Analysis of new patterns of innovation by jyotsana manglaniJyotsanaManglani
The document discusses new patterns of innovation and their managerial relevance. It identifies 5 patterns for generating new business ideas using data: 1) augmenting products, 2) digitizing assets, 3) combining data within/across industries, 4) trading data, and 5) codifying services. Actual initiatives often use 2+ patterns. Managers should systematically examine these patterns to conceive solid new business ideas by exploring available data. They must structure idea generation but not expect constant creativity from employees. The patterns are relevant for Indian managers with large workforces.
The document discusses new patterns of innovation driven by data and digital tools. It outlines how (1) augmenting products to generate data, (2) digitizing assets, and (3) combining data within and across industries allows for innovative business models and services. The key is asking the right questions to iteratively innovate the best business models by collating and prioritizing ideas and investigating key assumptions. Managers must develop systematic plans to properly leverage large data sources and understand how technology enables innovative products, services, and business models.
BI / POWER BI - Key Concepts Business FeaturesSamer Fouad
This document provides an overview and agenda for a presentation on Power BI key concepts. It discusses:
1) What business intelligence is and how it helps businesses make better decisions by transforming data into meaningful information.
2) How Power BI allows users to get started quickly by creating interactive reports from spreadsheets using Power BI Desktop and publishing live dashboards and reports.
3) The presentation agenda which covers an introduction to Power BI, identifying business questions, working with datasets, data transformations, data warehousing, and demonstrations of the tools.
How to keep pace with changing technology and increase speed-to-value. In order to keep pace in a constantly evolving marketplace, organizations need a new model for sourcin IT services. Sourcing has become one of the most critical functions of the IT organization.
The document outlines 5 patterns of innovation: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying a distinctive service capability. It then provides examples for each pattern, such as using sensors on devices to collect user data or combining different datasets across fields. The document argues that these patterns allow for new business models and services. It also notes that companies often combine multiple innovation patterns in real-world initiatives.
Why You Should Incorporate AI in Business Applications - Vasant RamachandranVasant Ramachandran
Vasant Ramachandran discusses why you should incorporate AI in business applications in this in-depth presentational blog. For more information, please visit VasantRamachandran.com!
Analysis of new patterns of innovation by jyotsana manglaniJyotsanaManglani
The document discusses new patterns of innovation and their managerial relevance. It identifies 5 patterns for generating new business ideas using data: 1) augmenting products, 2) digitizing assets, 3) combining data within/across industries, 4) trading data, and 5) codifying services. Actual initiatives often use 2+ patterns. Managers should systematically examine these patterns to conceive solid new business ideas by exploring available data. They must structure idea generation but not expect constant creativity from employees. The patterns are relevant for Indian managers with large workforces.
The document discusses new patterns of innovation driven by data and digital tools. It outlines how (1) augmenting products to generate data, (2) digitizing assets, and (3) combining data within and across industries allows for innovative business models and services. The key is asking the right questions to iteratively innovate the best business models by collating and prioritizing ideas and investigating key assumptions. Managers must develop systematic plans to properly leverage large data sources and understand how technology enables innovative products, services, and business models.
BI / POWER BI - Key Concepts Business FeaturesSamer Fouad
This document provides an overview and agenda for a presentation on Power BI key concepts. It discusses:
1) What business intelligence is and how it helps businesses make better decisions by transforming data into meaningful information.
2) How Power BI allows users to get started quickly by creating interactive reports from spreadsheets using Power BI Desktop and publishing live dashboards and reports.
3) The presentation agenda which covers an introduction to Power BI, identifying business questions, working with datasets, data transformations, data warehousing, and demonstrations of the tools.
How to keep pace with changing technology and increase speed-to-value. In order to keep pace in a constantly evolving marketplace, organizations need a new model for sourcin IT services. Sourcing has become one of the most critical functions of the IT organization.
