Corporate Innovation

FEBRUARY 11, 2016

In this first part of this two-part series, I discussed why the automotive industry, particularly the incumbent OEMs, is facing a big data challenge. To do so, automakers must: Think strategically and own the big data strategy. Establish and enforce data ownership rights among the appropriate constituencies.

Big Data 53

Big Data Data Strategy Strategy 53

ITONICS

JUNE 3, 2019

How machine learning is revolutionizing the search for trends and technologies. In this research project, ITONICS is actively involved in the development of an automated environmental scanning system for SMEs. Large amounts of data are available for this purpose, from which the relevant information must first be filtered out.

Big Data 28

Big Data Innovation Management Data Artificial Inteligence 28

ITONICS

JUNE 3, 2019

How machine learning is revolutionizing the search for trends and technologies. In this research project, ITONICS is actively involved in the development of an automated environmental scanning system for SMEs. Large amounts of data are available for this purpose, from which the relevant information must first be filtered out.

Big Data 28

Big Data Innovation Management Data Artificial Inteligence 28

Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension. Automakers must change their perspective.

Big Data 40

Big Data Data System Artificial Inteligence 40

Corporate Innovation

FEBRUARY 11, 2016

In this first part of this two-part series, I discussed why the automotive industry, particularly the incumbent OEMs, is facing a big data challenge. To do so, automakers must: Think strategically and own the big data strategy. Establish and enforce data ownership rights among the appropriate constituencies.

Big Data 40

Big Data Data Strategy Strategy 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

Paul Hobcraft

OCTOBER 2, 2023

This shift has prompted innovation to develop tools and design approaches that support these changes in several critical ways based on four global aspects: Learning from real-time data : Traditional analytics models and past performance data may not be entirely relevant in today’s ever-changing business landscape.

Design Thinking 147

Design Thinking Technical Review Design Technology 147

Acuvate

DECEMBER 7, 2022

Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs. What is Smart Water Management?

Data 78

Data Artificial Inteligence Management Technical Review 78

Acuvate

JANUARY 29, 2019

A large majority of the companies are still dependent on Legacy Systems, Sales and Operations Planning (S&OP) applications, integrated Enterprise Resource Planning (ERP) and homegrown trade promotion solutions. Another issue specifically with legacy systems is that they contribute to internal fragmentation of trade marketing data.

Artificial Inteligence 92

Artificial Inteligence Big Data Data Software Review 92

Idea to Value

JULY 1, 2020

Designers of performance management systems have many tools in their arsenal to make the judgement as “right” and as “fair” as possible. There are assessments for nearly everything and big data will probably provide more on the less tangible things like creativity and likeability.

Report 148

Report Big Data Leadership LEAN 148

Acuvate

APRIL 12, 2023

Productivity, labour costs, and product quality have benefited from the fixed automation and basic control systems used in traditional factory automation. With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Acuvate

APRIL 12, 2023

Productivity, labour costs, and product quality have benefited from the fixed automation and basic control systems used in traditional factory automation. With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Paul Hobcraft

SEPTEMBER 15, 2017

We design the innovation system we need after we know what we are trying to achieve in the challenge or idea. We need to adapt our system thinking to the challenge identified, not the other way around, that of trying to fit them into a generically designed process. It adjusts and you learn. We “pull down” what is needed.

Design 232

Design Technical Review Innovation System 232

Paul Hobcraft

OCTOBER 18, 2022

These barriers do not ‘magically’ change by delivering what I believe moves us to a better system for innovation, that of an ecosystem and platform architecture. It needs access to the best tools and techniques for foresight and interaction as equally critical and needed to build into any robust systems of the future.

Software Review 162

Software Review Innovation Design Technical Review 162

mjvinnovation

APRIL 26, 2019

In our Data Science universe, it represents Machine Learning. Machine learning is nothing more than a model of data analysis. The method starts from the premise that the machine can learn from the data collected, that is, it is able to identify patterns and make decisions on its own, with little human intervention.

Artificial Inteligence 40

Artificial Inteligence Learning Data Analysis 40

Qmarkets

APRIL 9, 2024

AI and big data have been prevalent in the Qmarkets platform for a long time already, including our ‘similar idea’ engine, ‘automated clustering’, ‘content matchmaking’, ‘expert recommendations’ and more. However if you want to harness that power to create value at an enterprise level, you need a much more sophisticated solution.

Innovation Management 59

Innovation Management Management Generative AI Innovation 59

Paul Hobcraft

MAY 9, 2023

I think of the Gartner Hype Cycle here as we have gone through each of the stages of recognition of the application and the learning from this; we have the innovation triggers first, then a peak or inflated expectations, followed by troughs of disillusionment and finally by the slope of enlightenment, to give a new plateau of productivity.

Artificial Inteligence 182

Artificial Inteligence Technical Review Agile Innovation 182

Acuvate

MARCH 16, 2019

Data Analytics in Business. According to Stastia , the global big data market is forecasted to grow to 103 billion U.S. If you are an organization set out to embrace data analytics, here’s a list of the top 5 myths you need to be aware of. Myth 1: Only large companies with big data need data analytics.

Data 80

Data Artificial Inteligence Technical Review Big Data 80

etventure

AUGUST 4, 2020

Deep Learning) require access to huge amounts of data to reach their full potential. Many countries globally have recognized that the handling and processing of these large data sets depend heavily on the agile innovation engines of our economies – the startups.

