This document provides an overview of Jalgos, an AI and data studio. It discusses Jalgos' mission to bring AI and data strategies to clients to help them innovate. It describes Jalgos' approach which includes strategic consulting, building prototypes, and developing internal research projects. The document outlines Jalgos' methodology, which focuses on data strategy, adapting algorithms through exploration, development and productization. It also discusses Jalgos' values, hiring process, and how to work with the company.
The document discusses a project that aimed to predict employee absenteeism using predictive analytics. It describes some of the key factors for the project's success, including having an interdisciplinary team and creating a large number of potential predictor variables from available data. The results showed that previous absenteeism, job evaluation scores, and feeling supported by colleagues were good predictors of future absenteeism. The model performed well at an aggregated level and can now be used and maintained by the company itself.
They serve customers across small, Mid-size and Enterprise segments-ranging from $50M to $50B in size-in multiple industries.
Services include: End-to-end implementations, managed services, project management, training, integrations with enterprise systems, and business process re-engineering.
Catalysing Innovation in Pharma IT: Keeping AstraZeneca Ahead of Disruptive T...Nick Brown
Presentation by Rob Hernandez (senior data scientist) in my team at 14th Annual Pharmaceutical IT Congress in London on September 28th 2016 . Brief overview about how our world and more specifically the pharmaceutical industry is being disrupted by technology. We share some emerging technology areas that we are focusing on, demonstrating value to our R&D, Operations and Commercial teams but also how we catalyse innovation across our IT organisation. Examples include exploratory work on AI chatbots, video facial sentiment detection, scientific search and sensor technology.
Extending Enterprise Search To Catalyse Innovation In A Global OrganisationNick Brown
Presentation by Steve Woodward in my team at Enterprise Search Summit 2015 in London on 20th October. Examples of how we have leveraged a cloud-based enterprise search platform to help drive our mobile and user experience competencies across a global organisation. Examples include an enterprise mobile app for simplifying approvals, search-based microapplications and in-video transcription.
This document provides an overview and agenda for building an analytics capability. It discusses key topics such as:
- The importance of big data and analytics for business decisions
- Building an analytics capability requires the right people, processes, and technology
- Companies can build capabilities internally, outsource work, or use a hybrid approach
- When outsourcing analytics work, firms need to consider issues like vendor skills, data protection, and intellectual property ownership
40 ° advises and supports companies and institutions to generate real added value from data and to generate data-driven innovations and new business models. We help to reinvent your business with data. 40 ° is the expert for data driven business transformation
Chris Day VP IT Transformation and Office of the CIO at AstraZenecaSteve Ashton
This document summarizes an event for IT executive leaders addressing digital challenges. The agenda introduces AstraZeneca and its focus on discovery, development and commercialization of medicines. It operates globally with $26.1B in annual sales. AstraZeneca IT aims to create a world-class environment through customer focus, operational excellence, technical leadership, simplification and collaboration. The digital transformation presents opportunities for IT leaders to strategically drive innovation and growth. New skills must be developed around data, technology, channels and digital capabilities. Barriers include strategy, skills and budgets. Recommendations include engaging on digital innovation and applying technology choices to business capabilities.
The document discusses a project that aimed to predict employee absenteeism using predictive analytics. It describes some of the key factors for the project's success, including having an interdisciplinary team and creating a large number of potential predictor variables from available data. The results showed that previous absenteeism, job evaluation scores, and feeling supported by colleagues were good predictors of future absenteeism. The model performed well at an aggregated level and can now be used and maintained by the company itself.
They serve customers across small, Mid-size and Enterprise segments-ranging from $50M to $50B in size-in multiple industries.
Services include: End-to-end implementations, managed services, project management, training, integrations with enterprise systems, and business process re-engineering.
Catalysing Innovation in Pharma IT: Keeping AstraZeneca Ahead of Disruptive T...Nick Brown
Presentation by Rob Hernandez (senior data scientist) in my team at 14th Annual Pharmaceutical IT Congress in London on September 28th 2016 . Brief overview about how our world and more specifically the pharmaceutical industry is being disrupted by technology. We share some emerging technology areas that we are focusing on, demonstrating value to our R&D, Operations and Commercial teams but also how we catalyse innovation across our IT organisation. Examples include exploratory work on AI chatbots, video facial sentiment detection, scientific search and sensor technology.
Extending Enterprise Search To Catalyse Innovation In A Global OrganisationNick Brown
Presentation by Steve Woodward in my team at Enterprise Search Summit 2015 in London on 20th October. Examples of how we have leveraged a cloud-based enterprise search platform to help drive our mobile and user experience competencies across a global organisation. Examples include an enterprise mobile app for simplifying approvals, search-based microapplications and in-video transcription.
This document provides an overview and agenda for building an analytics capability. It discusses key topics such as:
- The importance of big data and analytics for business decisions
- Building an analytics capability requires the right people, processes, and technology
- Companies can build capabilities internally, outsource work, or use a hybrid approach
- When outsourcing analytics work, firms need to consider issues like vendor skills, data protection, and intellectual property ownership
40 ° advises and supports companies and institutions to generate real added value from data and to generate data-driven innovations and new business models. We help to reinvent your business with data. 40 ° is the expert for data driven business transformation
Chris Day VP IT Transformation and Office of the CIO at AstraZenecaSteve Ashton
This document summarizes an event for IT executive leaders addressing digital challenges. The agenda introduces AstraZeneca and its focus on discovery, development and commercialization of medicines. It operates globally with $26.1B in annual sales. AstraZeneca IT aims to create a world-class environment through customer focus, operational excellence, technical leadership, simplification and collaboration. The digital transformation presents opportunities for IT leaders to strategically drive innovation and growth. New skills must be developed around data, technology, channels and digital capabilities. Barriers include strategy, skills and budgets. Recommendations include engaging on digital innovation and applying technology choices to business capabilities.
Pressing the Advantage - Disruptive Acceleration with DataViz & Analytics at ...Lewandog, Inc,
Cisco designs and sells networking products worldwide, with the goal of becoming the #1 IT company. The document discusses Cisco's efforts to advance data visualization and analytics through a community-driven approach. It outlines moving from traditional slow and expensive BI models to a more self-reliant approach that enables any business user to access, understand and share data through interactive visualizations. The analytics center of excellence aims to accelerate Cisco's competitive advantage by promoting a culture of data-driven decision making across the organization.
The document discusses the importance of operationalizing analytics and productizing predictive models. It notes that while companies often focus on developing new models and hiring data scientists, executives only care about improvements that generate revenue or savings. As such, 60% of big data projects fail because they do not progress beyond piloting. To successfully operationalize analytics, companies need an integrated technology platform, well-defined processes, and the right mix of skills among data scientists and analysts. This includes a focus on communication, business skills, and leveraging new technologies rather than just mathematical abilities. Organizing analytics teams into a center of excellence also improves coordination and impact.
See the Whole Story: The Case for a Visualization PlatformEric Kavanagh
Seeing is believing, which is why data visualization continues to play a major role in helping businesses understand their data. But there's more than meets the eye. Underneath that stimulating surface layer, some data environments are much more organized -- and thus reliable -- than others. The key to success? Taking a platform approach to address the entire end-to-end process of delivering governed, scalable analytics.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor explain why a platform approach to visual analytics enables the kind of governance that today's organizations need. He'll be briefed by Dan Brault of Qlik, who will showcase his company's analytics platform which was built from the ground up with the design point of delivering analytics to everyone in an organization. He'll stress the importance of governance, trust and scalability.
The ultimate value of historical data lays in addressing the questions "what will happen?" and "what is the best that could happen?". This session will detail how SAP Predictive Analytics empowers business decision makers by making accurate predictions in an agile and self-service manner.