The document outlines 5 patterns of innovation: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying a distinctive service capability. It then provides examples for each pattern, such as using sensors on devices to collect user data or combining different datasets across fields. The document argues that these patterns allow for new business models and services. It also notes that companies often combine multiple innovation patterns in real-world initiatives.
Why You Should Incorporate AI in Business Applications - Vasant RamachandranVasant Ramachandran
Vasant Ramachandran discusses why you should incorporate AI in business applications in this in-depth presentational blog. For more information, please visit VasantRamachandran.com!
In 2017, leading companies will roll out targeted search applications on a common platform to provide "search as a service" and increase employee productivity. While most organizations have Hadoop, very few can easily find, understand, and unify their data. The best performing companies will start by cataloging their data lakes to gain visibility and fuel agility. Forward-looking companies will recognize that modern, cognitive solutions rely on a global, semantic understanding of structured and unstructured information using machine learning, natural language processing, and text analytics on a single infrastructure.
This document discusses new patterns of innovation driven by information technology. It outlines five patterns that can help businesses determine if a new opportunity is relevant: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying distinctive service capabilities. Managers should understand the importance of IT in making businesses successful and take advantage of new opportunities opened up by advancing technology. The process for evaluating new opportunities involves asking questions, prioritizing ideas, further investigation, and detailing plans.
Primend Ärikonverents - Keynote: Surviving, Differentiating and Dominating on...Primend
Socrates once said “The secret of change is to focus all your energy, not on fighting the old, but on building the new”. Organizations throughout the world must think about the new digital world and evaluate how to get from where they are today to where they need to be in the future! In this presentation we will look into the changing landscape which is driving this 4th Industrial Revolution and present some areas you might like to focus on as you reposition your organization to compete in an increasingly digital world.
Esineja: Mark Torr (Microsoft)
Companies should pursue a simpler path to uncover insights from their data by creating a data supply chain using a hybrid of technologies. They should focus on next-gen business intelligence and data visualization to improve decision making, as well as data discovery techniques to uncover patterns. Machine learning can also be used to produce predictions and remove human elements from modeling. A company's analytics journey also depends on its culture.
The document outlines 5 new patterns of innovation that companies can use to create value: 1) Augmenting products to generate data, 2) Digitizing physical assets, 3) Combining data within and across industries, 4) Trading data, and 5) Codifying distinctive service capabilities. It provides examples of each pattern and notes that managers must be skilled in out-of-the-box thinking and supporting new ways of doing business to take advantage of these innovation opportunities using data and analytics.
"The New Patterns of Innovation" by Rashik Parmar, Ian Mackenzie, David Cohn ...Sachin Kumar Singh
This document discusses new patterns of innovation that are emerging due to advances in digital technology and data. It outlines five patterns that the authors have observed facilitating new business value creation: 1) Using data generated by physical objects to improve products/services or create new businesses, 2) Digitizing physical assets, 3) Combining data within and across industries, 4) Developing platforms to share content and get user feedback, and 5) Leveraging these patterns can help managers conceive new business ideas without needing cutting-edge technology. As more assets become digitized, competitive advantages may shift from physical to digital capabilities.
This document summarizes the services of a company that provides data analysis and machine learning solutions. They have an interdisciplinary team with over 15 years of experience in areas like machine learning, artificial intelligence, big data, and data engineering. Their expertise includes developing data models, analysis products, and systems to help companies with forecasting, decision making, and improving data operations efficiency. They can help clients across various industries like telecom, finance, retail, and more.
IBM Virtual Finance Forum 2016: Top 10 reasons to attendIBM Analytics
Explore the top 10 reasons to attend IBM's Virtual Finance Forum 2016 for insights and best practices on performance management in the cognitive era. Attend your choice of three broadcasts of IBM's Virtual Finance Forum 2016: http://bit.ly/oct5am, http://bit.ly/Oct512Noon or http://bit.ly/oct5eve.
10 Enterprise Analytics Trends to Watch in 2020MicroStrategy
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.
