Sumyag Insights provides data science and analytics services. They have a diverse team of over 15 data scientists and engineers with expertise in areas like machine learning, natural language processing, computer vision, and IoT. Their solutions include data wrangling, predictive modeling, prescriptive analytics, and building custom applications and dashboards. They follow an agile approach with sprints and focus on rapid prototyping to provide quick insights and business value to clients in industries like banking, insurance, retail, and manufacturing.
This document discusses opportunities for using big data in private wealth management. It begins by defining big data and describing how data volumes have increased exponentially. It then outlines several potential use cases for big data in areas like real-time performance metrics, portfolio optimization, and leveraging customer data. For each use case, it describes current limitations and how a big data approach could enable new capabilities. Finally, it proposes a phased approach for wealth managers to identify use cases, prioritize them, implement proofs of concept, and incrementally automate analysis and reporting. The overall message is that big data can enhance analytics and open up new opportunities previously only available to investment banks.
The webinar discussed how time series databases can create value by enabling organizations to profit from digital shifts related to applications, customer engagement, IoT, and globalization. Time series data is growing significantly due to IoT and is crucial for monitoring devices and infrastructure. The webinar covered how time series data and analysis can provide insights for customer retention and experience, high frequency trading and transactions, and global applications like solar energy monitoring.
A Journey Through The Far Side Of Data Sciencetlcj97
This document summarizes a presentation on data science and artificial intelligence. It discusses how AI is transforming businesses in many ways, including automating repetitive tasks, improving customer experiences, and driving revenue growth. It also mentions that while data is important, AI is needed to transform organizations through intelligent process optimization and innovation. The document provides examples of how various companies are applying AI in sales, customer service, and other areas. It emphasizes that AI strategies should focus on innovation, identifying high-impact use cases, and developing people's data science skills.
Visualization, Mobility and Analytical ReportingPatrick Spedding
Still over-reliant on Excel for reporting? Difficult to get access to the information you need to make informed decisions?
Most organisations now recognise the danger of relying too heavily on "gut feel" when it comes to making critical business decisions.
With emerging capabilities such as data visualisation, mobile devices and analytical reporting, now is the time to re-evaluate how information is consumed within your organisation.
Join us for this complementary event, and hear how companies such as ComSuper, CUA, American Express and others use Business Intelligence to support fact-based, decision-making and analytical reporting. Breakfast included.
AI Microservices APIs and Business Automation as a Service Denis GagneDenis Gagné
My presentation at the BBC2019 conference.
While the current AI fascination is fueled by Machine Learning, the architecture and application landscape is being redesigned around Microservices and APIs. These technologies are combining forces to affect many facets of business, creating a paradigm shift all around you. Do you know how to take advantage of the tsunami created by these technologies?
In this session, we will explain these technologies and how to extract business value from them. We will demonstrate how line of business people can integrate machine learning into business decisions that are explainable, auditable, and traceable and how they can easily assemble business automations that orchestrate a series of microservices via modern API platforms. With this knowledge in hand, you will be ready to face the next wave of technologies that are hitting your organization.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-tschudi
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yohann Tschudi, Technology and Market Analyst at Yole Développement, presents the "AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?" tutorial at the May 2019 Embedded Vision Summit.
Artificial intelligence is proliferating into numerous edge applications and disrupting numerous industries. Clearly this represents a huge opportunity for technology suppliers. But it can be difficult to discern exactly what form this opportunity will take. For example, will edge devices perform AI computation locally, or in the cloud? Will edge devices use separate chips for AI, or will AI processing engines be incorporated into the main processor SoCs already used in these devices?
In this talk, Tschudi answers these questions by presenting and explaining his firm's market data and forecasts for AI processors in mobile phones, drones, smart home devices and personal robots. He explains why there is a strong trend towards executing AI computation at the edge, and quantifies the opportunity for separate processor chips and on-chip accelerators that address visual and audio AI tasks.
Building the Future of Monitoring with Artificial IntelligenceIncedo
Incedo Inc is an artificial intelligence and technology firm that has experienced strong growth since its inception in 2011, growing from 1500 employees to over 671% in size. The company provides specialized product engineering and data analytics services with a focus on emerging technologies. Incedo has experience using machine learning and natural language processing for applications in various industries like monitoring industrial equipment, developing chatbots for customer service, and creating diagnostic services for connected vehicles.
This document discusses opportunities for using big data in private wealth management. It begins by defining big data and describing how data volumes have increased exponentially. It then outlines several potential use cases for big data in areas like real-time performance metrics, portfolio optimization, and leveraging customer data. For each use case, it describes current limitations and how a big data approach could enable new capabilities. Finally, it proposes a phased approach for wealth managers to identify use cases, prioritize them, implement proofs of concept, and incrementally automate analysis and reporting. The overall message is that big data can enhance analytics and open up new opportunities previously only available to investment banks.