Your smarter data analytics strategy - Social Media Strategies Summit (SMSS) ...Clark Boyd
This document provides an overview of developing an effective analytics strategy, covering key topics such as:
- Understanding why an analytics strategy is important for gaining insights from data
- Defining the right questions to ask of your data to address business objectives
- Implementing the right metrics and processes to optimize performance based on data
- Ensuring the right technology, data, people and culture are in place to execute the strategy
- Tips for reporting data to different stakeholders and developing the right analytics team
The presentation emphasizes that an analytics strategy should start by defining business goals and questions, and focus on using data insights to drive tangible improvements rather than just reporting metrics. Both qualitative and quantitative data are important to
Agile Analytics: The Secret to Test, Improve, Fail & Succeed Quickly.Venveo
The document discusses agile analytics and its benefits for businesses. Agile analytics involves rapidly testing hypotheses, analyzing results, and making improvements to gain a better understanding of customers, get results more quickly, and reduce risks. It recommends businesses focus on a single problem, develop small testable hypotheses, iterate testing every 2-4 weeks with specific changes, and use findings to direct the next round of improvements. Practicing agile analytics allows organizations to test, improve, fail, and succeed quickly.
Information Management is facing unprecedented upheaval due to one major force - Big Data. As quantities of information increase, it's possible to save vast amounts of data that in the past would have been discarded. Now, data is the raw material of exciting exercises in predictive analytics - and the results are game-changing for many businesses. Watch this joint webcast from Collaborative Consulting and IDG to learn how to launch a big data proof-of-concept at your organization.
Ironside's VP of Strategy & Innovation, Greg Bonnette, delivered a presentation on "How to Build a Winning Strategy for Data & Analytics" to provide a framework for data-driven decision making.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
ScienceSoft is an international IT company established in 1989 that provides custom software development, IT consulting, and outsourcing services. It has over 400 employees located in Minsk, Belarus and Helsinki, Finland. ScienceSoft has expertise in areas such as mobile applications, enterprise software, security solutions, and cloud services. It has completed projects for over 100 customers in 25 countries.
This document discusses privacy enhancing technologies and how to become a responsible data handler. It outlines the 7 principles of "Privacy by Design" which aim to embed privacy into system design from the start. Examples are given of how these principles can be applied, such as having a privacy expert on the design team, making privacy the default setting, and ensuring transparency. Benefits discussed include increased customer trust, profits, and insights. Trends in privacy research like differential privacy and artificial data are also mentioned. The overall message is that privacy should be seen as an opportunity rather than a hindrance.
Webinar: Business Intelligence From The Inside OutCorSourceTechPDX
There are a lot of terms thrown around in the world of business intelligence and analytics. Presented as a webinar, this deck is an introduction to the terminology and power of business intelligence to transform companies.
According to recent research report by Wall Street Journal, AI project failure rates near 50%, more than 53% terminates at proof of concept level and does not make it to production. Gartner report says that nearly 80% of the analytics projects are not delivering any business value. That means for every 10 projects, only 2 projects are useful to the organization. Let us pause here a moment, rather than looking at what makes AI projects to fail, let’s look at the challenges involved in AI projects and find a solution to overcome these challenges.
AI projects are different from traditional software projects. Typical software projects, as shown in Figure 1, consist of well-defined software requirements, high level design, coding, unit testing, system testing, and deployment along with beta testing or field testing. Now, organizations are adopting Agile process instead of traditional V or waterfall model, but still steps mentioned are valid.
However, AI and Machine Learning projects’ methodology is different from the above. Our experience working on many AI/ML projects has given us insights on some of the challenges of executing AI projects. Also, we are in regular touch with senior executives and thought leaders from different industries who understand the success formula. The following discussion is based on our practical experience and knowledge gained in the field.
Successful execution of AI projects depends on the following factors:
1. Clearly aligned Business Expectations
2. Clarity on Terminologies
3. Meeting Data Requirements
4. Tools and Technology
5. Right Resources
6. Understanding Output Results
7. Project Planning and the Process
The demand for data insights to drive decisions is higher today than ever before. This isn't just because volumes of accessible data are growing, but also because people are more data literate and accustomed to engaging information experiences from consumer apps like LinkedIn, Google Maps, & Yelp.
This same thirst for intelligence is probably apparent in your user base, whether you realize it or not - and taking the time to invest in a data & analytics strategy for your product can yield significant customer & business benefits over time.
About the Speakers:
Michelle Bradbury,Director of Product Management, Pentaho
Michelle has over 18 years of experience in technology product & project management. She enjoys collaboratively creating & delivering highly compelling products and has held roles at organizations including Microsoft, Fujitsu, & CapitalOne. Michelle's areas of expertise include database and data warehouse architecture and development, project and budget management, as well as process definition and implementation for group cohesiveness.
Ben Hopkins, Product Marketing Manager, Pentaho
Ben is focused on embedded analytics & OEM partnerships. He has also held product marketing roles at Marketo and Salesforce.com. He holds an MBA from the U.C. Berkeley Haas School of Business as well as a BA in Economics from Harvard College.
Pentaho is delivering the future of analytics with a comprehensive platform for data integration & business intelligence. Learn more at www.pentaho.com.
Upcoming Events
Would you like to lead innovation efforts within your company? Attend upcoming product innovation courses. Visit: http://bit.ly/CILCourse
Looking for a coach to accelerate your product marketing & management career?
Set up a free initial 30-minute appointment for more information: http://bit.ly/1gBFdaD.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, contact AIPMM at certification@aipmm.com.
About AIPMM
The AIPMM is the trusted authority in product management. It is where product professionals go for answers. With members in over 75 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
Subscribe: http://www.aipmm.com/subscribe
Articles: http://www.aipmm.com/html/newsletter/article.ph
Membership: http://www.aipmm.com/join.php
Smarter Banking Webinar - Transform the Customer Relationship into your Most ...DXC Eclipse
This document discusses how digital transformation can help banks adapt to changing customer expectations and industry forces. It outlines DXC's digital transformation offerings focused on customer experience, digital workplace, business optimization, and systems of insight. The presentation demonstrates capabilities like customer 360 views, business process optimization, financial insights, and bot automation. It also discusses DXC's agile delivery approach and partnership with startups to bring new offerings to market. DXC positions itself as the largest independent Microsoft Dynamics partner with deep industry expertise to help banks transform digitally.
Big Data : From HindSight to Insight to ForesightSunil Ranka
When it comes to Analytics and Reporting , There is a fine line between HindSight to Insight to Foresight . With the evolution of BigData technology, there is a need in deriving value out of the larger datasets, not available in the past. Even before we can start using the new shiny technologies, there is a need of understanding what is categorized as reporting or business intelligence or Big Data and Analytics. Based on my experience, people struggle to distinguish between reporting, Analytics, and Business Intelligence.
Who, What, Where and How: Why You Want to KnowEric Kavanagh
Hot Technologies with Dr. Robin Bloor, Dez Blanchfield and IDERA
In our increasingly data-driven society, knowing who did what with information assets is a must-have. Every aspect of the business benefits: operations, analytics, planning, compliance. The story gets even more serious when sensitive information comes into play. For all these reasons and more, the modern business needs to know what's happening where, and who is involved in the process.
Register for this episode of Hot Technologies to hear Dr. Robin Bloor and Data Scientist Dez Blanchfield extol the virtues of data awareness. They'll be briefed by Bullett Manale of IDERA, who will demonstrate how his company's software allows organizations to gain deep insights into their data, right down to the column level. He'll show how to audit the most sensitive information, monitor and alert on suspicious activity, satisfy audits for PCI, HIPAA, FERPA and SOX -- all from a Web-based dashboard that simplifies access from any browser.
