The document discusses data and internet usage in Malaysia. It notes that 87.4% of Malaysians, or 28 million people, use the internet with smartphones being the main access point. Most Malaysians use internet for messaging apps and 31 million have Facebook accounts. The document also discusses Sarawak state government's digital transformation training program which aims to train 500 people in the first year. It explores how understanding business goals, data capabilities, skills, and tools are important for becoming a data-driven organization.
The document discusses key aspects of transforming a learning institution into a data-driven university (DDU). It outlines that a DDU aims to utilize data analytics to make higher education smarter and optimize management processes. Some key success factors for a DDU include developing industry-ready talent with skills in analytics, digital, and business and achieving operational excellence through analytics to build competitive resilience. The document also provides parameters that define a digital ecosystem and discusses barriers to digital transformation in education.
The document discusses the top 10 career fields in 2020 according to Melda Washington's class notes, including data analysis, counseling, scientific research, and computer engineering. It also outlines the characteristics, skills, tools, challenges, and salaries of database administrators. Women in database administration are highlighted, with the first woman to win an exceptional DBA award mentioned.
CIS14: NSTIC - Why the Identity Ecosystem Steering Group (IDESG)?CloudIDSummit
The document discusses the Identity Ecosystem Steering Group (IDESG), which aims to create an identity ecosystem framework that is privacy-enhancing, secure, interoperable, and easy to use. The IDESG is working to complete version 1 of the framework by the end of 2014. It also outlines how individuals and organizations can get involved by joining committees, attending events, or running for leadership positions to help shape the future of digital identity.
Contribution igf 2016 bpf cybersecurity by shreedeep rayamajhi rayznewsShreedeep Rayamajhi
Contributions to contribute to the IGF 2016 BPF on Cybersecurity.Best Practices Forums over the last two years, there has been an emerging consensus from the community that the 2016 cyber security BPF might most benefit from addressing cooperation and collaboration between stakeholder groups as a topic.
AidHub is an online project management platform available for free to aid, development, and nonprofit organizations. It aims to help such organizations increase their effectiveness and efficiency, enhance transparency, ensure security and privacy, and improve their ability to measure outcomes and impact. By providing common frameworks, best practices, and tools for planning, management, monitoring, and reporting, AidHub seeks to help organizations achieve their goals faster and with better results. It also facilitates collaboration and knowledge-sharing between organizations to further drive improvement.
Though now nascent, quantum science could have significant implications for national security. By taking simple pragmatic steps today, government leaders can prepare their organizations for the coming quantum future.
The document discusses key aspects of transforming a learning institution into a data-driven university (DDU). It outlines that a DDU aims to utilize data analytics to make higher education smarter and optimize management processes. Some key success factors for a DDU include developing industry-ready talent with skills in analytics, digital, and business and achieving operational excellence through analytics to build competitive resilience. The document also provides parameters that define a digital ecosystem and discusses barriers to digital transformation in education.
The document discusses the top 10 career fields in 2020 according to Melda Washington's class notes, including data analysis, counseling, scientific research, and computer engineering. It also outlines the characteristics, skills, tools, challenges, and salaries of database administrators. Women in database administration are highlighted, with the first woman to win an exceptional DBA award mentioned.
CIS14: NSTIC - Why the Identity Ecosystem Steering Group (IDESG)?CloudIDSummit
The document discusses the Identity Ecosystem Steering Group (IDESG), which aims to create an identity ecosystem framework that is privacy-enhancing, secure, interoperable, and easy to use. The IDESG is working to complete version 1 of the framework by the end of 2014. It also outlines how individuals and organizations can get involved by joining committees, attending events, or running for leadership positions to help shape the future of digital identity.
Contribution igf 2016 bpf cybersecurity by shreedeep rayamajhi rayznewsShreedeep Rayamajhi
Contributions to contribute to the IGF 2016 BPF on Cybersecurity.Best Practices Forums over the last two years, there has been an emerging consensus from the community that the 2016 cyber security BPF might most benefit from addressing cooperation and collaboration between stakeholder groups as a topic.
AidHub is an online project management platform available for free to aid, development, and nonprofit organizations. It aims to help such organizations increase their effectiveness and efficiency, enhance transparency, ensure security and privacy, and improve their ability to measure outcomes and impact. By providing common frameworks, best practices, and tools for planning, management, monitoring, and reporting, AidHub seeks to help organizations achieve their goals faster and with better results. It also facilitates collaboration and knowledge-sharing between organizations to further drive improvement.
Though now nascent, quantum science could have significant implications for national security. By taking simple pragmatic steps today, government leaders can prepare their organizations for the coming quantum future.
Cracking the Code: Data Science Tackles Investment ManagementSharala Axryd
The document discusses how data science can be used to enhance investment management operations. It describes how machine learning algorithms can be used to power robo advisors that provide tailored investment recommendations to clients based on their risk tolerance, behavior, and preferences. Neural networks can also be used for fraud detection by analyzing customer behavior and transactions to identify suspicious activities. Predictive analytics uses historical data to build models to analyze current data, while scenario-based analytics considers alternative future outcomes. The document also discusses how data science can help reduce cognitive biases that investors tend to have.
This document discusses the importance of data-driven decision making. It contains quotes from experts emphasizing how data is a valuable asset and currency for companies. The document outlines the steps companies should take to become more data-driven, including understanding business goals, exploring available data and analytic capabilities, assessing skills, and selecting tools that align with goals and skills. It also provides an example of Handelsbanken, a Swedish bank that could benefit from these practices. The document discusses challenges like data silos and the need for communication and centralized strategies, and stresses the importance of learning from failures through a test-and-learn culture.
The document discusses how analytics and data can help organizations improve performance and address common reasons why analytics projects fail. It provides examples of how a Swedish bank called Handelsbanken successfully uses an empowering culture and personalized service to remain highly profitable. The document advocates that organizations build cultures allowing sustainable performance, empower people, and communicate strategies clearly. It also discusses how tools like data visualization and storytelling can help internal auditors gain insights from big data and improve auditing.
Data Done Right: Ensuring Information IntegritySharala Axryd
It’s the ultimate “garbage in, garbage out” quandary. Data can be an organization’s most valuable asset — but only to the degree its quality can be validated and trusted. Without the right guidelines, processes, and solutions in place to control the way applications, systems, databases, messages, and documents are managed, "dirty" data can permeate systems across the enterprise, negatively impacting everything from strategic planning to day-to-day decision making. High-quality data will ensure more efficiency in driving a company’s success because of the dependence on fact-based decisions, instead of habitual or human intuition.
To gain a better understanding of this topic, this speaking session will examine:
- what data quality and master data management is
- why they are so crucial for successful business operations and strategies
- how to improve data quality by organizational, procedural and technological means
Technology has transformed the way people work. Leaders can resolidify their teams by developing a robust Workforce Augmented Strategy to adjust their leadership behaviour, embrace digital workforce platforms and deepen their engagement with digitally enabled workers.