The webinar discussed how time series databases can create value by enabling organizations to profit from digital shifts related to applications, customer engagement, IoT, and globalization. Time series data is growing significantly due to IoT and is crucial for monitoring devices and infrastructure. The webinar covered how time series data and analysis can provide insights for customer retention and experience, high frequency trading and transactions, and global applications like solar energy monitoring.
A Journey Through The Far Side Of Data Sciencetlcj97
This document summarizes a presentation on data science and artificial intelligence. It discusses how AI is transforming businesses in many ways, including automating repetitive tasks, improving customer experiences, and driving revenue growth. It also mentions that while data is important, AI is needed to transform organizations through intelligent process optimization and innovation. The document provides examples of how various companies are applying AI in sales, customer service, and other areas. It emphasizes that AI strategies should focus on innovation, identifying high-impact use cases, and developing people's data science skills.
Visualization, Mobility and Analytical ReportingPatrick Spedding
Still over-reliant on Excel for reporting? Difficult to get access to the information you need to make informed decisions?
Most organisations now recognise the danger of relying too heavily on "gut feel" when it comes to making critical business decisions.
With emerging capabilities such as data visualisation, mobile devices and analytical reporting, now is the time to re-evaluate how information is consumed within your organisation.
Join us for this complementary event, and hear how companies such as ComSuper, CUA, American Express and others use Business Intelligence to support fact-based, decision-making and analytical reporting. Breakfast included.
AI Microservices APIs and Business Automation as a Service Denis GagneDenis Gagné
My presentation at the BBC2019 conference.
While the current AI fascination is fueled by Machine Learning, the architecture and application landscape is being redesigned around Microservices and APIs. These technologies are combining forces to affect many facets of business, creating a paradigm shift all around you. Do you know how to take advantage of the tsunami created by these technologies?
In this session, we will explain these technologies and how to extract business value from them. We will demonstrate how line of business people can integrate machine learning into business decisions that are explainable, auditable, and traceable and how they can easily assemble business automations that orchestrate a series of microservices via modern API platforms. With this knowledge in hand, you will be ready to face the next wave of technologies that are hitting your organization.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-tschudi
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yohann Tschudi, Technology and Market Analyst at Yole Développement, presents the "AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?" tutorial at the May 2019 Embedded Vision Summit.
Artificial intelligence is proliferating into numerous edge applications and disrupting numerous industries. Clearly this represents a huge opportunity for technology suppliers. But it can be difficult to discern exactly what form this opportunity will take. For example, will edge devices perform AI computation locally, or in the cloud? Will edge devices use separate chips for AI, or will AI processing engines be incorporated into the main processor SoCs already used in these devices?
In this talk, Tschudi answers these questions by presenting and explaining his firm's market data and forecasts for AI processors in mobile phones, drones, smart home devices and personal robots. He explains why there is a strong trend towards executing AI computation at the edge, and quantifies the opportunity for separate processor chips and on-chip accelerators that address visual and audio AI tasks.
Building the Future of Monitoring with Artificial IntelligenceIncedo
Incedo Inc is an artificial intelligence and technology firm that has experienced strong growth since its inception in 2011, growing from 1500 employees to over 671% in size. The company provides specialized product engineering and data analytics services with a focus on emerging technologies. Incedo has experience using machine learning and natural language processing for applications in various industries like monitoring industrial equipment, developing chatbots for customer service, and creating diagnostic services for connected vehicles.
How to analyze text data for AI and ML with Named Entity RecognitionSkyl.ai
About the webinar
The Internet is a rich source of data, mainly textual data. But making use of huge quantities of data is a complex and time-consuming task. NLP can help with this problem through the use of Named Entity Recognition systems. Named entities are terms that refer to names, organizations, locations, values etc. NER annotates texts – marking where and what type of named entities occurred in it. This step significantly simplifies further use of such data, allowing for easy categorization of documents, analyze sentiments, improving automatically generated summaries etc.
Further, in many industries, the vocabulary keeps changing and growing with new research, abbreviations, long and complex constructions, and makes it difficult to get accurate results or use rule-based methods. Named Entity Recognition and Classification can help to effectively extract, tag, index, and manage this fast and ever-growing knowledge.
Through this webinar, we will understand how NER can be used to extract key entities from large volumes of text data
What you will learn
- How organizations are leveraging Named Entity Recognition across various industries
- Live demo - Identify & classify complex terms & with NERC (Named Entity Recognition & Categorization)
- Best practice to automate machine learning models in hours not months
This document provides examples of how service-oriented architecture (SOA) and cloud computing can be applied in the life sciences industry. It discusses four key focus areas - federated cloud architecture, composable services, security, and governance. It then provides four examples: 1) a safety assessment portal that consolidates safety documents, 2) a clinical data repository that harmonizes data standards, 3) an investigator research center portal that enables collaboration between sponsors and sites, and 4) a clinical supply chain concept that tracks investigational products. The examples illustrate how SOA and cloud can help address industry challenges and create reusable services.