Information Builders is located in midtown Manhattan near major transportation hubs, providing an easy commute. The offices have panoramic views of iconic NYC landmarks. The company culture encourages work-life balance, believes all voices should be heard, and employees often form lifelong friendships as part of a collaborative work family. As a privately held company with a history of innovation in business intelligence, Information Builders is committed to long-term customer success.
Infocentric @ IntraNET Reloaded 2016 on "Effectiveness"Philipp Rosenthal
This document summarizes key points from a presentation on modern intranets and the digital workplace. It discusses how digital workplaces can improve employee satisfaction, effective communication and collaboration, and provide executives with stability. Specific topics covered include business process enablement, collaboration frameworks, best practices, continuous improvement, and the need for leadership, management, and individual responsibility to drive organizational change. The overall message is that digital workplaces can increase business effectiveness and efficiency if properly implemented and supported across all levels of an organization.
10 Enterprise Analytics Trends to Watch in 2019 MicroStrategy
View insights from Forrester analyst Mike Gualtieri, Constellation Research’s Ray Wang and Doug Henschen, Ventana Research’s Mark Smith and David Menninger, IDC’s Chandana Gopal, Marcus Borba, Ronald van Loon and other top analytics and business intelligence thought leaders.
The document discusses how IT sourcing must change to meet the demands of the "Ideas Age" economy. It notes that organizations now need to rapidly respond to changing customer needs. IT departments must be able to quickly source solutions or risk being replaced. The "Ideas Age" requires a focus on core competencies and interconnected functionality with customers. Leaders must source flexible, integrated systems using insourced, outsourced, and multi-sourced services. Cloud computing enables organizations to nimbly source innovative solutions. An "Information Services Sourcing Blueprint" can help organizations define, source, integrate, and deliver best-of-breed business and IT services to achieve outcomes.
The document discusses different perspectives on innovation and provides examples of patterns that companies can use to drive growth through data and new business models. It outlines five patterns: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying distinctive service capabilities. Each pattern is explained and real-world examples are provided to illustrate how companies have used these patterns to innovate, create new sources of value, and develop new business models. The document emphasizes that systematically tackling business innovation through these patterns can improve the odds of success.
The document highlights 5 new patterns of innovation for developing business ideas: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) insights from data. It discusses how these patterns can be used ingeniously for new business ideas by utilizing technologies like big data, data integration standards, and cloud computing. The key insights are to consider answers to probable questions within these 5 patterns and that relatively simple moves by existing businesses can help them grow into new large businesses.
The document discusses cognitive search and knowledge management. It notes that 53% of executives see knowledge management as important for innovation. Traditional knowledge management faces challenges around inefficiencies, integration, and consumerization of IT. The document promotes a cognitive, machine learning approach to knowledge management that can find answers, recommend content, and connect people through personalized delivery of information. Benefits include equipping a smarter workforce, tapping collective knowledge, and empowering continued insight. Case studies show how cognitive knowledge management helps Cisco, ThermoFisher, and National Instruments.
This presentation formed part of the Imperial 320 session that took place on Monday, 16 January.
Title of talk: New Patterns of Innovation, How to use Data to Drive Growth
In this presentation, Professor Gann will show how innovation is being transformed through the growth of data about customers, markets, cities and government. This is creating entrepreneurial opportunities to develop new products and services, stimulating new types of start-up business and social enterprise. It is disrupting and transforming the ways in which existing businesses and governments operate, intensifying competition and giving rise to new patterns of innovation.
Data-rich innovation is predicated on making information available for analysis. London provides examples of how this is generating new services and business models successful tech start-ups. Prof Gann’s recent Harvard Business Review article explains why five new patterns of innovation are leading to growth:
Pattern 1. Augmenting products to generate data
Pattern 2. Digitizing assets
Pattern 3. Combining data within and across industries
Pattern 4. Trading data
Pattern 5. Codifying a distinctive service capability
The challenge is to capture, frame, analyse and interpret data to create valuable insights. Success depends upon developing the talent of data scientists: data gatherers,
data modellers and data visionaries. It also requires the right conditions for entrepreneurship to flourish.
