses a chief data officer's roadmap for using customer analytics and data to understand the "customer network". It mentions using big data, business intelligence, data architecture, data governance, data integration, data quality, data strategy, data visualization and other techniques to gain insights into customers, customer relationships, and customer behavior to improve customer centricity and relationships. The CDO's roadmap would help organizations transform their business using next generation data platforms and an open, customer-focused approach.
Three Dimensions of Data as a Service
This document summarizes a webinar on data as a service. It discusses how data virtualization through Denodo can enable agile business intelligence by providing pre-aggregated data to users quickly. It describes how Denodo creates API access to data, allows for an enterprise data marketplace, and integrates machine learning models to power operational AI. A demonstration of a personal COVID-19 risk monitor is provided.
MapR Enterprise Data Hub Webinar w/ Mike Ferguson
This document discusses best practices for using Hadoop as an enterprise data hub. It provides an overview of how big data is driving new analytical workloads and the need for deeper customer insights. It discusses challenges with analyzing new sources of structured, unstructured and multi-structured data. It introduces the concept of a Hadoop enterprise data hub and data refinery to simplify access to new insights from big data. Key components of the data hub include a data reservoir to capture raw data from various sources, a data refinery to cleanse and transform the data, and publishing high value insights to data warehouses and other systems.
More Related Content
What's hot
Global data monetization market
Global data monetization Market is expected to reach US$ 4.9 Bn by 2026 from US$ 1.3 Bn in 2017 at a CAGR of 18.04%.
ANTS and BIG DATA - The it outsourcing trend - ICTCom 2016
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
The latest top 10 strategic technology trends
The document outlines Gartner's top 10 strategic technology trends for the year according to their latest report, including trends like mobile devices and apps, personal cloud, the internet of things, hybrid IT and cloud computing, strategic big data and actionable analytics, integrated ecosystems, and enterprise app stores. Big data is expected to drive $232 billion in IT spending through 2016 according to Gartner's analysis.
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCS
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCSTata Consultancy Services
In this opening key note, Ananth shared insights on technologies and trends that are changing the way we view atoms, people, materials, things and data, and how we can prepare ourselves to exploit these new opportunities.Data monetization webinar
This document discusses strategies for effective data monetization. It outlines challenges in data monetization like the increasing volume of data and the need for AI. It presents a data monetization maturity model and describes the top 5 best practices for successful data monetization as: getting the foundation right by infusing AI/data science; focusing on people like data engineers and scientists; constructing a robust business model; and ensuring trust and ethics. The document recommends using case generation and prioritization and provides industry examples. It promotes IBM Cloud Private for Data as an integrated analytics platform to overcome challenges and realize the benefits of data monetization.
10 Keynotes in STRATA and HADOOP World Conference
Strata and Hadoop is where data science and new business fundamentals merge. And, in Strata and Hadoop World Conference, there were many famous personalities who have given their views on Hadoop and Big data. In this PPT, you will get to know about speakers who have spoken on this topic.
Impact of big data on DCMI market
The key research findings how Big Data and Analytics are re-shaping the Data Center Infrastructure Management
Big Data LDN 2017: Pervasive Intelligence: the Future of Big Data, Machine Le...
Date: 16th November 2017
Location: Keynote Theatre
Time: 13:10 - 13:40
Speaker: Matt Aslett
Organisation: 451 Research
Future of Business Intelligence keynote
The document discusses the future of business intelligence. It provides a brief history of business intelligence, noting it was coined in 1989 to describe how end users could access and analyze company information. It then discusses how the term has been marketed differently over time by vendors. The document also examines emerging technologies like analytics, big data, artificial intelligence, and natural language processing that are shaping the future of business intelligence. It analyzes their position on Gartner's Hype Cycle and provides examples of how these technologies are being applied.
GraphTour - Opening Keynote
This document discusses graphs and graph databases. It provides examples of how organizations like eBay, NASA, and pharmaceutical companies use graph databases to connect disparate data sources and gain insights. Graph databases are becoming increasingly popular due to growth in connected data and can be used for applications like fraud prevention, product recommendations, and knowledge discovery. The document promotes Neo4j as the leading graph database and mentions its adoption by many large enterprises and upcoming cloud services.