Entry Points – How to Get Rolling with Big Data AnalyticsInside Analysis
The Briefing Room with Robin Bloor and IBM
Live Webcast Sept. 24, 2013
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?AT=pb&SP=EC&rID=7501927&rKey=664935ceb7de1aec
Where to begin? That question remains prominent for many organizations who are trying to leverage the value of big data analytics. Most sources of big data are quite different than traditional enterprise data systems. This requires new skill sets, both for the granular integration work, as well as the strategic business perspective required to design useful solutions.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains the pain points associated with modern data volumes and types. He will be briefed by Rick Clements of IBM, who will tout IBM's big data platform, specifically InfoSphere BigInsights, InfoSphere Streams and InfoSphere Data Explorer. He will also present specific use cases that demonstrate how IT and the line of business can springboard over existing challenges, gain insight and improve operational performance.
Visit InsideAnalysis.com for more information
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.
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017StampedeCon
This document discusses AI in the enterprise from past, present, and future perspectives. It provides an overview of the history and recent developments in AI and deep learning, including improved performance on tasks like image recognition. Case studies are presented showing how various large companies have successfully applied deep learning techniques like convolutional neural networks to problems in different industries involving computer vision, predictive maintenance, fraud detection, and more. The importance of data quantity for deep learning performance is highlighted. The final sections discuss challenges in AI adoption and the importance of piloting models before full production deployment.
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017StampedeCon
This talk will walk through the important building blocks of Automated AI. Rajiv will highlight the current gaps in the analytics organizations, how to close those gaps using automated AI. Some of the issues discussed around automated AI are the accuracy of models, tradeoffs around control when using automation, interpretability of models, and integration with other tools. These issues will be highlighted with examples of automated analytics in different industries. The talk will end with some examples of how automated AI in the hands of data scientists and business analysts is transforming analytic teams and organizations.
FORFIRM is a FINTECH consulting company with clients in European market answering real business challenges for our clients through innovation and deep industry knowledge.
In 2018 "European Innovation Management Academy", based on "House of Innovation" framework by A.T. Kearney " analyzed over 3000 digital companies around Europe scoring FORFIRM at the TOP in terms of Innovation strategy, Organization and culture of innovation, life cycle and Enabler factor.
Big data is generated from a variety of sources like web data, purchases, social networks, sensors, and IoT devices. Telecom companies process exabytes and zettabytes of data daily, including call detail records, network configuration data, and customer information. This big data is analyzed to enhance customer experience through personalization, predict churn, and optimize networks. Analytics also helps with operations, data monetization through services, and identifying new revenue streams from IoT and M2M data. Frameworks like Hadoop and MapReduce are used to analyze this distributed big data across clusters in a distributed manner for faster insights.
Engaging Your CFO in Business Analytics | Palestrante: Celso Chapinottesucesuminas
The document discusses the changing role of the CFO and importance of business analytics. It finds that CFO influence over IT investments is increasing as they seek to optimize performance and costs. Most CFOs believe IT should report to them. Business intelligence, analytics, and performance management are seen as top technology priorities and ways to address needs like measuring profitability and monitoring performance. The presentation recommends understanding the evolving CFO focus, enabling the CFO through technology, and improving the CFO-CIO relationship through communication and viewing projects as business rather than IT projects.
Gartner has identified the top 10 strategic technology trends for 2014. Take a look ahead at the strategic trends that have high potential to disrupt IT or the business in the next three years. Discover the technologies that may require major financial investments and the ones you cannot afford to miss.
The document discusses the challenges facing CIOs in managing a "two-speed IT" environment where there is both traditional stable IT (Mode 1) and new digital innovative IT (Mode 2).
Some key points:
- Mode 1 IT focuses on stability and efficiency while Mode 2 focuses on agility and innovation to drive new business opportunities.
- This creates differing cultures, skills requirements, metrics, and ways of working between the two modes that can cause issues.
- A large portion of IT spending is now outside of the CIO's direct control as business units directly purchase new digital technologies.
- Pricing models, vendor relationships, contracts, and skills needed are very different between traditional
HPE - "‘Software Defined’ Infrastructure, zeg je? Noem het ‘Generatie Z’ van ...VITO - Securitas
This document discusses hybrid IT infrastructure and how IT is evolving to support new workloads and intelligent data processing. It provides examples of how optimal hybrid IT infrastructure can support Internet of Things use cases. Specifically, it discusses using examples in areas like asset monitoring, location services, security and surveillance, and remote presence to illustrate how hybrid IT can intelligently process data.
This document discusses big data and analytics. It notes that digital data is growing exponentially and will reach 35 zettabytes by 2020, with 80% coming from enterprise systems. Big data is being driven by increased transaction data, interaction data from mobile and social media, and improved processing capabilities. Major players in big data include Google, Amazon, IBM and Microsoft. Traditional analytics struggle due to batch processing and lack of business context. The document introduces OpTier's approach of capturing real-time business context across interactions to enable insights with low costs and flexibility. Potential use cases for financial services are discussed.