How the Analytics Translator can make your organisation more AI drivenSteven Nooijen
The document discusses how the Analytics Translator role can help organizations become more AI-driven by bridging the gap between business and technology. The Analytics Translator collects and prioritizes ideas, develops business cases for AI solutions, guides the solution development process, and drives adoption. Characteristics of a good Analytics Translator include understanding both business and AI, taking ownership, and operating at the intersection of UX, technology, and business. Developing this role is important for companies to successfully create impact and value from data and AI.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
AstraZeneca is a global pharmaceutical company with over $24 billion in annual revenue. It has over 61,500 employees working across R&D, manufacturing, and collaborations in 17 countries. AstraZeneca's IT department was undergoing a transformation to become more customer-focused, operationally excellent, and a technical leader by 2018. This involved insourcing IT jobs to new technology centers in India, Mexico, China, and Eastern Europe, simplifying applications, using cloud services, and cutting annual IT spending from $1.35 billion to $930 million while improving services. The changes have led to improved user experiences, more mobile and collaborative tools, and helped position AstraZeneca for future technology-enabled business
Discover. Learn. Evolve
Technology is a discovery assisting you to evolve through the lifetime of learning. Global Infocloud believes in implementing our knowledge, hard work and talent to guide you on your success path.
AI Maturity Levels and the Analytics TranslatorGoDataDriven
Buzzwords like Big Data, Cloud, and AI have been out there now for a couple of years. But today, businesses have a clear focus on the application of data use cases and the challenges around that such as metadata management, governance, security, and maintainability in general. Everybody seems to have some version of a data lake and wants to consolidate it into something (more) useful, or move from an on-premise version to the cloud. There is a general need to streamline current practices while also attempting to give multiple segments of users (data scientists, analysts, marketeers, business people, and HR) access in a way that is tailored to their needs and skills. In other words: businesses today are heavily invested in data and AI, but many have a hard time knowing how to mature it to the next level.
This is exactly where a "maturity model" comes into play. The goal of a maturity model is to help businesses in understanding their current and target competencies. This helps organisations in defining a roadmap for improving their competency. A maturity model is therefore one way of structuring progression, whether the company already embraces data science as a core competency, or, if it is just getting started.
In this presentation on maturity models, we answer the following questions:
1. What exactly is a maturity model and why would you need it? We address this by sharing GoDataDriven's maturity model and describing the different phases we have identified based on our experience in the field.
2. How can you use a maturity model to advance your organisation? Having a maturity model alone is not enough, in order for it to be valuable you need to act upon it. This paper provides concrete examples on how to do act based on practical stories and experiences from our clients and ourselves.
Pressing the Advantage - Disruptive Acceleration with DataViz & Analytics at ...Lewandog, Inc,
Cisco designs and sells networking products worldwide, with the goal of becoming the #1 IT company. The document discusses Cisco's efforts to advance data visualization and analytics through a community-driven approach. It outlines moving from traditional slow and expensive BI models to a more self-reliant approach that enables any business user to access, understand and share data through interactive visualizations. The analytics center of excellence aims to accelerate Cisco's competitive advantage by promoting a culture of data-driven decision making across the organization.
The document discusses the importance of operationalizing analytics and productizing predictive models. It notes that while companies often focus on developing new models and hiring data scientists, executives only care about improvements that generate revenue or savings. As such, 60% of big data projects fail because they do not progress beyond piloting. To successfully operationalize analytics, companies need an integrated technology platform, well-defined processes, and the right mix of skills among data scientists and analysts. This includes a focus on communication, business skills, and leveraging new technologies rather than just mathematical abilities. Organizing analytics teams into a center of excellence also improves coordination and impact.
See the Whole Story: The Case for a Visualization PlatformEric Kavanagh
Seeing is believing, which is why data visualization continues to play a major role in helping businesses understand their data. But there's more than meets the eye. Underneath that stimulating surface layer, some data environments are much more organized -- and thus reliable -- than others. The key to success? Taking a platform approach to address the entire end-to-end process of delivering governed, scalable analytics.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor explain why a platform approach to visual analytics enables the kind of governance that today's organizations need. He'll be briefed by Dan Brault of Qlik, who will showcase his company's analytics platform which was built from the ground up with the design point of delivering analytics to everyone in an organization. He'll stress the importance of governance, trust and scalability.
The ultimate value of historical data lays in addressing the questions "what will happen?" and "what is the best that could happen?". This session will detail how SAP Predictive Analytics empowers business decision makers by making accurate predictions in an agile and self-service manner.
Your smarter data analytics strategy - Social Media Strategies Summit (SMSS) ...Clark Boyd
This document provides an overview of developing an effective analytics strategy, covering key topics such as:
- Understanding why an analytics strategy is important for gaining insights from data
- Defining the right questions to ask of your data to address business objectives
- Implementing the right metrics and processes to optimize performance based on data
- Ensuring the right technology, data, people and culture are in place to execute the strategy
- Tips for reporting data to different stakeholders and developing the right analytics team
The presentation emphasizes that an analytics strategy should start by defining business goals and questions, and focus on using data insights to drive tangible improvements rather than just reporting metrics. Both qualitative and quantitative data are important to
Agile Analytics: The Secret to Test, Improve, Fail & Succeed Quickly.Venveo
The document discusses agile analytics and its benefits for businesses. Agile analytics involves rapidly testing hypotheses, analyzing results, and making improvements to gain a better understanding of customers, get results more quickly, and reduce risks. It recommends businesses focus on a single problem, develop small testable hypotheses, iterate testing every 2-4 weeks with specific changes, and use findings to direct the next round of improvements. Practicing agile analytics allows organizations to test, improve, fail, and succeed quickly.
Information Management is facing unprecedented upheaval due to one major force - Big Data. As quantities of information increase, it's possible to save vast amounts of data that in the past would have been discarded. Now, data is the raw material of exciting exercises in predictive analytics - and the results are game-changing for many businesses. Watch this joint webcast from Collaborative Consulting and IDG to learn how to launch a big data proof-of-concept at your organization.
Ironside's VP of Strategy & Innovation, Greg Bonnette, delivered a presentation on "How to Build a Winning Strategy for Data & Analytics" to provide a framework for data-driven decision making.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
ScienceSoft is an international IT company established in 1989 that provides custom software development, IT consulting, and outsourcing services. It has over 400 employees located in Minsk, Belarus and Helsinki, Finland. ScienceSoft has expertise in areas such as mobile applications, enterprise software, security solutions, and cloud services. It has completed projects for over 100 customers in 25 countries.
This document discusses privacy enhancing technologies and how to become a responsible data handler. It outlines the 7 principles of "Privacy by Design" which aim to embed privacy into system design from the start. Examples are given of how these principles can be applied, such as having a privacy expert on the design team, making privacy the default setting, and ensuring transparency. Benefits discussed include increased customer trust, profits, and insights. Trends in privacy research like differential privacy and artificial data are also mentioned. The overall message is that privacy should be seen as an opportunity rather than a hindrance.
Webinar: Business Intelligence From The Inside OutCorSourceTechPDX
There are a lot of terms thrown around in the world of business intelligence and analytics. Presented as a webinar, this deck is an introduction to the terminology and power of business intelligence to transform companies.
According to recent research report by Wall Street Journal, AI project failure rates near 50%, more than 53% terminates at proof of concept level and does not make it to production. Gartner report says that nearly 80% of the analytics projects are not delivering any business value. That means for every 10 projects, only 2 projects are useful to the organization. Let us pause here a moment, rather than looking at what makes AI projects to fail, let’s look at the challenges involved in AI projects and find a solution to overcome these challenges.
AI projects are different from traditional software projects. Typical software projects, as shown in Figure 1, consist of well-defined software requirements, high level design, coding, unit testing, system testing, and deployment along with beta testing or field testing. Now, organizations are adopting Agile process instead of traditional V or waterfall model, but still steps mentioned are valid.
However, AI and Machine Learning projects’ methodology is different from the above. Our experience working on many AI/ML projects has given us insights on some of the challenges of executing AI projects. Also, we are in regular touch with senior executives and thought leaders from different industries who understand the success formula. The following discussion is based on our practical experience and knowledge gained in the field.