Malaysian Insurance Institute (MII) together with The Center of Applied Data Science (CADS) Founder and CEO Sharala Axryd will run a webinar for leaders to create a center of excellence for data literacy that addresses business needs and talent potential identification.
In doing so, leaders will be able to:
- improve employee engagement and talent retention
- improve data literacy and close competency gap
- digitize operations and automate process
Data for Impact Fellowship - SocialCops CareersSocialCops
The Data for Impact Fellowship is a unique opportunity where fellows partner with leaders in government, bilateral organizations, foundations and nonprofits — ranging from Ministers, CEOs and District Collectors — to implement a scalable data intelligence solution. The Fellowship seeks to bring together young, enterprising future leaders with experienced leaders in the development sphere to use the power of data to solve some of India's most critical problems.
For more details about the Fellowship and to get started on your application, visit http://soco.ps/2BHK6Ba!
Data Is The New Oil: How Shell Has Become A Data-Driven And AI-Enabled Business Bernard Marr
Today, every organization must become a more data-driven business. While most understand that this is important, they might not know how to do it. Here we share insights and learning from energy-giant Shell on how to prioritize data-driven operations.
Data Science, Analytics and AI: Gamechangers for the Future of WorkSharala Axryd
The Center of Applied Data Science (CADS) was established in 2014 in Malaysia and expanded to Singapore in 2018. CADS aims to establish a global standard in data science and analytics education. It has produced over 1,000 data professionals and advised both government and corporate clients through its BOLT methodology of building capabilities, operating solutions, learning skills, and transferring knowledge. Data science and analytics roles such as data scientists, data analysts, and data engineers are in high demand with increasing salaries and opportunities for career advancement.
This document summarizes an upcoming two-day workshop on big data and government analytics to be held in Ottawa on March 24-25, 2015. The workshop will cover topics such as leveraging big data to improve government services, maximizing data sharing across departments, incorporating big data into overall data strategies, using big data for security purposes, and making data-driven decisions. It lists the workshop leaders and participating organizations, and provides an overview of the scheduled sessions and speakers.
The document discusses establishing a centralized data infrastructure in India to harness government data for public benefit. It proposes integrating distinct sets of government data, following models of other open data initiatives. A centralized architecture would provide authenticated data and documents to improve targeting of welfare programs while granting selected access to the private sector to spur innovation. Citizens would greatly benefit from consolidated access to relevant data to solve problems and harness data for their own benefit. The goal is to establish data as a public good generated and used for the people.
BRIDGING DATA SILOS USING BIG DATA INTEGRATIONijmnct
1) The document discusses how big data integration can be used to bridge data silos that exist in many enterprises due to different business applications generating structured, semi-structured, and unstructured data. 2) It explains that traditional data integration techniques are not well-suited for big data due to issues with scale and handling semi-structured and unstructured data. 3) Big data integration techniques like Hadoop, Spark, Kafka and data lakes can be better suited for integrating large heterogeneous data sources in real-time or in batches at scale.
This document discusses new ways of handling old data and unlocking value from unstructured content through cognitive systems. It provides predictions for big data and analytics spending and adoption through 2020. Key points include:
- 90% of digital information is unstructured content stored in separate repositories that don't communicate.
- By 2020, 50% of business analytics software will incorporate prescriptive analytics using cognitive computing.
- Organizations that can analyze all relevant data and provide actionable insights will gain $430 billion in productivity over less analytical peers.
- Cognitive software can support better decision-making by applying broader evidence without bias to situations.
- The cognitive software market is expected to grow rapidly over the next five
Hagar & Associates aims to connect cities through big data to improve services like transportation, water, power, and emergency response. They partnered with IBM to use Watson for data analysis. A student group recommends ways for Hagar & Associates to take interns from California State University, San Bernardino, including paperwork required. The document also provides a cyber security plan and recommendations to protect data in their system and cloud, including access controls, passwords, firewalls, and physical security of servers.
Data2030 Summit Data Megatrends Turner Sept 2022.pptxMatt Turner
The next challenge in data is rapidly becoming clear: how can we scale data value and bring data driven decision making to everyone? We’ve made tremendous progress in bringing data together. The megatrends in data - data mesh, data fabric, modern data stack - are all about crossing the last mile to get data to everyone, not just the data experts. How can we empower everyone to better use data? Are the megatrends the road to actually scaling data value? And what does that mean for the data teams and data engineers creating systems and delivering dataops?
Hadoop and Big Data Readiness in Africa: A Case of Tanzaniaijsrd.com
Big data has been referred to as a forefront pillar of any modern analytics application. Together with Hadoop which is open source software, they have emerged to be a solution to the processing of massive generated both structured and unstructured data. With different strategies and initiatives taken by governments and private institutions in the world towards deployment and support of big data analytics and hadoop, Africa cannot be left isolated. In this paper, we assessed the readiness of Africa with a case study of Tanzania in harnessing the power of big data analytics and hadoop as a tool for drawing insights that might help them make crucial decisions. We used a survey in collecting the data using questionnaires. Results reveal that majority of the companies are either not aware of the technologies or still in their infancy stages in using big data analytics and hadoop. We identified that most companies are in either awakening or advancing stages of the big data continuum. This is attributed by challenges such as lack of IT skills to manage big data projects, cost of technology infrastructure, making decision on which data are relevant, lack of skills to analyze the data, lack of business support and deciding on what technology is best compared to others. It has also been found out that most of the companies' IT officers are not aware with the concepts and techniques of big data analytics and hadoop.
Big Data in Malaysia: Emerging Sector Profile 2014Tirath Ramdas
Big Data has become part of everyday organisational parlance. Increasingly, this awareness is being transformed into practice. Support for harnessing data to amplify capabilities and achieve organisational objectives at practitioner and senior management levels is becoming aligned. A report by Forrester on Big Data adoption in Asia Pacific in 2013-2014 observed a trend across all industries of ‘using more types of data, from more sources, to enable timelier better-informed insights’. Similarly in Malaysia, there is growing cultural acceptance that Big Data can and should enhance decision-making processes, although pathways for adoption are not uniformly understood. Nevertheless, we are now observing a transition phase from curiosity and enthusiasm to buy-in and action across startup, corporate, and government organisations. This groundswell of interest fuels the basis of Big Data Malaysia, a networking group for professionals with interest in all things Big Data, including NoSQL, Hadoop, data science, visualisation, business use cases, data governance, open data, and more. Our community has welcomed participation from stakeholders ranging from computer scientists to data journalists, reflecting a broad societal interest in Big Data. Our mission is to encourage high caliber knowledge sharing and to provide a space for professionals with different interests to collaborate. This report grew out of a need to understand in more detail the various networks that Big Data Malaysia helps to connect. In order to support the Big Data ecosystem that we see emerging, we identified critical questions that required further investigation, in particular:
• What are the opportunities and barriers to Big Data activity in Malaysia?