For more information, please visit: https://wwwf.imperial.ac.uk/business-school/imperial-business-insights-320/ #Imperial320
Various systematic patterns exist for creating new business value using data and analytics, beyond traditional "hits and misses". These include:
Pattern 1) Using big data to improve operations and explore new areas, like Rolls-Royce's engine health monitoring.
Pattern 2) Making assets mobile, measurable and flexible through digitization, like iTunes.
Pattern 3) Gaining broader access to data for new ventures through data combination across industries, like IBM's Bolzano smart city project.
Managers can apply these patterns by assessing their position, ambitions, and potential using available and creatable data from partners to innovate new business ideas and models in a systematic way beyond conventional approaches.
The search for new business ideas and new business models is hit-or-miss in most corporations, despite the extraordinary pressure on executives to grow their businesses.
In 2017, leading companies will roll out targeted search applications on a common platform to provide "search as a service" and increase employee productivity. While most organizations have Hadoop, very few can easily find, understand, and unify their data. The best performing companies will start by cataloging their data lakes to gain visibility and fuel agility. Forward-looking companies will recognize that modern, cognitive solutions rely on a global, semantic understanding of structured and unstructured information using machine learning, natural language processing, and text analytics on a single infrastructure.
This document discusses new patterns of innovation driven by information technology. It outlines five patterns that can help businesses determine if a new opportunity is relevant: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying distinctive service capabilities. Managers should understand the importance of IT in making businesses successful and take advantage of new opportunities opened up by advancing technology. The process for evaluating new opportunities involves asking questions, prioritizing ideas, further investigation, and detailing plans.
Primend Ärikonverents - Keynote: Surviving, Differentiating and Dominating on...Primend
Socrates once said “The secret of change is to focus all your energy, not on fighting the old, but on building the new”. Organizations throughout the world must think about the new digital world and evaluate how to get from where they are today to where they need to be in the future! In this presentation we will look into the changing landscape which is driving this 4th Industrial Revolution and present some areas you might like to focus on as you reposition your organization to compete in an increasingly digital world.
Esineja: Mark Torr (Microsoft)
Companies should pursue a simpler path to uncover insights from their data by creating a data supply chain using a hybrid of technologies. They should focus on next-gen business intelligence and data visualization to improve decision making, as well as data discovery techniques to uncover patterns. Machine learning can also be used to produce predictions and remove human elements from modeling. A company's analytics journey also depends on its culture.
The document outlines 5 new patterns of innovation that companies can use to create value: 1) Augmenting products to generate data, 2) Digitizing physical assets, 3) Combining data within and across industries, 4) Trading data, and 5) Codifying distinctive service capabilities. It provides examples of each pattern and notes that managers must be skilled in out-of-the-box thinking and supporting new ways of doing business to take advantage of these innovation opportunities using data and analytics.
"The New Patterns of Innovation" by Rashik Parmar, Ian Mackenzie, David Cohn ...Sachin Kumar Singh
This document discusses new patterns of innovation that are emerging due to advances in digital technology and data. It outlines five patterns that the authors have observed facilitating new business value creation: 1) Using data generated by physical objects to improve products/services or create new businesses, 2) Digitizing physical assets, 3) Combining data within and across industries, 4) Developing platforms to share content and get user feedback, and 5) Leveraging these patterns can help managers conceive new business ideas without needing cutting-edge technology. As more assets become digitized, competitive advantages may shift from physical to digital capabilities.
This document summarizes the services of a company that provides data analysis and machine learning solutions. They have an interdisciplinary team with over 15 years of experience in areas like machine learning, artificial intelligence, big data, and data engineering. Their expertise includes developing data models, analysis products, and systems to help companies with forecasting, decision making, and improving data operations efficiency. They can help clients across various industries like telecom, finance, retail, and more.