Software-Defined Supply Chain: The Next Industrial RevolutionLeonard Lee
Presentation of the Software-Defined Supply Chain that provides a point of view on the transformative potential of 3D printing, advanced robotics, and open source electronics hardware on manufacturing and supply chain as we know it today. This presentation was delivered to the CSCMP (Council of Supply Chain Management Professionals) on September 17, 2013.
The document summarizes an inaugural event hosted by Intel on business intelligence on the cloud. The event included sessions on Intel's cloud strategy, what BI on the cloud is, cloud computing for BI/DW, big data appliances, DW infrastructure for cloud, a business perspective on cloud for BI, and the transformational impact of cloud on DW/BI. There were also presentations on advanced analytics on the cloud and a closing keynote. The event aimed to discuss how cloud computing is changing the landscape for business intelligence and data warehousing.
Big Data LDN 2018: A LOOK INSIDE APPLIED MACHINE LEARNINGMatt Stubbs
Date: 13th November 2018
Location: Data-Driven Ldn Theatre
Time: 13:10 - 13:40
Speaker: Brian Goral
Organisation: Cloudera
About: The field of machine learning (ML) ranges from the very practical and pragmatic to the highly theoretical and abstract. This talk describes several of the challenges facing organisations that want to leverage more of their data through ML, including some examples of the applied algorithms that are already delivering value in business contexts.
1. The document discusses the shift from goods to services as the predominant part of economies and how innovation in services is changing.
2. It describes how services innovation requires a focus on customer experience, collaboration both inside and outside organizations, and new business models.
3. The document outlines different types of services innovation including business model innovation and provides a framework for services innovation involving multi-disciplinary collaboration.
This document provides a summary of Mayank Joshi's personal and professional details. It includes his contact information, education history, languages spoken, technical skills, and employment history working for various companies as a senior software engineer and developer specializing in Java, data analytics, AI/ML, and related technologies. His roles have involved designing and developing applications, analyzing data, and working on agile teams to implement new features.
The document discusses artificial intelligence (AI) and Capgemini's approach to AI. It provides examples of how AI can be applied in different industries and business functions. It also outlines Capgemini's AI platform, principles, and offerings. Capgemini aims to help clients implement impactful and scalable AI solutions through a combination of technology, services, and ecosystem partnerships.
How to analyze text data for AI and ML with Named Entity RecognitionSkyl.ai
About the webinar
The Internet is a rich source of data, mainly textual data. But making use of huge quantities of data is a complex and time-consuming task. NLP can help with this problem through the use of Named Entity Recognition systems. Named entities are terms that refer to names, organizations, locations, values etc. NER annotates texts – marking where and what type of named entities occurred in it. This step significantly simplifies further use of such data, allowing for easy categorization of documents, analyze sentiments, improving automatically generated summaries etc.
Further, in many industries, the vocabulary keeps changing and growing with new research, abbreviations, long and complex constructions, and makes it difficult to get accurate results or use rule-based methods. Named Entity Recognition and Classification can help to effectively extract, tag, index, and manage this fast and ever-growing knowledge.
Through this webinar, we will understand how NER can be used to extract key entities from large volumes of text data
What you will learn
- How organizations are leveraging Named Entity Recognition across various industries
- Live demo - Identify & classify complex terms & with NERC (Named Entity Recognition & Categorization)
- Best practice to automate machine learning models in hours not months
This document provides examples of how service-oriented architecture (SOA) and cloud computing can be applied in the life sciences industry. It discusses four key focus areas - federated cloud architecture, composable services, security, and governance. It then provides four examples: 1) a safety assessment portal that consolidates safety documents, 2) a clinical data repository that harmonizes data standards, 3) an investigator research center portal that enables collaboration between sponsors and sites, and 4) a clinical supply chain concept that tracks investigational products. The examples illustrate how SOA and cloud can help address industry challenges and create reusable services.
Entry Points – How to Get Rolling with Big Data AnalyticsInside Analysis
The Briefing Room with Robin Bloor and IBM
Live Webcast Sept. 24, 2013
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?AT=pb&SP=EC&rID=7501927&rKey=664935ceb7de1aec
Where to begin? That question remains prominent for many organizations who are trying to leverage the value of big data analytics. Most sources of big data are quite different than traditional enterprise data systems. This requires new skill sets, both for the granular integration work, as well as the strategic business perspective required to design useful solutions.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains the pain points associated with modern data volumes and types. He will be briefed by Rick Clements of IBM, who will tout IBM's big data platform, specifically InfoSphere BigInsights, InfoSphere Streams and InfoSphere Data Explorer. He will also present specific use cases that demonstrate how IT and the line of business can springboard over existing challenges, gain insight and improve operational performance.
Visit InsideAnalysis.com for more information
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.