Data 52

Data Big Data Artificial Inteligence Technical Review 52

InnovationManagement

FEBRUARY 15, 2019

While the business industry—much like the American educational system—has been slow to the uptake of implementing technological advancements into their marketing and planning strategies, the 2020s herald a new age for the use of data and technological advancement in companies big and small.

Data 61

Data Company Big Data Culture 61

Jeffrey Phillips

MAY 31, 2019

In my last post I tried to illustrate the importance (and the challenges) of data to digital transformation. This is often a complex and difficult idea for people to understand - why is "data" so hard? Why can't computer systems work more effectively? None of these things can be accomplished without data.

Data 129

Data Artificial Inteligence Innovation Big Data 129

Tullio Siragusa

JULY 25, 2022

The Tech Backstage Podcast is a live streamed video podcast that goes behind the scenes with today’s leaders of industry to learn what technologies are solving business problems, and how Design Thinking applied to the future of technology is impacting the world. Anyone can learn to be creative if they put in the effort. Pet Markt Co.

Data 118

Data Creativity Technical Review Innovation 118

Ecosystems4Innovating

NOVEMBER 2, 2023

Machine Learning and AI-Driven Insights : Integrating AI and machine learning into the Design Thinking process can provide valuable insights. For example, AI can analyze large datasets of user feedback to identify patterns and trends, guiding designers in making data-informed decisions.

Design Thinking 59

Design Thinking Design Technical Review Artificial Inteligence 59

The Inovo Group

NOVEMBER 8, 2017

To address this inherent uncertainty, it is useful to have a framework and model of the innovation system which defines the structural and operational components of the system as well as operational outcomes. This analysis was used to create an innovation system framework and model to help understand and categorize the various metrics.

System 40

System Analysis Innovation Data 40

Acuvate

FEBRUARY 21, 2022

Leveraging AI, Big Data, IoT, and Analytics to boost data-driven decision-making. Research by Gartner suggested that oil and gas CIOs listed AI, machine learning (ML), analytics, and industrial IoT as the top game-changing technologies in 2021. Digital Transformation Journeys in the Oil and Gas Industry.

Artificial Inteligence 52

Artificial Inteligence Industry Big Data Data 52

Acuvate

OCTOBER 10, 2022

Darryl Williams, Corporate Vice President of Energy at Microsoft , rightly said, “Technologies like AI and machine learning can analyze the past, optimize the present, and predict the future.” This data repository is analyzed by AI algorithms in real time. AI Applications in the Oil and Gas Industry. Driving workplace safety.

Artificial Inteligence 66

Artificial Inteligence Industry Big Data Data 66

hackerearth

MARCH 5, 2019

The Internet of Things (IoT) is a system of interrelated devices that have unique identifiers and can autonomously transfer data over a network. Philips e-Alert is an IoT-enabled tool that monitors critical medical hardware such as MRI systems and warns healthcare organizations of an impending failure, preventing unnecessary downtime.

Internet of things 110

Internet of things Artificial Inteligence Technical Review Data 110

Ecosystems4Innovating

MARCH 21, 2024

It is by the very nature of the interacting and interdependence in relationships that is driving this need to participate in an interconnected system, one that is looking to create and allocate new business value, acting together, and offering the potential for the outcomes to be greater than the sum of the individual parts.

Collaboration 52

Collaboration Competition Big Data Technology 52

Acuvate

JANUARY 2, 2020

Advanced analytics helps to mine through big data for actionable insights which can be used for a plethora of business use cases. These models use historical data on fraudulent activities to arrive at specific conditions that predict the possibility of claims being fake.

Industry 59

Industry Artificial Inteligence Big Data Data 59

Jeffrey Phillips

JANUARY 9, 2020

There were financial applications, manufacturing applications and customer service applications but no unified, enterprise application that integrated systems and data across all the functions. SAP changed that, taking the market by storm and changing our expectations about software solutions and data integration.

Artificial Inteligence 175

Artificial Inteligence Data Tools System 175

Acuvate

JANUARY 23, 2020

With the advancements in natural language processing (NLP), Big Data, artificial intelligence (AI) and automation, businesses are replacing their traditional Business Intelligence (BI) systems with modern automated BI systems over the last few years. with BI systems. Wrapping Up.

Artificial Inteligence 98

Artificial Inteligence Data System Report 98

Paul Hobcraft

JUNE 18, 2019

The second view we always need to consider is a “System thinking” one. I really love this visual for system thinking that outlines the key insights and tools needed to develop and advance a systems mindset for dealing with complex problem solving and transitioning to the Circular Economy. Does it go beyond the existing?

Design Thinking 217

Design Thinking Innovation Design System 217

Acuvate

NOVEMBER 6, 2019

Azure Synapse, built on Azure SQL Data warehouse, is an evolved analytics service, intended to bridge the gap between data warehouses and data lakes. It offers a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning applications. Data Engineers, data.

Data 49

Data Artificial Inteligence Big Data Learning 49

Norbert Bol

JANUARY 18, 2020

AI can be described as machines capable of imitating certain functionalities of human intelligence, including such features as perception, learning, reasoning, problem-solving, language interaction, and even producing creative work. Viewing AI-systems from a risk management perspective. Purpose and Principles.

Artificial Inteligence 56

Artificial Inteligence Technical Review Data System 56

Innovation 360 Group

MARCH 14, 2019

Ready for a lifelong learning journey. Insights and learnings. Creating Echo Systems and Eco System Innovation. Digitalization, Big Data and Artificial Intelligence – Linking to technology. Digitalization, Big Data and Artificial Intelligence – Linking to technology. Excel in ideation.

Artificial Inteligence 40

Artificial Inteligence Big Data Ideation System 40