IBM Virtual Finance Forum 2016: Top 10 reasons to attendIBM Analytics
Explore the top 10 reasons to attend IBM's Virtual Finance Forum 2016 for insights and best practices on performance management in the cognitive era. Attend your choice of three broadcasts of IBM's Virtual Finance Forum 2016: http://bit.ly/oct5am, http://bit.ly/Oct512Noon or http://bit.ly/oct5eve.
10 Enterprise Analytics Trends to Watch in 2020MicroStrategy
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.
Information Builders is located in midtown Manhattan near major transportation hubs, providing an easy commute. The offices have panoramic views of iconic NYC landmarks. The company culture encourages work-life balance, believes all voices should be heard, and employees often form lifelong friendships as part of a collaborative work family. As a privately held company with a history of innovation in business intelligence, Information Builders is committed to long-term customer success.
Infocentric @ IntraNET Reloaded 2016 on "Effectiveness"Philipp Rosenthal
This document summarizes key points from a presentation on modern intranets and the digital workplace. It discusses how digital workplaces can improve employee satisfaction, effective communication and collaboration, and provide executives with stability. Specific topics covered include business process enablement, collaboration frameworks, best practices, continuous improvement, and the need for leadership, management, and individual responsibility to drive organizational change. The overall message is that digital workplaces can increase business effectiveness and efficiency if properly implemented and supported across all levels of an organization.
10 Enterprise Analytics Trends to Watch in 2019 MicroStrategy
View insights from Forrester analyst Mike Gualtieri, Constellation Research’s Ray Wang and Doug Henschen, Ventana Research’s Mark Smith and David Menninger, IDC’s Chandana Gopal, Marcus Borba, Ronald van Loon and other top analytics and business intelligence thought leaders.
The document discusses how IT sourcing must change to meet the demands of the "Ideas Age" economy. It notes that organizations now need to rapidly respond to changing customer needs. IT departments must be able to quickly source solutions or risk being replaced. The "Ideas Age" requires a focus on core competencies and interconnected functionality with customers. Leaders must source flexible, integrated systems using insourced, outsourced, and multi-sourced services. Cloud computing enables organizations to nimbly source innovative solutions. An "Information Services Sourcing Blueprint" can help organizations define, source, integrate, and deliver best-of-breed business and IT services to achieve outcomes.
The document discusses different perspectives on innovation and provides examples of patterns that companies can use to drive growth through data and new business models. It outlines five patterns: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) codifying distinctive service capabilities. Each pattern is explained and real-world examples are provided to illustrate how companies have used these patterns to innovate, create new sources of value, and develop new business models. The document emphasizes that systematically tackling business innovation through these patterns can improve the odds of success.
The document highlights 5 new patterns of innovation for developing business ideas: 1) augmenting products to generate data, 2) digitizing assets, 3) combining data within and across industries, 4) trading data, and 5) insights from data. It discusses how these patterns can be used ingeniously for new business ideas by utilizing technologies like big data, data integration standards, and cloud computing. The key insights are to consider answers to probable questions within these 5 patterns and that relatively simple moves by existing businesses can help them grow into new large businesses.
The document discusses cognitive search and knowledge management. It notes that 53% of executives see knowledge management as important for innovation. Traditional knowledge management faces challenges around inefficiencies, integration, and consumerization of IT. The document promotes a cognitive, machine learning approach to knowledge management that can find answers, recommend content, and connect people through personalized delivery of information. Benefits include equipping a smarter workforce, tapping collective knowledge, and empowering continued insight. Case studies show how cognitive knowledge management helps Cisco, ThermoFisher, and National Instruments.
This presentation formed part of the Imperial 320 session that took place on Monday, 16 January.
Title of talk: New Patterns of Innovation, How to use Data to Drive Growth
In this presentation, Professor Gann will show how innovation is being transformed through the growth of data about customers, markets, cities and government. This is creating entrepreneurial opportunities to develop new products and services, stimulating new types of start-up business and social enterprise. It is disrupting and transforming the ways in which existing businesses and governments operate, intensifying competition and giving rise to new patterns of innovation.