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017StampedeCon
This document discusses AI in the enterprise from past, present, and future perspectives. It provides an overview of the history and recent developments in AI and deep learning, including improved performance on tasks like image recognition. Case studies are presented showing how various large companies have successfully applied deep learning techniques like convolutional neural networks to problems in different industries involving computer vision, predictive maintenance, fraud detection, and more. The importance of data quantity for deep learning performance is highlighted. The final sections discuss challenges in AI adoption and the importance of piloting models before full production deployment.
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017StampedeCon
This talk will walk through the important building blocks of Automated AI. Rajiv will highlight the current gaps in the analytics organizations, how to close those gaps using automated AI. Some of the issues discussed around automated AI are the accuracy of models, tradeoffs around control when using automation, interpretability of models, and integration with other tools. These issues will be highlighted with examples of automated analytics in different industries. The talk will end with some examples of how automated AI in the hands of data scientists and business analysts is transforming analytic teams and organizations.
FORFIRM is a FINTECH consulting company with clients in European market answering real business challenges for our clients through innovation and deep industry knowledge.
In 2018 "European Innovation Management Academy", based on "House of Innovation" framework by A.T. Kearney " analyzed over 3000 digital companies around Europe scoring FORFIRM at the TOP in terms of Innovation strategy, Organization and culture of innovation, life cycle and Enabler factor.
Big data is generated from a variety of sources like web data, purchases, social networks, sensors, and IoT devices. Telecom companies process exabytes and zettabytes of data daily, including call detail records, network configuration data, and customer information. This big data is analyzed to enhance customer experience through personalization, predict churn, and optimize networks. Analytics also helps with operations, data monetization through services, and identifying new revenue streams from IoT and M2M data. Frameworks like Hadoop and MapReduce are used to analyze this distributed big data across clusters in a distributed manner for faster insights.
Engaging Your CFO in Business Analytics | Palestrante: Celso Chapinottesucesuminas
The document discusses the changing role of the CFO and importance of business analytics. It finds that CFO influence over IT investments is increasing as they seek to optimize performance and costs. Most CFOs believe IT should report to them. Business intelligence, analytics, and performance management are seen as top technology priorities and ways to address needs like measuring profitability and monitoring performance. The presentation recommends understanding the evolving CFO focus, enabling the CFO through technology, and improving the CFO-CIO relationship through communication and viewing projects as business rather than IT projects.
Gartner has identified the top 10 strategic technology trends for 2014. Take a look ahead at the strategic trends that have high potential to disrupt IT or the business in the next three years. Discover the technologies that may require major financial investments and the ones you cannot afford to miss.
The document discusses the challenges facing CIOs in managing a "two-speed IT" environment where there is both traditional stable IT (Mode 1) and new digital innovative IT (Mode 2).
Some key points:
- Mode 1 IT focuses on stability and efficiency while Mode 2 focuses on agility and innovation to drive new business opportunities.
- This creates differing cultures, skills requirements, metrics, and ways of working between the two modes that can cause issues.
- A large portion of IT spending is now outside of the CIO's direct control as business units directly purchase new digital technologies.
- Pricing models, vendor relationships, contracts, and skills needed are very different between traditional
HPE - "‘Software Defined’ Infrastructure, zeg je? Noem het ‘Generatie Z’ van ...VITO - Securitas
This document discusses hybrid IT infrastructure and how IT is evolving to support new workloads and intelligent data processing. It provides examples of how optimal hybrid IT infrastructure can support Internet of Things use cases. Specifically, it discusses using examples in areas like asset monitoring, location services, security and surveillance, and remote presence to illustrate how hybrid IT can intelligently process data.
This document discusses big data and analytics. It notes that digital data is growing exponentially and will reach 35 zettabytes by 2020, with 80% coming from enterprise systems. Big data is being driven by increased transaction data, interaction data from mobile and social media, and improved processing capabilities. Major players in big data include Google, Amazon, IBM and Microsoft. Traditional analytics struggle due to batch processing and lack of business context. The document introduces OpTier's approach of capturing real-time business context across interactions to enable insights with low costs and flexibility. Potential use cases for financial services are discussed.
Software-Defined Supply Chain: The Next Industrial RevolutionLeonard Lee
Presentation of the Software-Defined Supply Chain that provides a point of view on the transformative potential of 3D printing, advanced robotics, and open source electronics hardware on manufacturing and supply chain as we know it today. This presentation was delivered to the CSCMP (Council of Supply Chain Management Professionals) on September 17, 2013.
The document summarizes an inaugural event hosted by Intel on business intelligence on the cloud. The event included sessions on Intel's cloud strategy, what BI on the cloud is, cloud computing for BI/DW, big data appliances, DW infrastructure for cloud, a business perspective on cloud for BI, and the transformational impact of cloud on DW/BI. There were also presentations on advanced analytics on the cloud and a closing keynote. The event aimed to discuss how cloud computing is changing the landscape for business intelligence and data warehousing.