Data monetization pov
Data monetization is generating revenue from data sources by capturing, analyzing, and disseminating data. It allows companies to sell data generated from customer interactions. To successfully monetize data, companies must understand their data assets, potential consumers, and how to add value through insights. A framework is needed to move raw data to solutions by assessing the data value stages from transactions to analytics. Various sectors can monetize data through use cases like banks providing merchant insights or telecom location data enabling targeted offers. Privacy and strategy are important considerations to effectively monetize data in the new digital economy.
Delivering data you can trust for data privacy
This document discusses delivering data privacy and compliance through establishing a data privacy hub. It outlines three key steps: 1) Know your data by capturing and tracking personal data through data cataloging. 2) Reconcile data using customer 360 degree views. 3) Take control of personal data through data stewardship and protecting data using techniques like data masking. It then provides examples of how major companies in hospitality, transportation, banking, and charities are using these approaches to gain control over personal data flows, enable personalization while respecting privacy, and streamline access rights fulfillment.
Top 15 Predictions about Data Analytics and AI for Decision Makers
Data Analytics and Artificial Intelligence are transforming businesses and societies in general. Know about how valuable they are for CXOs and other Decision Makers.
How to identify the Return on Investment of Big Data
OpenText is a leader in enterprise information management and analytics. It provides solutions for social and web data, ERP systems, databases, CRM, advanced analytics including risk management, fraud detection, and sales forecasting. OpenText offers analytics, data auditing and enrichment using big data sources. It also provides embedded analytics, visualization tools, and secure and scalable reporting capabilities.
Big Data Retail Banking
Nicolas has a vision of opening a French restaurant using his grandmother's recipes. He is discussing a loan with his banker. The banker not only offers the loan but also provides valuable business insights using data analytics. The banker examines demographic and spending data to recommend the best locations and price points for Nicolas's restaurant. This illustrates how banks can leverage big data to generate new revenue streams by providing business insights to customers.
ANTS - EXPLORE THE POWER OF BI & ANALYTICS | BIG DATA INDUSTRY INSIGHT 2015
Dr. Dinh Le Dat from ANTS Co-founder & CEO presented on big data industry insights from a global to Vietnam perspective. The presentation covered trends in big data usage, priority business problems in different industries, where to focus efforts, and case studies comparing approaches worldwide to those in Vietnam. The presentation provided an overview of big data applications and opportunities across various sectors drawing from analysis by Gartner.
Big Data Analytics in light of Financial Industry
Big data and analytics have the potential to transform economies and competition by delivering new productivity growth. Effective use of big data can increase operating margins over 60% for retailers and save $300 billion in US healthcare and $250 billion in European public sector. Companies that improve decision making through big data have seen a 26% performance improvement over 3 years on average. Emerging technologies like self-driving cars will rely heavily on analyzing vast amounts of real-time sensor data.
Data Monetization in a Corona Era
On behalf of SBI Consulting I’ve made a webinar on September 25th about Data Monetization.
In the post covid-19 era, transformation of businesses to govern their data more as an asset will become of huge importance. Becoming more data driven and digital will only increase at an unseen pace.
The essence of this transformation and the emphasis will be on Data Monetization. Monetizing your data assets will be of vital importance if you’d want to remain competitive and survive & thrive in the new normal.
In this webinar “Data Monetization in a post-Covid era”, I cover topics such as:
What does Data Monetization entails
Why Data Monetization is important for your business
How does the post-Covid era impacts this monetization process
What do we mean with Infonomics and Data Debt
The 5 key takeaways to get started with Data Monetization
The outcome? A good understanding of Data Monetization and practical insights to get going immediately!
Big data analytics in banking sector
The document discusses big data and big data analytics in banking. It defines big data as large, complex datasets that are difficult to process and store using traditional databases. Sources of big data include social media, sensors, transportation services, online shopping, and mobile apps. Characteristics of big data include volume, velocity, and variety. Hadoop is presented as an open source framework for analyzing big data using HDFS for storage and MapReduce for processing. The benefits of big data analytics in banking include fraud detection, risk management, customer segmentation, churn analysis, and sentiment analysis to improve customer experience.