Successful execution of AI projects depends on the following factors:
1. Clearly aligned Business Expectations
2. Clarity on Terminologies
3. Meeting Data Requirements
4. Tools and Technology
5. Right Resources
6. Understanding Output Results
7. Project Planning and the Process
The demand for data insights to drive decisions is higher today than ever before. This isn't just because volumes of accessible data are growing, but also because people are more data literate and accustomed to engaging information experiences from consumer apps like LinkedIn, Google Maps, & Yelp.
This same thirst for intelligence is probably apparent in your user base, whether you realize it or not - and taking the time to invest in a data & analytics strategy for your product can yield significant customer & business benefits over time.
About the Speakers:
Michelle Bradbury,Director of Product Management, Pentaho
Michelle has over 18 years of experience in technology product & project management. She enjoys collaboratively creating & delivering highly compelling products and has held roles at organizations including Microsoft, Fujitsu, & CapitalOne. Michelle's areas of expertise include database and data warehouse architecture and development, project and budget management, as well as process definition and implementation for group cohesiveness.
Ben Hopkins, Product Marketing Manager, Pentaho
Ben is focused on embedded analytics & OEM partnerships. He has also held product marketing roles at Marketo and Salesforce.com. He holds an MBA from the U.C. Berkeley Haas School of Business as well as a BA in Economics from Harvard College.
Pentaho is delivering the future of analytics with a comprehensive platform for data integration & business intelligence. Learn more at www.pentaho.com.
Upcoming Events
Would you like to lead innovation efforts within your company? Attend upcoming product innovation courses. Visit: http://bit.ly/CILCourse
Looking for a coach to accelerate your product marketing & management career?
Set up a free initial 30-minute appointment for more information: http://bit.ly/1gBFdaD.
Want To Certify Your Team?
If you have a product team of 10 or more that you want to certify, contact AIPMM at certification@aipmm.com.
About AIPMM
The AIPMM is the trusted authority in product management. It is where product professionals go for answers. With members in over 75 countries, it is the worldwide certifying body of product team professionals.
It is the world's largest professional organization of product managers, brand managers, product marketing managers and other product team professionals who are responsible for guiding their organizations, or clients, through a constantly changing business landscape.
AIPMM's certification programs are internationally recognized because they allow product professionals to demonstrate their expertise and provide corporate members an assurance that their product management and marketing teams are operating at a high competency level.
Visit http://www.aipmm.com.
Call For Speakers: http://bit.ly/1b006vm
Subscribe: http://www.aipmm.com/subscribe
Articles: http://www.aipmm.com/html/newsletter/article.ph
Membership: http://www.aipmm.com/join.php
Smarter Banking Webinar - Transform the Customer Relationship into your Most ...DXC Eclipse
This document discusses how digital transformation can help banks adapt to changing customer expectations and industry forces. It outlines DXC's digital transformation offerings focused on customer experience, digital workplace, business optimization, and systems of insight. The presentation demonstrates capabilities like customer 360 views, business process optimization, financial insights, and bot automation. It also discusses DXC's agile delivery approach and partnership with startups to bring new offerings to market. DXC positions itself as the largest independent Microsoft Dynamics partner with deep industry expertise to help banks transform digitally.
Big Data : From HindSight to Insight to ForesightSunil Ranka
When it comes to Analytics and Reporting , There is a fine line between HindSight to Insight to Foresight . With the evolution of BigData technology, there is a need in deriving value out of the larger datasets, not available in the past. Even before we can start using the new shiny technologies, there is a need of understanding what is categorized as reporting or business intelligence or Big Data and Analytics. Based on my experience, people struggle to distinguish between reporting, Analytics, and Business Intelligence.
Who, What, Where and How: Why You Want to KnowEric Kavanagh
Hot Technologies with Dr. Robin Bloor, Dez Blanchfield and IDERA
In our increasingly data-driven society, knowing who did what with information assets is a must-have. Every aspect of the business benefits: operations, analytics, planning, compliance. The story gets even more serious when sensitive information comes into play. For all these reasons and more, the modern business needs to know what's happening where, and who is involved in the process.
Register for this episode of Hot Technologies to hear Dr. Robin Bloor and Data Scientist Dez Blanchfield extol the virtues of data awareness. They'll be briefed by Bullett Manale of IDERA, who will demonstrate how his company's software allows organizations to gain deep insights into their data, right down to the column level. He'll show how to audit the most sensitive information, monitor and alert on suspicious activity, satisfy audits for PCI, HIPAA, FERPA and SOX -- all from a Web-based dashboard that simplifies access from any browser.
How the Analytics Translator can make your organisation more AI drivenSteven Nooijen
The document discusses how the Analytics Translator role can help organizations become more AI-driven by bridging the gap between business and technology. The Analytics Translator collects and prioritizes ideas, develops business cases for AI solutions, guides the solution development process, and drives adoption. Characteristics of a good Analytics Translator include understanding both business and AI, taking ownership, and operating at the intersection of UX, technology, and business. Developing this role is important for companies to successfully create impact and value from data and AI.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
AstraZeneca is a global pharmaceutical company with over $24 billion in annual revenue. It has over 61,500 employees working across R&D, manufacturing, and collaborations in 17 countries. AstraZeneca's IT department was undergoing a transformation to become more customer-focused, operationally excellent, and a technical leader by 2018. This involved insourcing IT jobs to new technology centers in India, Mexico, China, and Eastern Europe, simplifying applications, using cloud services, and cutting annual IT spending from $1.35 billion to $930 million while improving services. The changes have led to improved user experiences, more mobile and collaborative tools, and helped position AstraZeneca for future technology-enabled business
Discover. Learn. Evolve
Technology is a discovery assisting you to evolve through the lifetime of learning. Global Infocloud believes in implementing our knowledge, hard work and talent to guide you on your success path.
AI Maturity Levels and the Analytics TranslatorGoDataDriven
Buzzwords like Big Data, Cloud, and AI have been out there now for a couple of years. But today, businesses have a clear focus on the application of data use cases and the challenges around that such as metadata management, governance, security, and maintainability in general. Everybody seems to have some version of a data lake and wants to consolidate it into something (more) useful, or move from an on-premise version to the cloud. There is a general need to streamline current practices while also attempting to give multiple segments of users (data scientists, analysts, marketeers, business people, and HR) access in a way that is tailored to their needs and skills. In other words: businesses today are heavily invested in data and AI, but many have a hard time knowing how to mature it to the next level.
This is exactly where a "maturity model" comes into play. The goal of a maturity model is to help businesses in understanding their current and target competencies. This helps organisations in defining a roadmap for improving their competency. A maturity model is therefore one way of structuring progression, whether the company already embraces data science as a core competency, or, if it is just getting started.
In this presentation on maturity models, we answer the following questions:
1. What exactly is a maturity model and why would you need it? We address this by sharing GoDataDriven's maturity model and describing the different phases we have identified based on our experience in the field.
2. How can you use a maturity model to advance your organisation? Having a maturity model alone is not enough, in order for it to be valuable you need to act upon it. This paper provides concrete examples on how to do act based on practical stories and experiences from our clients and ourselves.
Gridle provides digital experiences, interfaces, and solutions for financial enterprises. They offer UI/UX research and design, development and deployment of solutions using an agile approach, and consultancy in areas like architecture, machine learning, and natural language processing. Some of their offerings include a collaboration suite, contract management system, and learning management system. They aim to streamline workflows, increase productivity and transparency, and optimize performance for their clients.
iiiQbets is an agile, customer-centric organization that provides digital transformation solutions such as data analytics, business intelligence, cloud services, application development, digital marketing, and business process reengineering. The company's mission is to help clients with their digital transformation journeys through services related to data science and managing data in the cloud. iiiQbets has a team of technology experts and relies on innovation and embracing new technologies to create value for customers and employees.