• Who is merely ‘interested’, versus who is actually committed?
• What is the current and future capacity for Big Data talent?
• Where are the critical gaps in training and skills?
• What are the soft inhibitors, including data access, regulation and perception?
There are two parts to this report. The first includes results from a questionnaire, while the latter features interviews conducted in-person or via email. In collaboration with various partners, we devised and distributed a questionnaire online across our networks and collected responses during October 2013. In our final sample, we collected responses from 108 individuals over 90 organisations. As our report will show, these viewpoints represent a diversity of organisational stakeholders and industries in the Big Data space. We followed up with interviews of high-profile respondents for richer insight.
KM SHOWCASE 2020 - "Implementing Knowledge-as-a-Service through the Digital W...KM Institute
The document discusses implementing Knowledge-as-a-Service (KaaS) through a digital workplace. KaaS blends knowledge management and AI to deliver the right knowledge to users. It discusses using AI for predictive analytics, knowledge mapping and chatbots. A case study describes implementing a KaaS framework and digital workplace at the IMF to improve knowledge sharing, collaboration and process efficiency across devices. Key challenges included integrating tools and developing an extensible information architecture to enable search and machine learning.
This document discusses the growth of data and analytics capabilities. It notes that data storage capacity is growing at 23% annually while computing capacity is growing at 54% annually. Lower barriers to connectivity are integrating different sources of data. The document discusses how Right Brain Systems uses analytics to build smarter organizations by focusing on data foundation, information design, analytics capabilities, operational framework, and business ownership. It provides examples of how different types of analytics can be applied to key areas like customers, operations, finance, and workforce.
Big data refers to large and complex data sets that are difficult to process using traditional methods. The Center of Applied Data Science (CADS) was founded to address the need for data science talent in Malaysia by training the next generation of data professionals. CADS partners with leading organizations like the Data Incubator, Harvard Business School, and Coursera to provide rigorous data science education programs. The goal is to cultivate data talent and empower individuals and organizations to leverage big data for competitive advantage.
The Future of Work is Here: Are You Prepared?Sharala Axryd
The document discusses how technology is changing the nature of work and the future workforce. Automation and AI will significantly impact jobs over the coming decades, with some jobs being replaced while new jobs are created. To stay relevant, professionals need to continually learn new skills. The future workforce will require skills in problem solving, critical thinking, and emotional intelligence rather than just technical skills. While AI will replace some jobs, it will also create new types of jobs. Malaysia needs to take advantage of new technologies like AI, IoT, and big data to increase productivity and improve livelihoods. However, it has not fully reached Industry Revolution 3.0 yet. Women and underrepresented groups also remain an untapped resource, and empowering them
Cracking the Code: Data Science Tackles Investment ManagementSharala Axryd
The document discusses how data science can be used to enhance investment management operations. It describes how machine learning algorithms can be used to power robo advisors that provide tailored investment recommendations to clients based on their risk tolerance, behavior, and preferences. Neural networks can also be used for fraud detection by analyzing customer behavior and transactions to identify suspicious activities. Predictive analytics uses historical data to build models to analyze current data, while scenario-based analytics considers alternative future outcomes. The document also discusses how data science can help reduce cognitive biases that investors tend to have.
This document discusses the importance of data-driven decision making. It contains quotes from experts emphasizing how data is a valuable asset and currency for companies. The document outlines the steps companies should take to become more data-driven, including understanding business goals, exploring available data and analytic capabilities, assessing skills, and selecting tools that align with goals and skills. It also provides an example of Handelsbanken, a Swedish bank that could benefit from these practices. The document discusses challenges like data silos and the need for communication and centralized strategies, and stresses the importance of learning from failures through a test-and-learn culture.
The document discusses how analytics and data can help organizations improve performance and address common reasons why analytics projects fail. It provides examples of how a Swedish bank called Handelsbanken successfully uses an empowering culture and personalized service to remain highly profitable. The document advocates that organizations build cultures allowing sustainable performance, empower people, and communicate strategies clearly. It also discusses how tools like data visualization and storytelling can help internal auditors gain insights from big data and improve auditing.
Data Done Right: Ensuring Information IntegritySharala Axryd
It’s the ultimate “garbage in, garbage out” quandary. Data can be an organization’s most valuable asset — but only to the degree its quality can be validated and trusted. Without the right guidelines, processes, and solutions in place to control the way applications, systems, databases, messages, and documents are managed, "dirty" data can permeate systems across the enterprise, negatively impacting everything from strategic planning to day-to-day decision making. High-quality data will ensure more efficiency in driving a company’s success because of the dependence on fact-based decisions, instead of habitual or human intuition.
To gain a better understanding of this topic, this speaking session will examine:
- what data quality and master data management is
- why they are so crucial for successful business operations and strategies
- how to improve data quality by organizational, procedural and technological means
Technology has transformed the way people work. Leaders can resolidify their teams by developing a robust Workforce Augmented Strategy to adjust their leadership behaviour, embrace digital workforce platforms and deepen their engagement with digitally enabled workers.
Malaysian Insurance Institute (MII) together with The Center of Applied Data Science (CADS) Founder and CEO Sharala Axryd will run a webinar for leaders to create a center of excellence for data literacy that addresses business needs and talent potential identification.
In doing so, leaders will be able to:
- improve employee engagement and talent retention
- improve data literacy and close competency gap
- digitize operations and automate process
Data for Impact Fellowship - SocialCops CareersSocialCops
The Data for Impact Fellowship is a unique opportunity where fellows partner with leaders in government, bilateral organizations, foundations and nonprofits — ranging from Ministers, CEOs and District Collectors — to implement a scalable data intelligence solution. The Fellowship seeks to bring together young, enterprising future leaders with experienced leaders in the development sphere to use the power of data to solve some of India's most critical problems.
For more details about the Fellowship and to get started on your application, visit http://soco.ps/2BHK6Ba!
Data Is The New Oil: How Shell Has Become A Data-Driven And AI-Enabled Business Bernard Marr
Today, every organization must become a more data-driven business. While most understand that this is important, they might not know how to do it. Here we share insights and learning from energy-giant Shell on how to prioritize data-driven operations.
Data Science, Analytics and AI: Gamechangers for the Future of WorkSharala Axryd
The Center of Applied Data Science (CADS) was established in 2014 in Malaysia and expanded to Singapore in 2018. CADS aims to establish a global standard in data science and analytics education. It has produced over 1,000 data professionals and advised both government and corporate clients through its BOLT methodology of building capabilities, operating solutions, learning skills, and transferring knowledge. Data science and analytics roles such as data scientists, data analysts, and data engineers are in high demand with increasing salaries and opportunities for career advancement.
This document summarizes an upcoming two-day workshop on big data and government analytics to be held in Ottawa on March 24-25, 2015. The workshop will cover topics such as leveraging big data to improve government services, maximizing data sharing across departments, incorporating big data into overall data strategies, using big data for security purposes, and making data-driven decisions. It lists the workshop leaders and participating organizations, and provides an overview of the scheduled sessions and speakers.