Data-rich innovation is predicated on making information available for analysis. London provides examples of how this is generating new services and business models successful tech start-ups. Prof Gann’s recent Harvard Business Review article explains why five new patterns of innovation are leading to growth:
Pattern 1. Augmenting products to generate data
Pattern 2. Digitizing assets
Pattern 3. Combining data within and across industries
Pattern 4. Trading data
Pattern 5. Codifying a distinctive service capability
The challenge is to capture, frame, analyse and interpret data to create valuable insights. Success depends upon developing the talent of data scientists: data gatherers,
data modellers and data visionaries. It also requires the right conditions for entrepreneurship to flourish.
For more information, please visit: https://wwwf.imperial.ac.uk/business-school/imperial-business-insights-320/ #Imperial320
Various systematic patterns exist for creating new business value using data and analytics, beyond traditional "hits and misses". These include:
Pattern 1) Using big data to improve operations and explore new areas, like Rolls-Royce's engine health monitoring.
Pattern 2) Making assets mobile, measurable and flexible through digitization, like iTunes.
Pattern 3) Gaining broader access to data for new ventures through data combination across industries, like IBM's Bolzano smart city project.
Managers can apply these patterns by assessing their position, ambitions, and potential using available and creatable data from partners to innovate new business ideas and models in a systematic way beyond conventional approaches.
The search for new business ideas and new business models is hit-or-miss in most corporations, despite the extraordinary pressure on executives to grow their businesses.
1) Organizations want to achieve business value from data-derived insights in four key ways: efficiency/cost reduction, growth of existing business streams, growth through new revenue streams from market disruption, and monetization of data itself through new business lines.
2) Most organizations are adopting an incremental approach to realizing this value, first proving value through use cases, then expanding to pilots in a line of business, and eventually achieving enterprise-wide adoption. This allows them to set a strategic direction while delivering value incrementally.
3) Current business intelligence technology like enterprise data warehouses are not meeting organizations' needs to democratize access to data and analytics. Decision-makers need the ability to rapidly create insights aligned with
Big & Fast Data: The Democratization of InformationCapgemini
Moving from the Enterprise Data Warehouse to the Business Data Lake
Is it possible that ubiquitous analytics represents the next phase of the information age? New business models are emerging, enabled by big data that business leaders are eager to adopt in order to gain advantage and mitigate disruption from start-ups and parallel industries. The winners are likely to be those that master a cultural shift as well as a technology evolution.
Our view is this will be realized through the alignment of a business-centric big data strategy, combined with democratization of the analytical tools, platforms and data lakes that will enable business stakeholders to create, industrialize and integrate insights into their business processes.
Innovative approaches are needed to free up data from silos whilst encouraging both the sharing and the continuous improvement of insights across the business. While it will be evolution for some, revolution for others; the risk of status quo is not just the loss of opportunity but also a widening gap between business and the internal technology functions.
https://www.capgemini.com/thought-leadership/big-fast-data-the-democratization-of-information
201308 Deloitte Tech Trends 2013 - Elements of Post Digital.pdf Francisco Calzado
This document provides a summary of the 2013 Technology Trends report from Deloitte. It identifies the main themes of the report as the "Elements of postdigital" which examines how the convergence of analytics, mobile, social, cloud and cyber technologies can help businesses achieve a "Postdigital Enterprise". The summary identifies the 10 trends covered in the report, which are split into 2 categories: "Disruptors" which can create positive disruption, and "Enablers" which are more evolutionary technologies. It provides a brief high-level description of each trend and notes that the report includes examples, perspectives and potential future directions for each trend.
The document discusses five patterns for developing new business ideas through innovation: 1) Augmenting products to generate data using sensors, 2) Digitizing physical assets, 3) Combining data within and across industries, 4) Trading data between companies, and 5) Codifying a distinctive service capability to sell to other companies using cloud computing. It recommends that managers encourage innovation, examine these five patterns to conceive new business ideas, and help their organization succeed.