Chief Data Officer: Customer Analytics Innovation
The document discusses a chief data officer's roadmap for using customer analytics and data to understand the "customer network". It mentions using big data, business intelligence, data architecture, data governance, data integration, data quality, data strategy, data visualization and other techniques to gain insights into customers, customer relationships, and customer behavior to improve customer centricity and relationships. The CDO's roadmap would help organizations transform their business using next generation data platforms and an open, customer-focused approach.
What's hot (20)
ANTS and BIG DATA - The it outsourcing trend - ICTCom 2016
ANTS and BIG DATA - The it outsourcing trend - ICTCom 2016
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCS
Innovation Leadership in the Digital Age by K. Ananth Krishnan, VP and CTO, TCS
Big Data LDN 2017: Pervasive Intelligence: the Future of Big Data, Machine Le...
Big Data LDN 2017: Pervasive Intelligence: the Future of Big Data, Machine Le...
Top 15 Predictions about Data Analytics and AI for Decision Makers
Top 15 Predictions about Data Analytics and AI for Decision Makers
How to identify the Return on Investment of Big Data
How to identify the Return on Investment of Big Data
ANTS - EXPLORE THE POWER OF BI & ANALYTICS | BIG DATA INDUSTRY INSIGHT 2015
ANTS - EXPLORE THE POWER OF BI & ANALYTICS | BIG DATA INDUSTRY INSIGHT 2015
Similar to How to identify the Return on Investment of Big Data / CIO (Infographic)
Three Dimensions of Data as a Service
This document summarizes a webinar on data as a service. It discusses how data virtualization through Denodo can enable agile business intelligence by providing pre-aggregated data to users quickly. It describes how Denodo creates API access to data, allows for an enterprise data marketplace, and integrates machine learning models to power operational AI. A demonstration of a personal COVID-19 risk monitor is provided.
MapR Enterprise Data Hub Webinar w/ Mike Ferguson
This document discusses best practices for using Hadoop as an enterprise data hub. It provides an overview of how big data is driving new analytical workloads and the need for deeper customer insights. It discusses challenges with analyzing new sources of structured, unstructured and multi-structured data. It introduces the concept of a Hadoop enterprise data hub and data refinery to simplify access to new insights from big data. Key components of the data hub include a data reservoir to capture raw data from various sources, a data refinery to cleanse and transform the data, and publishing high value insights to data warehouses and other systems.
Building the Cognitive Era : Big Data Strategies
This document discusses big data and its applications. It begins with an overview of the growth of data and defines big data. Examples are given of how companies like Walmart, the CIA, and Puig use big data. The challenges of big data including volume, veracity, velocity and variety are described. Common applications of big data like customer insights, marketing, and risk detection are mentioned. The document outlines a roadmap for implementing a big data strategy and discusses technologies and terms. Success cases in fast moving consumer goods are presented. Finally, the benefits of big data for survival, strategic decisions, and cost reductions are noted.
Data science market insights usa
As 2017 begins, we are seeing big data and data science communities engage with new tools that specifically cater to data scientists and data engineers who aren’t necessarily experts in these techniques. Given rapid technological advances, the question for companies now is how to integrate new data science capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries. Leading companies are using their data science capabilities not only to improve their core operations but also to launch entirely new business models.
Choosing the Right Big Data Architecture for your Business
This document discusses choosing the right data architecture for big data projects. It begins by acknowledging big data comes in many types, from structured transactional data to unstructured text data. It then presents several big data architectures and platforms that are suitable for different data types and use cases, such as relational databases, NoSQL databases, data grids, and distributed file systems. The document emphasizes that one size does not fit all and the right choice depends on the specific data and business needs.
Integration of Big Data Analytics with IoT and OT Systems to Turn Insights in...