The document discusses establishing a centralized data infrastructure in India to harness government data for public benefit. It proposes integrating distinct sets of government data, following models of other open data initiatives. A centralized architecture would provide authenticated data and documents to improve targeting of welfare programs while granting selected access to the private sector to spur innovation. Citizens would greatly benefit from consolidated access to relevant data to solve problems and harness data for their own benefit. The goal is to establish data as a public good generated and used for the people.
BRIDGING DATA SILOS USING BIG DATA INTEGRATIONijmnct
1) The document discusses how big data integration can be used to bridge data silos that exist in many enterprises due to different business applications generating structured, semi-structured, and unstructured data. 2) It explains that traditional data integration techniques are not well-suited for big data due to issues with scale and handling semi-structured and unstructured data. 3) Big data integration techniques like Hadoop, Spark, Kafka and data lakes can be better suited for integrating large heterogeneous data sources in real-time or in batches at scale.
This document discusses new ways of handling old data and unlocking value from unstructured content through cognitive systems. It provides predictions for big data and analytics spending and adoption through 2020. Key points include:
- 90% of digital information is unstructured content stored in separate repositories that don't communicate.
- By 2020, 50% of business analytics software will incorporate prescriptive analytics using cognitive computing.
- Organizations that can analyze all relevant data and provide actionable insights will gain $430 billion in productivity over less analytical peers.
- Cognitive software can support better decision-making by applying broader evidence without bias to situations.
- The cognitive software market is expected to grow rapidly over the next five
Hagar & Associates aims to connect cities through big data to improve services like transportation, water, power, and emergency response. They partnered with IBM to use Watson for data analysis. A student group recommends ways for Hagar & Associates to take interns from California State University, San Bernardino, including paperwork required. The document also provides a cyber security plan and recommendations to protect data in their system and cloud, including access controls, passwords, firewalls, and physical security of servers.
Data2030 Summit Data Megatrends Turner Sept 2022.pptxMatt Turner
The next challenge in data is rapidly becoming clear: how can we scale data value and bring data driven decision making to everyone? We’ve made tremendous progress in bringing data together. The megatrends in data - data mesh, data fabric, modern data stack - are all about crossing the last mile to get data to everyone, not just the data experts. How can we empower everyone to better use data? Are the megatrends the road to actually scaling data value? And what does that mean for the data teams and data engineers creating systems and delivering dataops?
Hadoop and Big Data Readiness in Africa: A Case of Tanzaniaijsrd.com
Big data has been referred to as a forefront pillar of any modern analytics application. Together with Hadoop which is open source software, they have emerged to be a solution to the processing of massive generated both structured and unstructured data. With different strategies and initiatives taken by governments and private institutions in the world towards deployment and support of big data analytics and hadoop, Africa cannot be left isolated. In this paper, we assessed the readiness of Africa with a case study of Tanzania in harnessing the power of big data analytics and hadoop as a tool for drawing insights that might help them make crucial decisions. We used a survey in collecting the data using questionnaires. Results reveal that majority of the companies are either not aware of the technologies or still in their infancy stages in using big data analytics and hadoop. We identified that most companies are in either awakening or advancing stages of the big data continuum. This is attributed by challenges such as lack of IT skills to manage big data projects, cost of technology infrastructure, making decision on which data are relevant, lack of skills to analyze the data, lack of business support and deciding on what technology is best compared to others. It has also been found out that most of the companies' IT officers are not aware with the concepts and techniques of big data analytics and hadoop.
Big Data in Malaysia: Emerging Sector Profile 2014Tirath Ramdas
Big Data has become part of everyday organisational parlance. Increasingly, this awareness is being transformed into practice. Support for harnessing data to amplify capabilities and achieve organisational objectives at practitioner and senior management levels is becoming aligned. A report by Forrester on Big Data adoption in Asia Pacific in 2013-2014 observed a trend across all industries of ‘using more types of data, from more sources, to enable timelier better-informed insights’. Similarly in Malaysia, there is growing cultural acceptance that Big Data can and should enhance decision-making processes, although pathways for adoption are not uniformly understood. Nevertheless, we are now observing a transition phase from curiosity and enthusiasm to buy-in and action across startup, corporate, and government organisations. This groundswell of interest fuels the basis of Big Data Malaysia, a networking group for professionals with interest in all things Big Data, including NoSQL, Hadoop, data science, visualisation, business use cases, data governance, open data, and more. Our community has welcomed participation from stakeholders ranging from computer scientists to data journalists, reflecting a broad societal interest in Big Data. Our mission is to encourage high caliber knowledge sharing and to provide a space for professionals with different interests to collaborate. This report grew out of a need to understand in more detail the various networks that Big Data Malaysia helps to connect. In order to support the Big Data ecosystem that we see emerging, we identified critical questions that required further investigation, in particular:
• What are the opportunities and barriers to Big Data activity in Malaysia?
• Who is merely ‘interested’, versus who is actually committed?
• What is the current and future capacity for Big Data talent?
• Where are the critical gaps in training and skills?
• What are the soft inhibitors, including data access, regulation and perception?
There are two parts to this report. The first includes results from a questionnaire, while the latter features interviews conducted in-person or via email. In collaboration with various partners, we devised and distributed a questionnaire online across our networks and collected responses during October 2013. In our final sample, we collected responses from 108 individuals over 90 organisations. As our report will show, these viewpoints represent a diversity of organisational stakeholders and industries in the Big Data space. We followed up with interviews of high-profile respondents for richer insight.
KM SHOWCASE 2020 - "Implementing Knowledge-as-a-Service through the Digital W...KM Institute
The document discusses implementing Knowledge-as-a-Service (KaaS) through a digital workplace. KaaS blends knowledge management and AI to deliver the right knowledge to users. It discusses using AI for predictive analytics, knowledge mapping and chatbots. A case study describes implementing a KaaS framework and digital workplace at the IMF to improve knowledge sharing, collaboration and process efficiency across devices. Key challenges included integrating tools and developing an extensible information architecture to enable search and machine learning.
This document discusses the growth of data and analytics capabilities. It notes that data storage capacity is growing at 23% annually while computing capacity is growing at 54% annually. Lower barriers to connectivity are integrating different sources of data. The document discusses how Right Brain Systems uses analytics to build smarter organizations by focusing on data foundation, information design, analytics capabilities, operational framework, and business ownership. It provides examples of how different types of analytics can be applied to key areas like customers, operations, finance, and workforce.
Big data refers to large and complex data sets that are difficult to process using traditional methods. The Center of Applied Data Science (CADS) was founded to address the need for data science talent in Malaysia by training the next generation of data professionals. CADS partners with leading organizations like the Data Incubator, Harvard Business School, and Coursera to provide rigorous data science education programs. The goal is to cultivate data talent and empower individuals and organizations to leverage big data for competitive advantage.