The document discusses how companies can fully harness the power of data analytics. It provides two key insights: 1) Companies must choose the right data, build predictive models, and transform capabilities. 2) They should develop business-relevant analytics, embed analytics in simple tools, and develop big data skills. The insights emphasize upgrading managerial analytics skills so decision-making is data-driven. Acting on these insights can help Indian managers lead a successful digital transformation.
The rising collection and analysis of data has shifted the way companies do business. Four key ingredients to develop a data strategy, how to leverage next-generation technologies, and three essential steps for rolling out implementation are included. The Data Ecosystem will show you how to develop and implement the strategies that will meet the needs of your business.
The document discusses analytics and key performance indicators for logistics operations. It covers four main topics: big data, data management, business intelligence tools, and defining and managing indicators. Under big data, it discusses introducing business intelligence and how the digital revolution is transforming markets and the value of information, as well as innovation in business processes and models.
The document discusses the role of the CIO in leading organizations through the Postdigital era, where five forces of analytics, mobile, social, cloud, and cyber are converging and disrupting businesses. It argues that CIOs are uniquely positioned to catalyze change across organizations and help others understand how to leverage new digital opportunities. While CIOs have traditionally faced challenges balancing operational responsibilities with innovation, the current environment presents both risks and opportunities. Forward-thinking CIOs who rise to provoke disruption through these forces may take on expanded leadership roles, such as a Chief Digital Officer, and drive competitive advantage for their organizations.
The document provides information about the Gartner Business Intelligence & Analytics Summit 2013 to be held in Barcelona, Spain from February 5-7, 2013. The summit will focus on key topics in business intelligence and analytics including the future of BI, integrating analytics and BI, predictive analysis, mobile BI, and big data analytics. Attendees can choose from tracks on data management, organization and strategy, performance management, analytic trends, and a virtual track on big data. The agenda includes plenary sessions on the future of information use, information as a business strategy, identity in the digital age, Statoil's beyond budgeting management model, and networking effectively. Early registration before December 7, 2012 provides a €300 discount.
The document discusses five patterns of innovation that companies can use to create customer value using data and analytic tools: 1) Augmenting products by developing insights from product data, 2) Digitizing assets to improve their value, 3) Combining internal and external data, 4) Trading data by structuring it into higher-value information, and 5) Codifying capabilities into digital services. It encourages companies to systematically examine these patterns to engage with the digital economy and find new business opportunities and models using advances in information technology.
The document discusses the role of the CIO in leading business innovation in the postdigital era, where forces like analytics, mobile, social, cloud, and cyber are enabling disruption. It argues that CIOs are uniquely positioned to catalyze value from these forces and change how business is done by harnessing their convergence. Specifically, the CIO can help businesses understand what is possible, provoke thinking beyond existing solutions, and realize transformation. While CIOs face both opportunity and existential threats from disruption, leading CIOs will rise to the challenge by forging new identities as postdigital catalysts. The document suggests some CIOs may take on roles like Chief Digital Officer to lead digital revenue sources and products.
This document discusses how companies have struggled to realize top-line growth from their big data initiatives despite improvements. It argues that companies need a business model innovation capability to complement big data in order to fully realize its growth potential. The document outlines key attributes of big data like volume, variety and velocity. It also presents frameworks for establishing an operational big data process and assessing an organization's big data maturity. Finally, it discusses how companies commonly fail to capitalize on new business ideas from big data and principles for overcoming these pitfalls.