This document discusses key applications for building responsible artificial intelligence in industry. It begins by noting that consumers and enterprises have different AI needs. It then outlines Google's approach to responsible AI, including their AI principles, product and use case reviews, and governance practices. The document discusses several potential use cases for generative AI in communication service providers, including contact center automation, network capacity planning, and creative generation. It provides examples of how generative AI could increase employee and operational efficiency through customer service automation, employee knowledge search, and contract analysis. The document emphasizes the importance of an organization's data governance, security, and responsible AI practices when pursuing a generative AI transformation.
GeekSpoc is a 20+ person software development and IT consulting company with over 16 years of experience. They work with clients of all sizes in India, the Middle East, US, and Europe. Their services include IT consulting, web development, mobile app development, business app development, ERP software, digital marketing, IT recruitment, and outsourcing. GeekSpoc uses both agile and traditional development methodologies depending on the project. They aim to provide technical excellence, be client focused, and have high performance teams.
Infotachus Pvt Ltd is an IT solutions provider with over 15 years of experience in project management and software development. They offer a full range of services including web and app development, digital marketing, cloud computing, AI/ML, and quality assurance testing. Their team of skilled professionals aims to help clients succeed by delivering innovative and customized solutions. They have offices in Noida, India and Vancouver, Canada and serve clients across various industries.
Eque2 offers integrated business management software tailored for construction and contracting companies. Their software streamlines estimating, financials, project management and other business functions. They invest heavily in research and development to ensure their solutions, which are often based on Microsoft and Sage technologies, benefit from continuous improvements. Eque2 has over 1,200 customers, many of whom have been using their software for decades, and their industry experts provide support to help customers efficiently manage their businesses.
This document offers an overview of the 6-month ZIGRAM internship program which is meant for those candidates and individuals who wish to get aligned and trained in Data Assets related skills and technologies.
Empowering Industries with Artificial Intelligence Solutions. At byteLAKE, we harness cutting-edge technology to provide advanced quality inspection and data insights tailored for the Manufacturing, Automotive, Paper, Chemical, and Energy sectors. Additionally, we offer self-checkout stations for Restaurants and object recognition solutions for Retail businesses.
Explore our featured products:
► byteLAKE's CFD Suite: Accelerate your Computational Fluid Dynamics (CFD) simulations by leveraging the speed and efficiency of artificial intelligence. Slash simulation times, minimize trial-and-error costs, and supercharge decision-making for heightened productivity. Learn more at www.byteLAKE.com/en/CFDSuite.
► byteLAKE's Cognitive Services: Unlock the full potential of Industry 4.0 with our comprehensive suite of AI solutions.
• Manufacturing: Employ image analytics for precise visual inspection of processes, parts, components, and products, ensuring impeccable quality control and minimizing errors. Learn more at www.byteLAKE.com/en/manufacturing.
• Automotive: Harness sound analytics to assess and analyze the quality of car engines, enabling proactive maintenance and preventing potential issues. Discover more at www.byteLAKE.com/en/automotive.
• Paper Industry: Implement advanced cameras to continuously monitor the papermaking process, accurately detecting and analyzing the wet line. Optimize production, reduce waste, and enhance efficiency. Explore further at www.byteLAKE.com/en/paper.
• Data Insights: Leverage our AI module for advanced predictive maintenance, detecting risky situations and triggering alarms. Seamlessly turn data from various sources (IoT sensors, documents, online weather forecasts, etc.) into actionable information for better decisions. Learn more at: www.byteLAKE.com/en/DataInsights.
• Restaurants / Retail: Simplify and expedite the checkout process with our solution for self-checkout stations. Our AI module can recognize meals and groceries effortlessly, sending the list directly to the cashier's machine for efficient self-checkout. Shorten queues and wait times, elevating customer satisfaction. Learn more at www.byteLAKE.com/en/AI4Restaurants.
Experience the future of AI-driven excellence. Discover more about byteLAKE's Cognitive Services at www.byteLAKE.com/en/CognitiveServices.
► Custom AI Software Development: Choose from our range of AI services, including AI Workshops with inspiring case studies and insights, Edge AI for real-time analytics on images, videos, sounds, and time-series data, Cognitive Automation for the automation of complex tasks with software robots, and HPC for algorithm optimization across various CPU, GPU, and FPGA architectures.
► Incubation: Explore our innovative product brainello, an AI-powered document processing software that works without templates, and Ewa Guard, AI for Drones enabling large area visual analytics.
The 10 Most Admired Analytics Companies to Watch in 2018Merry D'souza
We introduce “The 10 Most Admired Analytics Companies to Watch in 2018”, in order to assist businesses to choose their right analytics companies. Assessing the scenario in versatile perceptions, our magazine has brought light onto the companies, who have flaunted excellence in providing technologically advanced analytics solutions. This list showcases the analytics companies which are creating a better ‘Analytics’ world.
The 10 Most Admired Analytics Companies to Watch in 2018Merry D'souza
"We introduce “The 10 Most Admired Analytics Companies to Watch in 2018”, in order to assist businesses to choose their right analytics companies. Assessing the scenario in versatile perceptions, our magazine has brought light onto the companies, who have flaunted excellence in providing technologically advanced analytics solutions. This list showcases the analytics companies which are creating a better ‘Analytics’ world."
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
We are a team of technology leaders and engineers with passion and single-minded focus on providing efficient and robust Information Technology solutions for clients across the globe.
We are extremely passionate about our work that keeps us agile and makes us who we are. We help each other and work together to make Ejyle a great workplace.
Skoder Technologies provides technical support and services to help entrepreneurs turn their ideas into successful businesses. It offers startup development, software solutions, web and mobile app development, and other advanced technologies. Skoder has multiple affiliates that provide services such as branding, media, venture capital connections, and training to help clients innovate and succeed.
QueBIT is a trusted expert in business analytics. They help organizations apply analytics to key functions to improve performance. QueBIT uses a collaborative approach to implement customized analytics solutions tailored for each client. Their solutions and expertise span data management, business intelligence, and advanced analytics. This allows clients to gain insights from their data to make better decisions and outperform competitors.
This document provides a summary of key strategies for successfully scaling artificial intelligence (AI) within an organization. It discusses the importance of having a clear business strategy that AI supports, focusing AI projects on delivering tangible business value. It also emphasizes having the right data strategy to power AI initiatives and taking a portfolio view of AI projects that balances experimentation with alignment to strategic goals. The document recommends challenging assumptions about how work gets done and preparing employees for how AI will change and augment their roles. It argues that organizations must think holistically about scaling AI to realize its full potential for driving business outcomes.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsAggregage
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
Moving to the Cloud: Artificial Intelligence in Cloud-Based SolutionsNicolas Rodriguez
With the advent of chatbots, artificial intelligence, interactive voice response, and machine learning, novel technologies continue to disrupt the contact center industry. These advances initially gave the impression that automation will replace the human element. Join Rick Nucci, Co-Founder and CEO of Guru, as he demystifies AI, explains how machine learning helps contact centers rather than replaces them, and demonstrates how to leverage this new technology to create innovative solutions.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Easily Verify Compliance and Security with Binance KYCAny kyc Account
Use our simple KYC verification guide to make sure your Binance account is safe and compliant. Discover the fundamentals, appreciate the significance of KYC, and trade on one of the biggest cryptocurrency exchanges with confidence.
IMPACT Silver is a pure silver zinc producer with over $260 million in revenue since 2008 and a large 100% owned 210km Mexico land package - 2024 catalysts includes new 14% grade zinc Plomosas mine and 20,000m of fully funded exploration drilling.
Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Structural Design Process: Step-by-Step Guide for BuildingsChandresh Chudasama
The structural design process is explained: Follow our step-by-step guide to understand building design intricacies and ensure structural integrity. Learn how to build wonderful buildings with the help of our detailed information. Learn how to create structures with durability and reliability and also gain insights on ways of managing structures.