The Future of Work is Here: Are You Prepared?Sharala Axryd
The document discusses how technology is changing the nature of work and the future workforce. Automation and AI will significantly impact jobs over the coming decades, with some jobs being replaced while new jobs are created. To stay relevant, professionals need to continually learn new skills. The future workforce will require skills in problem solving, critical thinking, and emotional intelligence rather than just technical skills. While AI will replace some jobs, it will also create new types of jobs. Malaysia needs to take advantage of new technologies like AI, IoT, and big data to increase productivity and improve livelihoods. However, it has not fully reached Industry Revolution 3.0 yet. Women and underrepresented groups also remain an untapped resource, and empowering them
1) The document discusses how 5 out of 10 future jobs have yet to be created due to technological innovation and the need for professionals to be agile and adopt new solutions.
2) By 2050, industries like banking and manufacturing will integrate automation and robotics according to economists, showing how digital disruption has already occurred.
3) Jobs that did not exist 10 years ago like data scientists, online community managers, and drone operators are highlighted to demonstrate how new roles are emerging while traditional jobs in areas like healthcare, education and law are threatened by advances in big data and machine learning.
Jumpstart a Lucrative Career in Data ScienceSharala Axryd
The Center of Applied Data Science (CADS) aims to make the world more sustainable through technology, data insights, and intelligence. CADS educates clients on data management, integration, and analysis to empower them and promote independence. As the first comprehensive data science training institution in ASEAN, CADS integrates learning, networking, and professional growth to train effective data scientists and cultivate the next generation of data professionals. There is high demand for data scientists as 90% of data in the last 2 years remains unused, with the potential value from data exceeding $300 billion annually. However, many countries in ASEAN still face gender gaps that CADS hopes to help address through education and training.
The Future Agenda: Digitising Democracy and the Fake News SagaSharala Axryd
The document discusses digitizing democracy and fake news. It provides an overview of The Center of Applied Data Science (CADS), which aims to empower clients through data education. It then discusses definitions of fake news and Malaysia's Anti-Fake News Act of 2018. Several countries around the world have also implemented or discussed laws against fake news. To combat misinformation, the root causes of its proliferation must be addressed. Connecting with alternative sources of information online can spread misinformation, so mainstream media should not be suppressed.
Digital Business Today: Where is it heading?Sharala Axryd
This document discusses trends in digital business and data science, including the future of technologies like edge computing, artificial intelligence, and the Internet of Things. It outlines eight categories of data scientists and notes that data visualization and chief data officer will be important roles. The new chief data officer will need skills in vision, managing multidisciplinary teams, multiple communication forms, computational thinking, and innovation. The Center of Applied Data Science provides certification in these areas.
This document discusses careers in data science and provides information about data science roles. It summarizes that data scientists apply expertise to make predictions and answer business questions, data engineers build and optimize systems for data analysis, and data analysts deliver value by analyzing data and communicating results. It also discusses how big data can be used to cure disease, prevent crime, and explore planets, and emphasizes that digital disruption has already occurred.
Those Who Rule The Data, Rule The WorldSharala Axryd
Though 85% of global companies are trying to be data-driven, only 37% of that number say they’ve been successful.
In this Information Generation, leaders are being pressed to rewrite the rules for how they organize, develop, manage, and engage their 21st-century businesses. More precious than oil or gold, data can prove to be the crucial x-factor between gaining a competitive edge and facing extinction.
Success at Work through the Power of Analytical ThinkingSharala Axryd
The document is a presentation about success at work through analytical thinking presented by Sharala Axryd of The Center of Applied Data Science (CADS). CADS aims to make the world more sustainable through technology, insights, and intelligence. They educate clients on data management, integration, and analysis to empower clients and enable their independence from CADS services. The presentation discusses crucial 21st century skills like analytical thinking, creativity, and communication skills. It also notes that training for soft skills is the top priority for talent development and discusses how digital technologies can transform industries like oil and gas.
Rethinking Employment in an Automated EconomySharala Axryd
The document discusses how technology is automating many jobs and changing the nature of work. It suggests that while automation may eliminate some occupations, it will change most jobs by automating certain tasks. Companies need to rethink which job roles and skills are best suited for humans versus machines. To prepare for these changes, workers will need to learn new skills through retraining. The role of HR is also evolving to help companies with digital transformation, talent acquisition, performance management, diversity and strategic planning. Mastering skills like adaptability, learning new technologies, and communicating value will help individuals succeed in the changing job market.
Empowerment of Women through STEM Education in MalaysiaSharala Axryd
This document discusses empowering women through STEM education in Malaysia. It notes that STEM achievement gaps emerge as early as kindergarten for girls due to lack of role models, peer influence, and gender stereotypes. Early introduction of STEM skills and a growth mindset are important to develop meaningful learning for both boys and girls. Promoting women in STEM fields can unlock significant economic potential for Malaysia by addressing the underrepresentation of women. Mentors and role models and challenging gender stereotypes are keys to engaging more girls and women in STEM careers.
This document discusses the importance of using storytelling techniques when presenting data insights to others. It notes that people are more likely to remember stories than statistics, and stories are more persuasive than statistics alone. Effective data storytelling involves structuring the narrative through chronological or reverse-chronological ordering, depending on the audience. It is important to provide full context and avoid misleading visualizations when telling data stories. Data stories should question assumptions and avoid making claims not supported by the data.
Achieving greater heights at work through the power of data and analytical th...Sharala Axryd
The document discusses the importance of women embracing data and digitalization. It notes that including women in technology conversations brings valuable perspectives to drive innovation. It also notes that many future jobs will require new skills, so retraining will be important. Women who perform technology-related tasks receive higher pay increases. However, there is a lack of female role models in technology fields. When women are left out of decision making processes, products can fail to consider women's needs. Embracing data and digital skills will help women adapt to changing skills needs and have more career opportunities.
A presentation on mastering key management concepts across projects, products, programs, and portfolios. Whether you're an aspiring manager or looking to enhance your skills, this session will provide you with the knowledge and tools to succeed in various management roles. Learn about the distinct lifecycles, methodologies, and essential skillsets needed to thrive in today's dynamic business environment.
12 steps to transform your organization into the agile org you deservePierre E. NEIS
During an organizational transformation, the shift is from the previous state to an improved one. In the realm of agility, I emphasize the significance of identifying polarities. This approach helps establish a clear understanding of your objectives. I have outlined 12 incremental actions to delineate your organizational strategy.
Designing and Sustaining Large-Scale Value-Centered Agile Ecosystems (powered...Alexey Krivitsky
Is Agile dead? It depends on what you mean by 'Agile'. If you mean that the organizations are not getting the promised benefits because they were focusing too much on the team-level agile "ways of working" instead of systemic global improvements -- then we are in agreement. It is a misunderstanding of Agility that led us down a dead-end. At Org Topologies, we see bright sparks -- the signs of the 'second wave of Agile' as we call it. The emphasis is shifting towards both in-team and inter-team collaboration. Away from false dichotomies. Both: team autonomy and shared broad product ownership are required to sustain true result-oriented organizational agility. Org Topologies is a package offering a visual language plus thinking tools required to communicate org development direction and can be used to help design and then sustain org change aiming at higher organizational archetypes.