Contents
Discovery-Driven Digital Transformation by Rita McGrath and Ryan McManus
The Transformative Business Model by Stelios Kavadias, Kostas Ladas, and Christoph Loch
Digital Doesn’t Have to Be Disruptive by Nathan Furr and Andrew Shipilov
What’s Your Data Strategy? by Leandro DalleMule and Thomas H. Davenport
Competing in the Age of AI by Marco Iansiti and Karim R. Lakhani
Building the AI-Powered Organization by Tim Fountaine, Brian McCarthy, and Tamim Saleh How Smart,
Connected Products Are Transforming Companies by Michael E. Porter and James E. Heppelmann
The Age of Continuous Connection
The Problem with Legacy Ecosystems by Maxwell Wessel, Aaron Levie, and Robert Siegel
Your Workforce Is More Adaptable Than You Think by Joseph B. Fuller, Judith K. Wallenstein, Manjari Raman, and Alice de Chalendar
How Apple Is Organized for Innovation by Joel M. Podolny and Morten T. Hansen
Digital Transformation Comes Down to Talent in Four Key Areas
1. The document discusses how companies can make advanced analytics work for them by following three steps: choosing the right data, building models that predict and optimize outcomes, and transforming the company's capabilities.
2. It emphasizes that companies first need to identify business problems and opportunities, source data creatively around those issues, and get necessary IT support. Models should be built with the goal of improving performance, not just analyzing data.
3. Transforming capabilities requires developing business-relevant analytics, embedding analytics into simple tools for managers, and developing analytical skills across the organization so data-driven insights can permeate decision making.
Data has become a key focus for corporate leaders today. Chartered Global Management Accountant (CGMA) designation holders are well placed to help translate data into commercial insights and value.
Are you a Digital Transformation leader? Can you create a high-performance strategy in the digital age? Have you got what it takes to avoid the tumbling barrels of distracting digital tactics, over hyped technology or the belief that your market is immune to disruption? Have you allocated the right resources to deliver a focused plan of transformation?
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
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
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
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.
Natural Language Processing (NLP), RAG and its applications .pptxfkyes25
1. In the realm of Natural Language Processing (NLP), knowledge-intensive tasks such as question answering, fact verification, and open-domain dialogue generation require the integration of vast and up-to-date information. Traditional neural models, though powerful, struggle with encoding all necessary knowledge within their parameters, leading to limitations in generalization and scalability. The paper "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks" introduces RAG (Retrieval-Augmented Generation), a novel framework that synergizes retrieval mechanisms with generative models, enhancing performance by dynamically incorporating external knowledge during inference.
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
2. Managers are
supposed to tackle
business innovation
systematically rather
than hoping that
people will get creative
on the fly. The most
recent approach of
searching for ideas is
based on opportunities
generated by Big Data
and Data Analytics
3. This approach poses the question:
How can we create value for
customers using data and analytic
tools we own or we could have access
to ?
4. Advances in IT
Industries have lead
to the search for new
business values in
five different
patterns, examining
which the managers
can conceive solid
ideas for new
businesses.
5.
6. Because of advances in sensors,
wireless communications, and big
data, it’s now feasible to gather and
crunch enormous amounts of data
in a variety of contexts—from wind
turbines to kitchen appliances to
intelligent scalpels.
7. Those data can be used to
improve the design,
operation, maintenance,
and repair of assets or to
enhance how an activity is
carried out. Such
capabilities , in turn, can
become the basis of new
services or new business
models.
8.
9. As mobile technologies continue to
fuel this trend, more creative
businesses are tapping into it and
generating their own enhanced
services or new business models.
Digitized versions of physical assets
are transforming the way people
operate in other industries as well.
10.
11. The science of big
data, along with new
IT standards that
allow enhanced data
integration, makes it
possible to coordinate
information across
industries or
sectors in new ways.
18. In India, managers are expected to
manage a huge workforce. This huge
workforce may consist of people with
loads of out-of-the box ideas but these
ideas are not implemented due to the
lack of strategies for implementing
them in a defined direction.
Brainstorming ideas is a good activity,
but managers cannot expect creative
spree from their employees by
creative jam exercises.
19. The manager must keep in mind all
the four approaches that are
needed to conceive solid ideas for
new businesses, as actual
initiatives encompass more than
one of the approaches. What
begins as a rarely simple business
idea grows up to be a whole new
business.