Presentation Main Points:
A- The Role of OT & IoT Systems in Digital Business Transformation
1- What is digital business
2- Digital business platform reference architecture
3- How to use the enterprise architecture to plan and implement digital business transformation
4- Use case: transportation industry digital business platform
B- How to Integrate Big Data Analytics with IoT and OT Systems
1- Basic definitions related to big data analytics
2- Essentials of big data strategy
3- Use cases of integrating big data analytics with IoT and OT systems (in transportation and petroleum industries)
4- Big data platform integration options and their cost benefit trade-offs
The boom in Xaas and the knowledge graph
The document discusses the growing importance of digital twins, knowledge graphs, and data-centric approaches to managing large, diverse datasets. It notes that current methods often struggle to integrate and contextualize data at scale. Effective digital twins and AI require integrated, disambiguated data flowing to where it's needed. Knowledge graphs are presented as a way to achieve this by providing a unified semantic model that treats relationships as a first-class citizen. The document outlines the large and growing markets for knowledge graph technologies and discusses how a data-centric approach can help enterprises better leverage emerging technologies.
Certus Accelerate - Building the business case for why you need to invest in ...
The document discusses building a business case for investing in data by highlighting the large percentage of unstructured data growth across different industries like healthcare, government, utilities and media. It emphasizes that 80% of new data is unstructured and invisible to computers. The world is being rewritten in software code and cloud is the new platform for reimagining industries. It then discusses the need for predictive, prescriptive and cognitive systems to make sense of vast amounts of data. Investing in data integration, governance and master data management is essential to unlock insights from all data sources and provide a comprehensive view of information. Justifying such investments requires looking at the potential costs of data quality failures and benefits of avoiding rework.
Smart Data Module 6 d drive the future
This document discusses the future of big data, including predictions such as machine learning becoming prominent and data scientists being in high demand. It outlines trends like the growth of open source technologies, in-memory computing, machine learning, predictive analytics, intelligent applications, integrating big data with security and the internet of things. Challenges mentioned include dealing with large amounts of data from IoT and high salaries for data professionals.
Maximize the Value of Your Data: Neo4j Graph Data Platform
In this 60-minute conversation with IDC, we will highlight the momentum and reasons why a graph data platform is a breakthrough solution for businesses in need of a flexible data model.
Please join Mohit Sagar, Group Managing Director of CIO Network, as he hosts the conversation with Dr. Christopher Lee Marshall, Associate VP at IDC, and Nik Vora, Vice President of APAC at Neo4. During this very exciting discussion, you'll discover the insights and knowledge unlocked with the graph data platform.
10 Enterprise Analytics Trends to Watch in 2020
As businesses face a 2020 reality check and use this year to hone their strategy for the next decade, MicroStrategy has compiled insights on the top enterprise analytics trends to watch from leading BI, analytics and digital transformation influencers including analysts from Forrester, IDC, Constellation Research, Ventana Research and more.
From artificial intelligence and mobile intelligence, to the explosion of data and data sources, to some very human factors, we hope you’ll find this gathering of insights (plus the patterns and themes that have emerged here) a valuable resource for taking action now, but also looking and planning ahead to become an Intelligent Enterprise.
The Path to Manageable Data - Going Beyond the Three V’s of Big Data
This document discusses how businesses can gain value from big data through effective analysis and actionable insights. It outlines the traditional "3 Vs" of big data (volume, velocity, variety) and additional "Vs" like veracity, variability, visualization, and value. Effective business analytics software can help validate data quality, analyze diverse data formats, and present insights visually for quick decision making. The document also provides examples like how a local authority used analytics software to transform large volumes of parking, service, and tax records into actionable reports.
QuickView #3 - Big Data
Forecast to contribute £216 billion to the UK economy via business creation, efficiency and innovation, and generate 360,000 new jobs by 2020, big data is a key area for recruiters.
In this QuickView:
- Big data in numbers
- Top 10 industries hiring big data professionals
- Top 10 qualifications sought by hirers
- Top 10 database and BI skills sought by hirers
- Getting started in big data: popular big data techniques and vendors
Quick view Big Data, brought by Oomph!, courtesy of our partner Sonovate
Quick view Big Data, brought by Oomph!, courtesy of our partner Sonovate
contact:
contact@oomphrecruitment.com
Prabal Acharyya - Industrial IoT
The document discusses how OSIsoft is helping industrial companies gain valuable operational intelligence from sensor-based IoT data through advanced analytics. It describes OSIsoft's PI Integrator product which prepares IIoT data for predictive and prescriptive analytics using technologies like SQL Server 2016 R Services. This enables customers to more quickly solve problems like equipment failures and optimize operations.