Impact of Effective Performance Appraisal Systems on Employee Motivation and ...Dr. Nazrul Islam
Healthy economic development requires properly managing the banking industry of any
country. Along with state-owned banks, private banks play a critical role in the country's economy.
Managers in all types of banks now confront the same challenge: how to get the utmost output from
their employees. Therefore, Performance appraisal appears to be inevitable since it set the
standard for comparing actual performance to established objectives and recommending practical
solutions that help the organization achieve sustainable growth. Therefore, the purpose of this
research is to determine the effect of performance appraisal on employee motivation and retention.
A team is a group of individuals, all working together for a common purpose. This Ppt derives a detail information on team building process and ats type with effective example by Tuckmans Model. it also describes about team issues and effective team work. Unclear Roles and Responsibilities of teams as well as individuals.
Originally presented at XP2024 Bolzano
While agile has entered the post-mainstream age, possibly losing its mojo along the way, the rise of remote working is dealing a more severe blow than its industrialization.
In this talk we'll have a look to the cumulative effect of the constraints of a remote working environment and of the common countermeasures.
Ganpati Kumar Choudhary Indian Ethos PPT.pptx, The Dilemma of Green Energy Corporation
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Source: Data gathered from MCMC (Malaysian Communications and Multimedia Commission), Facebook, Department of Statistics Malaysia, etc.
https://www.skmm.gov.my/skmmgovmy/media/General/pdf/Internet-Users-Survey-2018.pdf
Internet
With so much information at our fingertips, we’re adding to the data stockpile every time we turn to our search engines for answers.
We conduct more than half of our web searches from a mobile phone now.
More than 3.7 billion humans use the internet (that’s a growth rate of 7.5 percent over 2016).
On average, Google now processes more than 40,000 searches EVERY second (3.5 billion searches per day)!
While 77% of searches are conducted on Google, it would be remiss not to remember other search engines are also contributing to our daily data generation. Worldwide there are 5 billion searches a day.
Innovation happens fast and slowly. The GPS applications so prevalent today to guide us from Point A to Point B took their first baby steps nearly three decades ago when President Ronald Reagan encouraged the release of military GPS signals free of charge. Will a key initiative of President Barack Obama-to move government data to the Web-lead to public benefits much faster?
Data.gov, the subject of a new HBS case study, taught for the first time this summer, highlights the potential of raw data to spur citizen creativity and practical applications. It also suggests the possibility that organizations in private industry could learn from the example of Data.gov to the extent of unlocking data from individual silos in their firm even though data remain protected within firewalls. HBS assistant professor Karim R. Lakhani, who specializes in the management of technological innovation and product development in firms and communities, co-wrote the case with former HBS professor Robert D. Austin and Yumi Yi to encourage further exploration of the benefits and tactics of open-data approaches.
“ ALL AGENCIES WILL HAVE ISSUES, OF COURSE, ABOUT MAKING DATA AVAILABLE, BECAUSE HISTORICALLY THEY MAY HAVE NOT”
Joined in class by the Chief Information Office (CIO) of the United States, Vivek Kundra, who oversees Data.gov, Lakhani led the case discussion for 50 technology executives in a weeklong HBS executive education course, Delivering Information Services. The participants-CTOs, CIOs, and other top executives representing fields as diverse as telecommunications, financial services, and pharmaceuticals, as well as government entities in the US and overseas-debated the pluses and minuses of Data.gov's decisions, its organizational realities in the context of their own experience, and tactics to improve its reach and impact. Kundra joined the conversation near the end of class to answer questions and share insights.
"There is tremendous interest internationally" in the example of Data.gov, said Lakhani. When the initiative was less than a year old it had already posted 118,000 datasets for public use. "I cowrote the case in part to provide a field guide to suggest how to encourage data openness within organizations and even countries. Some countries, I think, would be better at it: Canada, Scandinavian countries, for instance, and Western democracies generally."
Goals Of The Case Study
"I have several teaching goals," said Lakhani as he prepared for class. "One is to highlight the imperative for organizations to shift towards an open-data approach, especially in government where the default has been to keep data closed and secure.
"Second, to explore the organizational constraints and resistance to an open-data approach. All agencies will have issues, of course, about making data available, because historically they may have not.
"Third, to probe issues of strategy concerning the best way to launch a similar initiative, both in terms of technology as well as the buy-in needed from various agencies.
"Fourth, to ask executive participants in my class how Data.gov should reconcile both its public-citizen aspects of accountability and its potential to mediate private innovation.”
Success for CIO Kundra is two-fold, Lakhani added. It means fulfilling the public mission of an informed citizenry as well as also the private mission of enabling innovation. In terms of building government IT infrastructure, Data.gov demonstrates a way to be rapid and agile, not bloated and bureaucratic.
"Kundra wants to post on the site any government data that does not have national security or privacy concerns. That's a lot of data. Anything that can be put online should be put online."
Pros And Cons
In class, participants who had read the case pointed to a wealth of positive factors about Data.gov:
Transparency: Its official motive of transparency allows citizens more control of information that affects them. Giving "power to the people" puts a new set of eyes and ears on government and holds officials more accountable.
Business opportunities: Data.gov opens the door for the private sector to add value to government data. In particular, it may prove a boon to small businesses, which can devise creative applications.
Organizational agility: As a lean organization with minimal staff, Data.gov made the right move by posting, as a first step, varieties of data from the US Census Bureau, the Centers for Disease Control, the Environmental Protection Agency, and the Department of Interior, without focusing on specific "customer" needs. One executive observed, "What customers do is up to the customers.”
Changing the face of government: Its example could improve the culture of government. "Getting agencies into the habit of making data available is a good first step," said a CTO in the class. Other agencies want to look good, too. There is pressure on officials to not get left behind.
A go-to site for citizens: It centralizes datasets for citizen use. It may cut down on the volume of requests that local agencies need to field on a day-to-day basis.
Participants also probed questions of concern:
Political window dressing: Will Data.gov release controversial datasets or will it favor uncontroversial information such as health statistics over military casualties? If it releases what is construed by the public as sanitized data, will citizens view the site cynically?
Customer needs: As business people, some class participants wanted to see a clearly outlined customer perspective defining customer needs.
Tradeoffs for fast growth: Several participants wondered what the endeavor interrupted in local agencies as it began to fulfill its mandate of gathering data. "I don't believe there were no ripple effects," said one executive.
Public trust and consistency of data architecture: Does government data match across various agencies? Will inconsistencies raise doubts among the public about data veracity overall?
As instructor, Lakhani challenged the executive participants to consider Data.gov as a lean organization needing to fulfill quickly President Obama's mandate without excessive discussion of pros and cons. They would experience similar pressure from an executive directive in any industry, he said. "We have to face tradeoffs when we design and execute. There are different ways to approach the same problem," he said.