Big Data LDN 2018: A LOOK INSIDE APPLIED MACHINE LEARNINGMatt Stubbs
Date: 13th November 2018
Location: Data-Driven Ldn Theatre
Time: 13:10 - 13:40
Speaker: Brian Goral
Organisation: Cloudera
About: The field of machine learning (ML) ranges from the very practical and pragmatic to the highly theoretical and abstract. This talk describes several of the challenges facing organisations that want to leverage more of their data through ML, including some examples of the applied algorithms that are already delivering value in business contexts.
1. The document discusses the shift from goods to services as the predominant part of economies and how innovation in services is changing.
2. It describes how services innovation requires a focus on customer experience, collaboration both inside and outside organizations, and new business models.
3. The document outlines different types of services innovation including business model innovation and provides a framework for services innovation involving multi-disciplinary collaboration.
This document provides a summary of Mayank Joshi's personal and professional details. It includes his contact information, education history, languages spoken, technical skills, and employment history working for various companies as a senior software engineer and developer specializing in Java, data analytics, AI/ML, and related technologies. His roles have involved designing and developing applications, analyzing data, and working on agile teams to implement new features.
The document discusses artificial intelligence (AI) and Capgemini's approach to AI. It provides examples of how AI can be applied in different industries and business functions. It also outlines Capgemini's AI platform, principles, and offerings. Capgemini aims to help clients implement impactful and scalable AI solutions through a combination of technology, services, and ecosystem partnerships.
IBM Solutions Connect 2013 - Getting started with Big DataIBM Software India
You've heard of Big Data for sure. But what are the implications of this for your organisation? Can your organisation leverage Big Data too? If you decide to go ahead with your Big Data implementation where do you start? If these questions sound familiar to you then you've stumbled upon the right presentation. Go through the presentation to:
a. Learn more on Big data
b. How Big data can help you outperform in your marketplace.
c. How to proactively manage security and risk
d. How to create IT agility to underpin the business
Also, learn about IBM's superior Big Data technologies and how they are helping today's organisations take smarter decisions and actions.
This document provides an overview of a proposed "Superdata Solution" or "Command Center" to help various personas within an organization better access and utilize data. It describes current challenges around isolated data solutions and proposes consolidating different data sources onto a centralized data platform to provide self-serve data and insights. Key aspects of the proposed solution include a data lake, data marts, orchestration services, data transformation/ML tools, and serving data through dashboards, APIs and reports to help business users, developers and other teams.
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTXtsigitnist02
This document provides instructions for using a presentation deck on Cloud Pak for Data. It instructs the user to:
1. Delete the first slide before using the deck.
2. Customize the presentation for the intended audience as the deck covers various topics and using all slides may not fit a single meeting.
3. The deck contains 6 embedded video records for a demo that takes 15-25 minutes to present. Guidance on pitching the demo is available.
The appendix contains slides on Cloud Pak for Data licensing and IBM's overall strategy.
LoQutus helps organisations to innovate with analytics and to get insights with data visualisation. We also build large scale data layers to enable interaction with core data, and develop data-driven applications to deliver the insights our customers need. During this session we’ll share what we have learned along the way. We’ll show you our framework for self-service analytics & insights, and some successful case studies.
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.
Artificial intelligence is becoming a hot topic due to recent advances in hardware capabilities, neural networks research, and technology investments. Deep learning is driving this resurgence by using neural networks with multiple layers to interpret nonlinear relationships in high-dimensional data. Deep learning is delivering improved performance on complex problems and creating value with little domain knowledge required. The presentation provides examples of AI applications in industries like banking, automotive, and healthcare. It also outlines steps to get started with an AI pilot project and developing an AI strategy and roadmap.
Happiest Minds have worked extensively with Industrial and Manufacturing companies to provide customized and value rich IoT consulting and product assessment services. Our comprehensive tools and frameworks combined with our talent rich pool of IoT consultants have helped shape the IoT journeys of our customers.
The document provides a summary of Sharada Papanaidu's experience and qualifications. She has over 15 years of experience leading IT teams and implementing business intelligence solutions using SAP technologies. Currently she is a SAP BI Lead at Microfocus International, a global software company, where she has led SAP FI, PTP, BI, and BPC implementations. Previously she held SAP BI leadership roles at NetIQ, which is now part of Microfocus, where she implemented BI solutions for CRM and led development teams. She has extensive experience designing, developing, testing, and supporting SAP BI, BW, BEx, BObj, and BPC applications.
Bhadale group of companies data science project methodologies catalogueVijayananda Mohire
This is our offering for data science project methodologies. We offer our expertise in transforming your enterprise for the next big data revolution for Data science project
Four Key Considerations for your Big Data Analytics StrategyArcadia Data
This document discusses considerations for big data analytics strategies. It covers how big data analytics have evolved from focusing on structured data and batch processing to also including real-time, multi-structured data from various sources. It emphasizes that discovery is key and requires visual exploration of granular data details. Native big data analytics platforms are needed that can handle real-time streaming data and provide self-service capabilities through customizable applications. The document provides examples of how various companies are using big data analytics for applications like cybersecurity, customer analytics, and supply chain optimization.