Bringing the Industrial IoT to life with advanced analytics
The document discusses how OSIsoft is helping industrial companies gain valuable operational intelligence from sensor-based IoT data through advanced analytics. It describes OSIsoft's PI Integrator product which prepares IIoT data for predictive and prescriptive analytics using technologies like SQL Server 2016 R Services. This enables customers to more quickly solve problems like equipment failures and optimize operations.
CS309A Final Paper_KM_DD
This document provides an overview of predictive analytics and its growing importance. It discusses how advances in technologies like cloud computing and the internet of things are enabling businesses to gather and analyze vast amounts of data. While descriptive and diagnostic analytics describe what happened in the past, predictive analytics uses statistical techniques to create models that forecast future outcomes. The document outlines several key drivers that are pushing predictive analytics towards mainstream adoption over the next few years, including easier-to-use tools, open source software, innovation from startups, and the availability of cloud-based solutions. It concludes that the combination of big data and predictive analytics will continue to accelerate innovation across industries.
Customer Experience: A Catalyst for Digital Transformation
Customer experience is a catalyst in many digital transformation projects. It is why many businesses invest in new technologies and processes to more effectively engage customers, constituents, or employees. The goal of putting digital tools to work in a transformative way is to ensure that data and insights connect people with information and processes that ultimately lead to a better experience for customers. Yet, it demands a modern approach that considers all of the platforms, processes, and data across the customer journey. The goal for many organizations is dynamically maintaining a single source of truth about each customer to drive personalized experiences based on individual preferences and behaviors.
However, businesses today have primarily invested in systems of record. While these systems are critical for managing internal operational processes, they are typically not effective for today's pace of business change. Insight-driven experiences require customer intelligence platforms that can finally create a customer 360. The deeper data and improved algorithms now available let users factor in individual affinity, segment, and a myriad of growing data sources. The result is greater relevance and effectiveness to deliver a differentiated experience that in today’s competitive landscape is not a luxury, but a necessity for survival.
In this session we will address:
3 things to learn:
•Leaders and Laggards of digital transformation
•How to create data-driven customer insights
•The importance of machine learning to uncover hidden insights
Why Big Data is a Top Priority for Enterprises - Infographics by RapidValue
This is an info-graphics which tells why Big Data is a top priority for enterprises. It also predicts the size of the Big Data industry By 2017 and the industries most likely to invest in Big Data. The info-graphic also talks about the most important areas of Big Data usage and use cases for various industries.
Dr. Maher salameh - new age of data analytics
This document discusses the rise of big data and analytics. It notes that analytics uses data, technology, and quantitative methods to help managers make better decisions. The amount of data is doubling every 18 months due to factors like the internet of things. Analytics needs to evolve to deliver collective insights by engaging users, enabling prediction, and helping users visualize data. Advanced analytics can help anticipate business trends in real-time. The document provides an example of how predictive analytics could be used in customer intelligence. It also notes challenges in detecting meaningful signals in big data and applying predictive algorithms, and how analytics needs to bridge skills gaps.
Similar to How to identify the Return on Investment of Big Data / CIO (Infographic) (20)
Choosing the Right Big Data Architecture for your Business
Choosing the Right Big Data Architecture for your Business
Integration of Big Data Analytics with IoT and OT Systems to Turn Insights in...
Integration of Big Data Analytics with IoT and OT Systems to Turn Insights in...
Certus Accelerate - Building the business case for why you need to invest in ...
Certus Accelerate - Building the business case for why you need to invest in ...