Several participants in the class agreed. Said one, who works for a government agency, "I can attest that when huge initiatives come along, whatever 'seems impossible' soon becomes a fact of life. To say, 'I need to do a study first' is not a [wise] response.”
Advice For The Us Cio
Asked by Lakhani how Data.gov should grow strategically, executive participants suggested that while transparency of government data overall was an important goal in principle, Data.gov should prioritize its acquisition efforts and pursue specific high-value targets. One CTO recommended giving priority to environmental data in order to encourage the public to invent ways to help clean up the disastrous effects of the recent oil spill in the Gulf of Mexico.
Another class participant pointed to an example of high-value data use documented in the Data.gov case study: In Virginia where there were problems with a bidding process, citizens were able to learn where exactly money was being wasted, and take action to stem the tide.
A third said that Data.gov should focus less attention on data acquisition than on encouraging private industry to develop applications. "Brand them as 'powered by Data.gov.' The end user, rather than the average citizen, should be a key focus of your strategy," he advised.
These views were challenged by one participant, however. For the sake of public trust, he said, Data.gov should focus on transparency rather than commit too much organizational attention to the development of applications. "A problem we face in the United States today is a lack of trust in government officials," he explained. "There is no point in adding services over a foundation we don't trust. The number-one priority of Data.gov should be to restore confidence in our government. The average person should be able to interpret these data.”
The Us Cio Weighs In
"This discussion has been about binary choices," observed Kundra with a smile as he rose to address the class. "I would like to step back a bit and share with you some of the motivations behind Data.gov."
Information is power, he began. By "democratizing data," ordinary citizens have the ability to shift the balance of power in positive ways that can encourage innovative ideas to be developed into practical goods and services. "Washington, DC does not have a monopoly on the best ideas," he told the executives. "The public has the ability to innovate.”
Data.gov allows people to be watchdogs as well as innovators, he continued. One helpful innovation marries government data about recalls of baby products with the nifty Red Laser app that is available for the iPhone: Before considering purchase of something for their child, parents with the app can scan the bar code of any product and immediately check for recalls, thus ensuring the safety of their children.
Releasing government data and allowing the public to innovate creates a process of continuous feedback, he said. People can see how the government spends taxpayer money. "Our goal is to create a runway, a platform for innovation. The government can't make the most innovative apps. But Data.gov can be a platform.”
“OUR GOAL IS TO CREATE A RUNWAY, A PLATFORM FOR INNOVATION”
Transparency of information leads by necessity to controversy, Kundra allowed. People are bound to ask which data is on the site and which is not. "We release data on toxicity, but not on national security and privacy. It would be a mistake, for instance, to release zip-code level data about health care" because the privacy of individuals would be at stake, he said. Data.gov is seeking even more raw data from US agencies such as the Department of Defense, Health and Human Services, and the Environmental Protection Agency, but his organization does not expect to gain controversial datasets.
Rather than focusing unduly on issues of data governance, the executive participants should think about innovation opportunities in data curation, he suggested. "Some US government data is still on COBOL-based platforms," Kundra reminded the class. "So we think an industry will form around data curation. The Internal Revenue Service, the Centers of Disease Control, and the National Institutes of Health are huge enterprises. There will not be a single governance model.”
What Can Private Industry Learn From Government?
Data.gov serves as a beacon for changing the IT culture in Washington, DC to focus more attention on execution, he said. As CIO of the United States, his role from President Obama is to identify troubled projects, hold CIOs accountable (there are 200 CIOs across various government agencies, he said) and practice relentless follow-up. Gone are the days of deliverables scheduled five to ten years from now, Kundra promised. "A deliverable that is customer-facing should be ready within 6 months. On Data.gov we put up our IT Dashboard, an interactive site that tracks Federal IT investments over time, in 60 days.”
A key aspect of the Data.gov case is the extent to which innovation can be encouraged within individual organizations by pursuing a similar model of openness of data, added Lakhani. Just as there are benefits for the public when data is unleashed, so are there benefits for innovation-minded employees in private enterprise when data that was formerly held within silos is made available throughout the organization.
"CIOs and CEOs could consider what data they should make available throughout their enterprise," Lakhani said. "It would be great if any employee could look at data and think about different ways to mash it up. Just as there are concerns about security and privacy with the government's data, there are security, privacy, and intellectual property concerns about private-sector data. But Data.gov shows that those things are manageable."
How do countries’ strategies compare? And what are the implications for the world? I have selected six countries with very different approaches which will have a significant impact outside their national boundaries.
US
Distinctive characteristic Defend the lead; private sector the envy of the world
State role Largely silent Highlights
Clear lead in AI in terms of leading-edge research, advanced algorithms, specialised computing hardware, fast-growing inventory of data and talent. Tech giants such as Google, Amazon, Facebook and Apple are investing billions in AI R&D.
No central AI policy, but government agencies such as the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Advanced Research Projects Activity (IARPA) are funding AI projects. DARPA, which is responsible for the development of emerging technologies, recently announced an investment of $2 billion (£1.52 billion) to build the next-gen AI. But the bridges that the Defense Department has tried to build with Silicon Valley have come under pressure due to the employee protests from companies such as Google and Microsoft.
Recent government policies are seen as putting a dampener on the growth of the AI industry. Tightening of the immigration rules is starving Silicon Valley of much needed talent.
Statements from a one-page fact sheet released by the White House and the speech by Michael Kratsios, Deputy Assistant to the President for technology policy, that set the tone for the national strategy:
America has been the global leader in AI and the Trump administration will ensure “our great nation” remains in that position.
President Trump has taken executive action to give US workers the skills to succeed in the 21st-century economy.
China
China announced its ambition to lead the world in AI theories, technologies, and applications in its July 2017 plan, A Next Generation Artificial Intelligence Development Plan. The plan is the most comprehensive of all national AI strategies, with initiatives and goals for R&D, industrialization, talent development, education and skills acquisition, standard setting and regulations, ethical norms, and security. It is best understood as a three step plan: first, make China’s AI industry “in-line” with competitors by 2020; second, reach “world-leading” in some AI fields by 2025; and third, become the “primary” center for AI innovation by 2030. By 2030, the government aims to cultivate an AI industry worth 1 trillion RMB, with related industries worth 10 trillion RMB. The plan also lays out the government’s intention to recruit the world’s best AI talent, strengthen the training of the domestic AI labour force, and lead the world in laws, regulations, and ethical norms that promote the development of AI. The latter includes the intent to actively participate in and lead the global governance of AI.