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
Learn ABC Again – Analytics and Business Intelligence on Cloud provides an overview of the evolution of business intelligence and analytics from the 1980s to present day. It discusses how business intelligence has shifted from on-premise implementations to cloud-based solutions that allow for greater collaboration, mobility, and real-time access to data. The document also introduces SmartPrise BI Suite, a cloud-based business intelligence product that offers features such as single interface access to reports, role-based security, and access to both structured and unstructured data.
CIO priorities and Data Virtualization: Balancing the Yin and Yang of the ITDenodo
Watch here: https://bit.ly/3iGMsH6
Today’s CIOs carry a paradoxical responsibility of balancing the yin and yang of the Business – IT interface. That is, "Backroom IT’s quest for Stability" with the “Frontline Business’ need for Agility".
A paradox that is no longer optional, but is essential. A paradox that defines the business competitiveness, business survival, and business sustainability. Also enables the visibility to the fuzzy future.
“Trusted Data Foundation with Data Virtualization” provides a powerful ammunition in the hands of the CIO, to effectively balance these Yin and Yang at the speed of the business. In a trusted, compliant, auditable, flexible and regulated fashion.
Find out more on how you can enhance the competitive edge for your business in the CIO special webinar from COMPEGENCE and DENODO.
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalHarvinder Atwal
Title
DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed.
Synopsis
● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure.
● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities.
● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product.
● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills.
● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products.
● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.
BizLogic Infosystems Pvt. Ltd. is an information technology firm dedicated to business success through long-term relationships with our clients and staff. Based in India, Business Logic (BizLogic Infosystems Pvt. Ltd.) is a dynamic, service-oriented enterprise, and is positioned to successfully respond to trends and changes in the information technology industry.
These slides—based on the on-demand webinar hosted by leading IT analyst firm Enterprise Management Associates (EMA) and Confluent –examines how business and technology leaders are adopting streaming strategies and how the world of streaming data implementations have changed for the better.
This document provides a summary of the book "Sri Sankara" by ShankaraNarayanan. It discusses Sankara's life and philosophy in 7 chapters. The key points are:
1. Sankara was born in Kerala, India in the 5th century AD to a Brahmin family. He had several spiritual experiences from a young age and became a sannyasi at a young age.
2. As a philosopher, he traveled throughout India debating scholars of other schools and establishing the doctrine of Advaita Vedanta. He wrote commentaries on the principal Upanishads, Bhagavad Gita, and Brahma Sutras.
3. S
My read and summarization of the booklet on devops by mike loukides from O Reilly, great read for starters.. a good reference on automation, inreastructure as code
1) There is a growing gap in capabilities and performance between companies that invest heavily in data and analytics compared to those that invest less. The capability gap is exacerbated by a shortage of analytical talent.
2) The amount of data being created is growing exponentially, estimated at 2.5 quintillion bytes per day globally. However, most organizations are not effectively using the data they already have.
3) Investing in analytics can provide significant financial benefits across industries. For example, leveraging big data in healthcare could capture $300 billion annually and increase retailers' operating margins by 60%.
Tom Davenports Classic on hwo to Build Organizations of Knowledge workers, around talent Management, Information and Managerial Hygiene.. great reference for managers
Read in 2011, a very foundational book on physics, narrated in a very easy lay-man terms.. This book talks about constants, in nature and how we need to interpret and listen to these constants..
These are my book notes, great book one can buy this book on Amazon... worth a read for science buffs
In 2011 i read this wonderful book from the found of IDEO Tom Kelley, on how to manage and inculcate innovation.. this book was a precursor for the book ten faces of Innovation
A personal collection of HR concepts through training sessions attended.. highlights.. Areas like Presentations, Leadersdhip, Influencing, Interviews .. etc...
This document provides a summary of the life and works of Adi Sankara based on various biographical accounts. It discusses Sankara's birthplace in Kaladi, key milestones in his life like upanayana at age 5 and completing Vedic studies by age 7. It outlines his works like bhashyas on 11 Upanishads and Brahma Sutras. It also mentions his debates with Mandana Misra and establishment of the Sankara Mathas. In the end, it discusses the relevance of Advaita philosophy propounded by Sankara in modern times for inner peace and overcoming challenges like fear and depression.
This document discusses concepts from Hinduism as presented by DevDutt Pattnaik. It is organized into 18 chapters based on the Mahabharata war and discusses themes of householders, hermits, different perspectives of truth and the self, the five layers of existence, and issues with some historical narratives. It also briefly mentions swastikas representing the four beings of elements, plants, animals, and humans.
The document discusses the growing importance and opportunities of analytics for businesses. It notes that there is a widening performance gap between top performers and bottom performers in their use of data and analytics. While the amount of data is growing exponentially, there is also a significant skills gap in having enough talent to effectively analyze and use data. The document outlines several major themes where businesses are applying analytics, including customer insights, risk management, operations, and product design. It argues that analytics can drive significant business value when integrated into operations and transformations.