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
HOW TO START UP A COMPANY A STEP-BY-STEP GUIDE.pdf46adnanshahzad
How to Start Up a Company: A Step-by-Step Guide Starting a company is an exciting adventure that combines creativity, strategy, and hard work. It can seem overwhelming at first, but with the right guidance, anyone can transform a great idea into a successful business. Let's dive into how to start up a company, from the initial spark of an idea to securing funding and launching your startup.
Introduction
Have you ever dreamed of turning your innovative idea into a thriving business? Starting a company involves numerous steps and decisions, but don't worry—we're here to help. Whether you're exploring how to start a startup company or wondering how to start up a small business, this guide will walk you through the process, step by step.
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
How to Implement a Real Estate CRM SoftwareSalesTown
To implement a CRM for real estate, set clear goals, choose a CRM with key real estate features, and customize it to your needs. Migrate your data, train your team, and use automation to save time. Monitor performance, ensure data security, and use the CRM to enhance marketing. Regularly check its effectiveness to improve your business.
How to Implement a Strategy: Transform Your Strategy with BSC Designer's Comp...Aleksey Savkin
The Strategy Implementation System offers a structured approach to translating stakeholder needs into actionable strategies using high-level and low-level scorecards. It involves stakeholder analysis, strategy decomposition, adoption of strategic frameworks like Balanced Scorecard or OKR, and alignment of goals, initiatives, and KPIs.
Key Components:
- Stakeholder Analysis
- Strategy Decomposition
- Adoption of Business Frameworks
- Goal Setting
- Initiatives and Action Plans
- KPIs and Performance Metrics
- Learning and Adaptation
- Alignment and Cascading of Scorecards
Benefits:
- Systematic strategy formulation and execution.
- Framework flexibility and automation.
- Enhanced alignment and strategic focus across the organization.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
Company Valuation webinar series - Tuesday, 4 June 2024FelixPerez547899
This session provided an update as to the latest valuation data in the UK and then delved into a discussion on the upcoming election and the impacts on valuation. We finished, as always with a Q&A
Income Tax exemption for Start up : Section 80 IAC
Jalgos - Playbook
1.
This is the Jalgos Playbook
Dive into our
A.I.-Native Company.
This playbook offers an overview of how we conduct great AI innovation projects and how we
run our company.
This document is for everyone to read, from clients to future hires or anyone interested in how
to work with AI the Jalgos way.
Choose a topic and dive into our world of data, algorithms and innovation.
A big thanks to our partners at French Bureau for inspiring this Playbook!
Jalgos Playbook 2017
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Introducing: Jalgos 5
Our Mission 5
Advocates for Good A.I. 5
What we do 5
The value we add 6
How we do it 7
Data strategy 7
Transplanting algorithms 8
Phase 1 - Explore 8
Phase 2 - Adapt 8
Phase 3 - Productify 8
What we care about 9
Deliverables 9
Training 10
What we expect from our clients 11
The Jalgos way 11
Our ever-evolving toolbox 12
Our views on AI and its impact 14
AI & ethics 14
AI & society 14
AI & organisations 15
How to work with us 16
First contact 16
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Data security & confidentiality 16
Intellectual property 16
Billing 17
What it’s like to work with us 18
The Jalgos spirit 18
Innovator mindset 18
Team work 18
Technological agnosticism 18
How, when, and where we work 19
The sandbox 19
Our tools of choice 19
Building AI startups of our own 20
New Hires 21
The Jalgos type 21
Hiring process 21
Onboarding & continuous learning 21
Introductory training (for technical hires) 21
Continuous learning 22
Research project 22
Salary & equity 22
Say hi! 23
Jalgos Playbook 2017
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Introducing: Jalgos
Our Mission
We are an AI & data studio dedicated to innovation for large corporations, startups,
governments and organisations.
We are a team of high-end experts in AI, data, and strategy. Thanks to both our entrepreneurial
and researcher mindset we bridge the gap between R&D and business to make you benefit
from the tremendous opportunities offered by AI, in a fast and reliable way.
Our mission is to bring AI and data-powered strategy to our clients to place them at the
forefront of innovation in their sector.
Advocates for Good A.I.
As algorithm specialists, we are striving for good AI and we contribute our best to building it.
In our day to day work with our clients and partners, we take pride in:
- scientific rigor, not algorithmic hacking;
- creating real business values for customers, employees and business owners;
- thinking for the long term, on reliability, and continuous innovation;
- evangelising about the opportunities and consequences of AI.
Alongside our client work, we design and develop our own research and AI products to solve
the most interesting questions we find.
What we do
Our goal is to leverage cutting-edge AI research to solve real-world problems for our
clients, bringing algorithmic solutions and data awareness to organisations.
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We fulfill this mission through 3 main activities:
● The “Workshop” is where the deep work happens, where we thoroughly analyse data
for our clients, build and adapt algorithms, design dashboards and visualisations and
store our products until we find new opportunities for them to bring value to
organisations. Projects are typically a few months in duration, at the end of which we
deliver a working prototype and full documentation.
● The “Strategic Office” is dedicated to advising, auditing and training our clients. We
work on data and AI strategy, and we provide general, data-powered strategic
consulting. We also create high-level content that we publish and push towards
governments and organisations in order to promote our convictions on AI and its
consequences.
● The “Studio” - This is an AI-powered startup launcher dedicated to exploring new
market opportunities for our technologies and expertise, to test, create and accelerate
new businesses with our partners.
The value we add
The core value we bring you is to bridge the gap between two worlds: AI research and
innovation on one hand, and business strategy, growth and development on the other.
Jalgos’ raison d’être is the belief that by bringing algorithmic mastery to business, we can
generate high impact innovation with a strong ROI in short time spans.
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How we do it
We develop, refine and are constantly testing sound methodologies for rapidly transforming AI
research into efficient and durable algorithmic products. The whole process, from strategic
consulting and exploration to a working product, typically takes 4 to 8 months, depending on
the complexity of the data and the problem at hand.
Data strategy
We are convinced that AI will become critical to virtually all business sectors in the coming
years. At the same time successful AI projects or large-scale AI transitions have to reflect each
company’s culture, business, and value proposition. Not the other way around - even as
algorithms bring deep changes in organisations and value creation.
● We help you define the most relevant strategy for embracing AI and data in your
business, both short and long term.
● We audit your current data strategy, architecture and processes and recommend the
best way to level up.
● We identify all the data sources inside your systems, outside your systems, data
creation, gathering and collection opportunities.
● We design, plan and price the most efficient course of action to make the best out of
AI technologies.
Our hybrid backgrounds, as both accomplished data scientists and seasoned consultants, will
bring you the best of both worlds.
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Transplanting algorithms
This is the core of what AI innovation is about, and we know how to do it best.
Phase 1 - Explore
This is where it all starts, always.
Data exploration is as much about data science as it is about understanding the field of
application of the nascent algorithm. Along with data cleaning, we interact with the data
through using our methods and toolbox, and with subject matter experts, using precise
documentation and clear visualisation.
The output of going back and forth between signal and interpretation leads to finding key
actionable insights and reaching a deep understanding of the internal structure of the data and
the useful information it contains.
It is this information that will be automatically detected and harnessed by the final algorithm.
Phase 2 - Adapt
Once signal is extracted from the data, we go to our algorithmic shelves to find the most
relevant algorithm to deploy on the data, and solve the problem at hand, whether it is about
prediction, optimisation, matching, identification, etc.
After a period of testing and improvement, the prototype’s internal motor is ready.
Phase 3 - Productify
This phase is about enabling the algorithm to interact with our clients’ teams, and with our
clients’ data. It is all about UX design, data visualisation, and data management.
Our designers work hand-in-hand with our clients to define the perfect interface, and give
direct, visual access to the algorithm’s output and underlying data. Our data engineers make
interaction with the database and the system seamless - be it through deployment to our
clients’ environment or hosted on our platform.
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What we care about
● Authenticity & rigor: We are experts who know business, and we take pride in creating
sound solutions that bring the most value to our clients.