Since the release of the Next Generation Plan, the government has published the Three-Year Action Plan to Promote the Development of New-Generation Artificial Intelligence Industry. This plan builds on the first step of the Next Generation plan to bring China’s AI industry in-line with competitors by 2020. Specifically, it advances four major tasks: (1) focus on developing intelligent and networked products such as vehicles, service robots, and identification systems, (2) emphasize the development AI’s support system, including intelligent sensors and neural network chips, (3) encourage the development of intelligent manufacturing, and (4) improve the environment for the development of AI by investing in industry training resources, standard testing, and cybersecurity. In addition, the government has also partnered with national tech companies to develop research and industrial leadership in specific fields of AI and will build a $2.1 billion technology park for AI research in Beijing.
Russia
President Putin’s assertion that “whoever becomes the leader in this sphere will become the ruler of the world” is frequently used by observers as evidence of a global AI arms race. But Putin’s statement is often quoted without context and, as a result, vastly overstates Russia’s AI capabilities. Speaking to students during a national “open lesson” on the first day of the school year in September 2017, Putin was asked a question about AI. He responded with the above quote, but also stated that “it would not be very desirable that this monopoly be concentrated in someone’s specific hands. That’s why, if we become leaders in this area, we will share this know-how with the entire world.” Putting aside whether or not Russia would actually share its AI technology with the world, this part of the quote is a crucial omission of Russia’s AI capabilities. “If we become leaders in this area” confirms that Russia is far from being a leader in the global AI race and is instead hustling to catch up. As Samuel Bendett reports for Defense One, “Russia’s annual domestic investment in AI is probably around 700 million rubles ($12.5 million) — a paltry sum next to the billions being spent by American and Chinese companies.”
In March 2018, Russia’s Ministry of Defence, the Ministry of Education and Science, and the Russian Academy of Sciences hosted a conference titled, “Artificial Intelligence: Problems and Solutions — 2018.” As a result of the conference, the Ministry of Defence released a list of 10 policies that the conference recommended. While the list is not an official strategy for the Russian government, it does lay the foundation for a national AI strategy. Key recommendations include creating a state system for AI education and talent retainment, establishing a national center for AI, and hosting war games to study the impact of AI on military operations.
Two Possible Futures
Data is the commodity of this century and the way we use it will shape how we live our lives in the future. Politicians are slowly coming to understand the importance of mastering the use of data to address the challenges society faces. At the same time, tech companies are developing tools and services to understand the needs and interests of citizens in a more precise way than governments will ever be able to, with many of these products already being implemented in cooperation with governments around the world.
The increasing dependence on algorithms and machines in decision-making raises questions of legitimacy. Automating decisions based on big amounts of data makes it difficult to hold governments to account as algorithms get more sophisticated and people who designed the rationale behind them are less capable of understanding them. Assuming that automated data will be an inherent part of governments and their interactions with the society, two possible futures can be imagined.
The increasing dependence on algorithms and machines in decision-making raises questions of legitimacy. On the positive spectrum, data can help optimise resources, increase transparency, foster learning and optimise individual choices. On the negative side, data can be used for social control, to reinforce biases, misinform, or make government actions less accountable.
Data usage has the potential to dramatically change life as we know it. The way we overcome the challenges and exploit the opportunities it brings will guide the future we will build. If basic standards of privacy and accountability are in place, data can help improve the relationship between governments and their citizens. However, governments alone cannot address these challenges only by using regulation: tech companies need to take action to build a healthier online environment as well.
How to Move Towards the Good Version of a Data-Driven Future
In order to explore the positive outcomes of data usage, governments, private companies, and civil society need to think outside of the box, not only offering regulation as a solution, but a multi-stakeholder approach to this question.
With significant job cuts expected in the wake of automation, governments need to think about offering a mix of training and social security policies to facilitate the transition of workers in the labour market in the short run. In the long term, educational systems and redistributive policies need to align with the effects of these trends, if we want to avoid profits from technological development going only to those at the top.
But government does have an important role to play. Data protection laws should dictate the rules of what can and what cannot be done. Without comprehensive protection of citizens’ personal data and ways to verify and make those who develop machine learning applications accountable, it will be difficult to ensure that we explore the full potential of innovation without avoiding its risks.
If a democratic government neglects its duty to regulate data usage, it may find its power short-lived. The idea of a machine automating decisions that should be in the hands of public authorities challenges the social contract that exists between voters and elected officials. This issue should be on the public agenda if politicians want to avoid criticism about the lack of transparency and accountability that automation may bring. Governments should foster open-data and open-government initiatives in order to allow civil society to hold authorities accountable for their actions.
Both futures are possible, and we will likely live a world in which both of them coexist. The way we guide the use of technology in government and in civil society will determine whether we can take advantage of its benefits or live in fear of its consequences. We should not blame technology, but rather make it work for all of us.
What is the HiPPO Effect?
Avinash Kaushik was the first to coin the term HiPPO in his book Web Analytics: An Hour a Day. When a HiPPO is in the room and a difficult decision needs to be made but there’s not data or data analysis to determine the right course of action one way or another, the group will often defer to the judgement of the HiPPO. HiPPOs usually have the most experience and power in the room. Once their opinion is out, voices of dissent are usually shut out and in some cases, based on the culture, others fear speaking out against the HiPPO’s direction even if they disagree with it.
When Ron Johnson, former head of retail at Apple who was responsible for the highly profitable Apple Stores, took over as CEO at J.C. Penney, he suffered from the HiPPO Effect. Without reviewing the existing data or investing in new data about the very different retail store he was now leading, he went full throttle ahead on his strategy for the department store chain. When his strategy was launched and he checked in to see if it was working, few had the courage to give him the unvarnished truth and be labeled as a resistor. Needless to say, his strategy wasn’t succeeding with J.C. Penney’s customers.
https://finance.yahoo.com/news/jc-penneys-controversial-former-ceo-is-unsure-if-the-retailer-will-be-around-in-5-years-145259863.html
The Harvard Business Review found that while 80 percent of survey respondents rely on data in their roles and 73 percent rely on data to make decisions, 84 percent still said managerial judgment is a factor when making key decisions.
If you are the HiPPO, follow the example of Alfred Sloan, long-term president, chairman and CEO of General Motors who “had a strong belief about making decisions; they shouldn’t be made until someone had expressed why the ‘preferred’ option might not be the right one.” Invite disagreement; make yours a culture that you seek multiple opinions and even ask someone to play devil’s advocate prior to an important decision being made.
A college degree at the start of a working career does not answer the need for the continuous acquisition of new skills, especially as career spans are lengthening. Vocational training is good at giving people job-specific skills, but those, too, will need to be updated over and over again during a career lasting decades. – The Economist
Fortunately it doesn’t take much time or money to boost your skills to make you more competitive. You just need to have a strategy for ensuring that your knowledge and skills are always up-to-date. Even if you aren’t in a technical job, technical skills like software and social media help everyone. Creative skills like graphic design and photography are also useful in a variety of jobs. Skills like project management, team leadership, and conflict resolution are critical to anyone’s success. In short, knowledge work is an area that will continue to grow; career options will become more varied and require ongoing education to remaining current.
2nd last slide. Final slide will be the same as the 1st slide.