Maximize the Value of Your Data: Neo4j Graph Data Platform
Maximize the Value of Your Data: Neo4j Graph Data Platform
The Path to Manageable Data - Going Beyond the Three V’s of Big Data
The Path to Manageable Data - Going Beyond the Three V’s of Big Data
Quick view Big Data, brought by Oomph!, courtesy of our partner Sonovate
Quick view Big Data, brought by Oomph!, courtesy of our partner Sonovate
Bringing the Industrial IoT to life with advanced analytics
Bringing the Industrial IoT to life with advanced analytics
Customer Experience: A Catalyst for Digital Transformation
Customer Experience: A Catalyst for Digital Transformation
Why Big Data is a Top Priority for Enterprises - Infographics by RapidValue
Why Big Data is a Top Priority for Enterprises - Infographics by RapidValue
Recently uploaded
一比一原版(Unimelb毕业证书)墨尔本大学毕业证如何办理
原版制作【微信:41543339】【(Unimelb毕业证书)墨尔本大学毕业证】【微信:41543339】《成绩单、外壳、雅思、offer、留信学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同进口机器一比一制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
毕业原版【微信:176555708】【(UCSB毕业证书)圣芭芭拉分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Learn SQL from basic queries to Advance queries
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
Open Source Contributions to Postgres: The Basics POSETTE 2024
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
The Building Blocks of QuestDB, a Time Series Database
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
Analysis insight about a Flyball dog competition team's performance
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版制作【微信:41543339】【利兹贝克特大学毕业证(LeedsBeckett毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
毕业原版【微信:176555708】【(UCSF毕业证书)旧金山分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Population Growth in Bataan: The effects of population growth around rural pl...
A population analysis specific to Bataan.
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Intelligence supported media monitoring in veterinary medicine
Media monitoring in veterinary medicien
Global Situational Awareness of A.I. and where its headed
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Recently uploaded (20)
Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
How to identify the Return on Investment of Big Data / CIO (Infographic)
- 1. OPENTEXT™ IS THE LEADER IN ENTERPRISE INFORMATION MANAGEMENT SOCIAL WEB ERP RDBMS MYSQL CRM COLUMNAR DATABASE ADVANCED ANALYTICS RISK MANAGEMENT CUSTOMER PROFILE FRAUD DETECTION SALES FORECAST NEXT BEST OFFER CUSTOMER CHURN ANALYTICS: ADVANCED & PREDICTIVE ANALYTICS DATAAUDIT&ENRICHMENT BIG DATA SOURCES OPENTEXT™ BIG DATA ANALYTICS BIG DATA INSIGHTS REPORTING: EMBEDDED ANALYTICS OPENTEXT™ ANALYTICS DESIGNER OPENTEXT™ INFORMATION HUB USERS DESIGN DEPLOY VISUALIZATION HTML 5 VISUALS DATA OBJECTS REPORTS SECURE SCALE MANAGE Download at goo.gl/pHwF6a The Internet of Things and Business Intelligence from Dresner Advisory Services is a 70-page research that provides a wealth of information and analysis, offering value to both consumers and producers of business intelligence technology and services. The business intelligence vendor ratings include scores for location intelligence, end user data preparation, cloud BI, and advanced and predictive analytics–all key capabilities for business intelli- gence in an IoT context. Internet of Things Market Study From Dresner Advisory Services 2015 How to Identify Return of Investment of Big Data? OPENTEXT IS LEADER IN THE GARTNER MAGIC QUADRANT FOR ENTERPRISE CONTENT MANAGEMENT OPENTEXT IS LEADER IN THE FORRESTER WAVE™: ENTERPRISE BUSINESS INTELLIGENCE PLATFORMS, Q1 2015 OPENTEXT RANKED #1 FOR THE EMBEDDED BUSINESS INTELLIGENCE MARKET STUDY BY DRESNER 2015 95% CIO Business Use Cases Should Drive the Big Data Project, so Business Stakeholders Should be In- volved from Day One There Is an Anticipated 100,000+ Person Analytic Talent Shortage Through 2020 User Experience, Talent & Big Data Analytics Top the CIO Agenda for 2016 CIOs Will Need to Focus on Building Platforms to Support Algorithmic Business 95% of Organizations Want End Users to Be Able to Manage and Prepare Their Own Data Cloud Is the New Electricity and There Is Renewed Interest in Gaining Insights from Big Data The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information Most Organizations Consider Integration of Embedded Analytics to Be a Function of IT How OpenText Analytics Works Sources: "How to Improve Big Data ROI" by UPSIDE, "User experience, talent and analytics top the CIO agenda for 2016" by The Wall Street Journal, "Defining and Differentiating the Role of the Data Scientist" by Gartner, "Five top priorities for CIOs in 2016" by ZDNet, "IT Industry Outlook 2016" by CompTIA, "Dresner Internet of Things (IoT) Market Study 2015" by OpenText, "Dresner 2015 Embedded BI" by OpenText