● Design: Our algorithms, documentation and solutions come with great UX design and
visualisations, to make interactions natural and information clear and direct.
● Transparency: Our no-black-box policy is not just about giving you information about
what happens in our products, it is also about absolute efficiency, scientific excellence
and long term reliability. We provide you with detailed documentation of what we do
and how we do it, to enable you to properly interpret our algorithms’ output.
● Skill transfer: Acculturation and what we call a data mindset are key for an algorithm’s
real world success. Such adaptation takes time, this is why we work on it from the very
start, and dedicate time for skill transfer to our clients’ teams all along the way.
● Long term: We think and build our products keeping in mind that they will have to
evolve, and serve as the foundation of future products and services. We care for long
term reliability and adaptability as much as we care about quick prototyping.
Deliverables
Many things happen during the course of a full 4 to 8 months mission, and we give our client as
much information about these as possible.
From a business problem to a working algorithmic solution, we deliver a lot along the way, to
create value early on and prepare for integrating our solution to our clients’ teams from the
kick-off.
● Strategy and architecture: We deliver comprehensive and well-designed reports from
start to finish. We present our strategic and technical recommendations to our clients,
as well as the findings, goals, and thought processes that lead us there. All our reports
are well-designed and illustrated in order to convey our ideas and technical
specifications in an easy-to-understand way.
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● Technical, readable documentation: The path that starts with data exploration and
culminates in a working prototype is extremely rich in key insights, findings, new ideas
emerging from the data, but also hypotheses, trials, and technical choices. Gathering all
this in well designed comprehensive reports not only has tremendous value for our
clients, it is also a requirement for long term success in data transformation, and one of
the ways we demonstrate our attention to detail.
● Interactive dashboards: Thanks to our designers, we transform data into intuitive
visualisations, and results into clear interactive dashboards. We co-construct our
dashboards and visualisations with our clients to give them direct contact with data and
a flawless UX to interact with our algorithms.
● The prototype: The product itself. Functional, adapted to your constraints and goals, we
can host it on our servers or help your IT team integrate it in your own environment. We
also provide you with a technical and functional documentation to fully empower your
use of it.
● Skill and knowledge transfer: In addition to pure quality of the product and
documentation, we know for a fact that acculturation, skill and knowledge transfers are
critical success factors for data and AI projects or transitions. From the very start of our
missions, we dedicate ourselves to prepare our clients’ teams to integrate the future
algorithm and to acquire a data and AI mindset. In addition to our frequent and
comprehensive documentation, this is done through regular meetings and in-depth
exchanges about the budding tool.
Training
What your business needs, even more than data scientists, is managers with a sound insight
into data and algorithm related questions. They must be able to interact with data science
teams while keeping a high level view on strategy and business.
With all the humility required in perpetually evolving fields in, we train C-suite members,
managers and consultants to the principles of AI, data science and modelling. We provide the
tools that allow them to integrate the opportunities offered by data and AI in their strategic
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thinking, as well as to manage, challenge and interact efficiently with technical teams. Our
training programmes are designed to be accessible to non-specialists.
We have also built extensive technical training, that we offer internally for the onboarding of
new recruits.
What we expect from our clients
Our methodology for innovation in AI and data grants us great autonomy. We work from our
own offices, on our machines, and the minimal involvement we expect from our clients is the
following:
● Gather the stakeholders inside the organisation and through a written discussion thread,
in order to make communication easy and transparent
● Read the weekly or bimonthly documentation we provide, and attend conference calls
the day after in order to exchange information and feedback.
This is the bare minimum that we expect even from very busy clients. For more involved ones,
we welcome clients to our offices on a regular basis to dive deeper into our methodology and
participate actively in our working sessions.
The Jalgos way
Our AI innovation method takes its inspiration from many academic, entrepreneurial, industrial
and personal sources. Among the key ideas that support the Jalgos way, here are the most
important to us:
● Model thinking: Models are the basis of all scientific analysis and innovation, whether
powered by data or not. It is the fundamental way we can make sense of the world and
frame discussions. Using model thinking as exposed for example by Scott E. Page
enables us to quickly dive into complex fields previously unknown to us. Without
becoming specialists, it allows us to rapidly bring sound innovation through algorithms.
● Rapid prototyping: Very early in the process, we start sketching the UX and designing
the internal logic of the prototype we will build using AI algorithms. This allows us to
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precisely understand the needs and constraints of the future final users of the product,
while we dig deeply into the data and the precious information it holds. This makes our
innovation process fast and reliable.
● Scientific rigor: The need to go fast and the appeal of out-of-the-box algorithms makes
algorithmic hacking over proper R&D tempting for some, but not us. We created Jalgos
with the strong belief that data science and AI innovation requires, even more than
other fields, highly rigorous scientific methodology in order to create durable and
powerful innovation. Not “wow factor” hacks that will disappoint or backfire in the
mid-term. We all have strong scientific backgrounds, centred on modelling, and we
apply this rigor to our development, analyses and innovation in order to serve our clients
best in the short and long term.
● Unwavering optimism: Boldness and optimism are at the core of a successful
innovator’s attitude. We love what we do, and we make it a point to pass our enthusiasm
and passion on to our clients’ teams.
Our ever-evolving toolbox
We dedicate at least 30% of our time to designing and developing algorithmic libraries and
bricks with which we can build fast and sound solutions. The outputs of all this fundamental AI
R&D work, started years ago, is our evolving toolbox, that covers a wide range of applications,
from parallel and distributed computing to algebraic operations. We pick the most relevant
bricks and algorithmic engines on our shelves for each application, and adapt them so they fit
perfectly to the constraints. Thanks to this ongoing work, we can offer both fast and cutting
edge algorithmic products to our clients.
As we embrace the open source model of part of our work, we want to give back and are
opening parts of our toolbox to the community.
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Our views on AI and its impact
We do not limit our activity to developing tomorrow's algorithms and putting them in the hands
of our clients. We are also very conscious of and passionate about the deep consequences that
our field will have on many aspect of our lives. We dedicate time and effort to refine our own
views on the issue, and to share them in conferences, articles, or through awareness sessions.
The topic is endless and algorithms are expected to impact every aspect of our lives - they
already do in many ways - so we have selected a few areas where we find that the challenges
particularly compelling.
AI & ethics
Free will and the right to privacy are just two aspects of who we are that are being deeply
influenced by algorithms, and are expected to be threatened if we do not properly anticipate
the consequences of what we do with AI.
Furthermore, extensive delegation of decisions, including life and death ones, and the creation
of illusions of empathy and sensitivity in machines raises questions about our identity and what
should and shouldn’t be done. We are convinced these questions should be studied deeply and
shared in public forums as early as today. This is critical for building the good AI and future we
aspire to.
AI & society
The growing impact of algorithms on the job market ought to be anticipated properly in order
to manage it up front.
Furthermore, the way algorithms already influence how we consume information, and thus
how we think and vote, needs an in-depth analysis in order to address the negative
consequences of their involvement. We are actually building a set of tools internally that aim at
fighting the cognitive bias caused by recommendation engines, and more generally at enriching
the way we read and get informed online.
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Finally, algorithms open interesting opportunities, to refine the way we think about state,
politics and social norms, along with risks. We encourage and advise public figures to dive into
these questions in order to make the most and the best out of these innovations.
AI & organisations
Algorithms are all about detecting, managing, harnessing and communicating information in
order to enable the people that constitute them to accomplish their mission. This is exactly
what organisations are also about. The coming of AI is already having an important impact on
internal processes, in addition to the expected replacement of some of today’s jobs. These
questions are crucial for all types of organisations, and we are convinced they should be
addressed seriously without delay, which is why we raise awareness and advise organisations
on the matter.
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How to work with us
First contact
First contact is all about deciding if we are both enthusiastic about working together on data
and AI innovation projects. We’ve defined - and are constantly refining - our offering so that it
is most valuable for our clients, by taking the best of both R&D and consulting. We do not try to
sell a single one size-fits-all product. And we do not stop at proofs-of-concept. We always start
by presenting the way we work and why we are convinced of its value, so you know what to
expect from working with us.
At this early stage, we will identify with you the main processes and opportunities related to
data and algorithms in within your business. We will articulate the business question(s) and
technical challenges, and our proposition to solve them.
Data security & confidentiality
Security is our primary concern when it comes to data and information in general. Our highly
secured data setup has successfully passed an in-depth audit for hosting data with military
grade and national interest confidentiality requirements. We take pride in continuing to exceed
security requirements. In addition to data protection and security, secrecy is also deeply rooted
in the way we interact inside the company itself. Access to information and data is defined on a
case by case, need-to-know basis, and we stringently keep track of it.
Intellectual property
Everything that is produced during the mission belongs de facto to our clients. When a project
consists in adapting one of our existing products, an IP transfer or other agreement is defined
between us and the client after a trial phase.
Once a prototype or full product is delivered, the client may choose to:
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- Keep the IP for himself to continue the project internally or just use the product as is
- Transfer us the IP in exchange for a share in a startup launched through our Studio
Billing
Our billing model is pretty simple:
For projects shorter than two months we bill 50% at the beginning of the assignment and 50%
when we deliver the final result. For work longer than two months, we bill 30% at the
beginning, 30% in the middle, and 40% at the end.
We’ll expect you to pay us promptly, cashflow is key for startups!
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What it’s like to work with us
The Jalgos spirit
Innovator mindset
An innovator mindset is a subtle mix of strong optimism and enthusiasm, humility, intellectual
honesty, directness, and imagination. We foster all of these within our team and the way we
interact.
We encourage kind and straightforward communication, respectfully and without ambiguity.
Thus we expect everybody to challenge anybody, without being hindered by hierarchy. And to
always communicate keeping in mind our shared goals, discovering new ways to solve big
problems with our minds and tools.
Team work
Jalgos is first and foremost about building and nurturing a team of passionate people that
enjoy working and spending time together, to create the very best in AI innovation. We foster
teamwork; working alone on a project is a no go with us. We know it is more efficient and more
fun to exchange ideas and share progress and questions with partners. We also set aside time
for our AI retreats, during which we leave our day-to-day lives to spend up to a week in a nice
destination, work on a prototype of ours and have fun. Our last outing was in Greece!
Technological agnosticism
While many people stick to talking about database technologies and languages when they
discuss data and AI, we consider the diversity of technologies available as an evolving toolbox
from which we can pick the best. That being said, we have our favorites, and most of the time
we develop in R and C++, and usually use MongoDB for our database needs. But we also use
Python, Javascript, Java, Scala, or any other language or database technology when needed.
We’re polyglot, we just learn what’s appropriate when it’s relevant.
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How, when, and where we work
Our typical working day is from 9am to 7pm and these times are a guide for when we may
schedule meetings. But each team member can structure their day in the way that best suits
them, as long as it is compatible with teamwork. Even if the workload is heavier on occasions,
workdays should not be consistently longer than this, or we would take it as a sign a problem to
be resolved. We care for work done and managing maintaining stamina, not time spent
working.
Being in the same location when working together is something that is both efficient and fun.
It’s our preferred setup, and what we we expect when we welcome you to the team. That being
said, we are flexible concerning remote work, and after the onboarding phase is passed, anyone
can work remotely when needed.
The sandbox
Our tools of choice
We don’t have fixed beliefs about the best tool, the best algorithm, or the best technology. It
just does not work that way. That being said, there are a few internal tools we love and that
help us stay efficient and nimble.
● Slack: It’s our favorite internal tool; basically all internal communication flows through
our channels. All our communicating are on Slack in a dedicated channel for each topic,
integrated with other tools such as Gitlab, in order to be able to follow and keep track of
everyone’s work and progress. These habits are also what enables us to work remotely
sometimes, with almost no loss of efficiency.
● Gitlab: Git is a no-brainer when it comes to handling coding projects, and that’s what we
do all the time. We set up a Gitlab instance on our servers and every line of code that is
ever written gets into it.
● R with data.table: While we quite often use other languages and many other libraries, R
and data.table work as the very basis of our analytics build up. It’s fast, well
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implemented, and the syntax is close to our mathematicians’ way of thinking about data.
What else would we want? Distributed data.table? We built it.
● Shiny, Rmarkdown & ggplot2: They are our basic go-to solutions when it comes to
presenting results, documenting what we do, and building interactive interfaces. The
freedom, simplicity and speed these solutions offer are what we need to have amazing
design quickly, even if we also go for other tools when relevant.
● Google Drive: For everything that’s about sharing information and documents, we use
google drive for its simplicity.
● GMail: We limit the use of email to external communication, so that our inboxes stay
nice. Slack takes care of the rest.
● Our loyal supercomputers: Last but not least, we need our powerful servers to run our
computations in reasonable time. They are hosted by OVH, our provider of choice when
it comes to reliability, security, and quality of service.
Building AI startups of our own
When we are not working on client missions, we build our own algorithms to solve the
problems wecare about.
Any team member can choose an idea she wants to realise, and form a team to work on it.
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New Hires
The Jalgos type
We only look for the best: smart, insightful, self-starters, passionate and generous team
players.
Hiring process
The hiring process starts with a short conversation by phone - or a physical meeting if you’re
around - with two of us. If it fits, the real process starts and you’ll be invited to meet the
founders and be tested more deeply on your technical skills and motivation.
We only hire permanently (CDI) and through an internship that we expect will lead to a
contract. We don’t see any reason for temporary contracts once trust is established.
Onboarding & continuous learning
Introductory training (for technical hires)
Being hired is just the beginning of what we hope will be a fun and exciting adventure.
● Technical profiles: Even if you are a data science specialist or computer scientist, you’ll
start by going through our dedicated internal training programme alongside with your
first assignments. This will make you become operational, and go from someone who
knows data science or computer science to someone who can use it relevantly and
rigorously Jalgos-style.
● Business & strategy profiles: Along with your first assignments, you will also get
in-depth non-technical training about data strategy, algorithms, and AI direct from our
founders. The training will help you understand precisely what we do, how we do it, and
how it can be applied and adapted to solve our clients’ challenges.
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Continuous learning
Once the onboarding phase is complete, we never stop learning. We organise weekly
presentations about a data science subject, where one of us usually presents an interesting
mathematical theory or algorithm to the team. We discuss it afterwards and identify if and how
it could become part of our stack and projects.
We also maintain a dynamic and kind atmosphere where we encourage everybody to challenge
each other and to share the knowledge each has so that the team grows as a whole.
Research project
Each one of us gets a more long-term research and development project when joining the
team. In addition to being intellectually exciting, it is also one of the ways we maintain a
research-oriented mindset. You are fully responsible of your project, but you’re encouraged to
share it with team members for discussion. You’ll be helped, challenged and managed by our
founders.
The main criterion for choosing your research subject is that you find it fun!
Our research mindset and associated projects extend beyond our data scientists, to our
computer scientists, designers and business profiles alike.
These projects, in addition to their intrinsic value, are also a very efficient way to have all of us
build powerful libraries, clever methodologies and write high-impact articles.
Salary & equity
Our salaries are solely based on level of experience, regardless of field of expertise or any other
factor. We make a point of paying our people fairly. We want great people in, so we consider it
fair to reward them accordingly.
In addition, variable compensation is distributed every year to the team depending on a
collective appreciation of each one’s performance.
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Every member receives equity in the form of options when joining the team. The amount
depends on the risk taken (the age and size of the company when joining) and the position in
the company.
Say hi!
Let’s bring AI to the world together.
Drop us a message: data@jalgos.com
Our playbook is provided under the terms of a Creative Commons public
license, share it!
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