This document provides summaries of various Android apps for news, maps, fitness tracking, finance, communications, and productivity. It discusses the key features and alternatives for apps like Flipboard, Google Maps, MyTracks, iMobile, WhatsApp, and Evernote. For each app, it briefly describes the app's main purpose and functionality, and then lists 2-3 other similar apps as alternatives. The document aims to help readers choose from different options for popular app categories on Android.
The document provides an overview of Six Sigma, which is a philosophy and methodology for process improvement. It aims to reduce defects and variability in processes by measuring defects, focusing on areas for improvement, and setting a target of 3.4 defects per million opportunities. Six Sigma has helped companies like GE, Motorola, HP and American Express achieve significant cost savings and quality improvements through systematic efforts to measure processes, identify sources of defects, and continuously improve performance. The principles of Six Sigma can also be seen in small organizations like the Mumbai Tiffinmens Association, which delivers lunches with only one defect per 17.5 million opportunities through cultural emphasis on quality, measurement and continuous improvement.
UCF framework presented to a large IT service company in Mumbai in 2008.. showing my thinking then on how an organization could approach organization capability recording and building.. related to PCMMI.
Morey stettner wrote a very practical guide for managers, do surely read it.. this is my prime reference for managing my teams at work.. the presentation is a precis of that book and the key principles resident there..
The document discusses three skills that are important for an effective executive:
1. Conceptual skills - The ability to understand complex situations and see the big picture. This includes skills like strategic thinking, problem solving, and decision making.
2. Human skills - Skills for motivating, communicating with, and developing people. This involves skills like leadership, team building, and coaching.
3. Technical skills - Expertise in a specific business function like finance, marketing, or operations. While not as important as conceptual and human skills, technical skills are still needed for credibility.
This document discusses the importance of design and innovation in developing new dimensions and business models. It outlines an iterative design process that involves early prototyping and user feedback to develop deep user understanding. Case studies are presented of how design was used at Target Pharma to improve prescription bottles, at Boeing to transform their workplace culture, and at Pfizer to reframe communication around Viagra to increase patient-doctor dialogue. The process involves understanding user activity, multi-prototyping with feedback, and considering use in broader contexts to drive breakthrough innovation.
Anticipatory Failure Determination <afd> is a method similar to FMEA in design, to extract and discover failures in design ad how to cope and manage these risks.
Robert Katz identified 3 key skills for effective executives:
1) Conceptual skills - seeing the big picture and understanding complex relationships between different parts of an organization.
2) Human skills - understanding other people, communicating effectively, and motivating others.
3) Technical skills - having expertise in a specific business or management function. Effective executives draw from all 3 skills depending on the situation.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
The Evolution and Impact of OTT Platforms: A Deep Dive into the Future of Ent...ABHILASH DUTTA
This presentation provides a thorough examination of Over-the-Top (OTT) platforms, focusing on their development and substantial influence on the entertainment industry, with a particular emphasis on the Indian market.We begin with an introduction to OTT platforms, defining them as streaming services that deliver content directly over the internet, bypassing traditional broadcast channels. These platforms offer a variety of content, including movies, TV shows, and original productions, allowing users to access content on-demand across multiple devices.The historical context covers the early days of streaming, starting with Netflix's inception in 1997 as a DVD rental service and its transition to streaming in 2007. The presentation also highlights India's television journey, from the launch of Doordarshan in 1959 to the introduction of Direct-to-Home (DTH) satellite television in 2000, which expanded viewing choices and set the stage for the rise of OTT platforms like Big Flix, Ditto TV, Sony LIV, Hotstar, and Netflix. The business models of OTT platforms are explored in detail. Subscription Video on Demand (SVOD) models, exemplified by Netflix and Amazon Prime Video, offer unlimited content access for a monthly fee. Transactional Video on Demand (TVOD) models, like iTunes and Sky Box Office, allow users to pay for individual pieces of content. Advertising-Based Video on Demand (AVOD) models, such as YouTube and Facebook Watch, provide free content supported by advertisements. Hybrid models combine elements of SVOD and AVOD, offering flexibility to cater to diverse audience preferences.
Content acquisition strategies are also discussed, highlighting the dual approach of purchasing broadcasting rights for existing films and TV shows and investing in original content production. This section underscores the importance of a robust content library in attracting and retaining subscribers.The presentation addresses the challenges faced by OTT platforms, including the unpredictability of content acquisition and audience preferences. It emphasizes the difficulty of balancing content investment with returns in a competitive market, the high costs associated with marketing, and the need for continuous innovation and adaptation to stay relevant.
The impact of OTT platforms on the Bollywood film industry is significant. The competition for viewers has led to a decrease in cinema ticket sales, affecting the revenue of Bollywood films that traditionally rely on theatrical releases. Additionally, OTT platforms now pay less for film rights due to the uncertain success of films in cinemas.
Looking ahead, the future of OTT in India appears promising. The market is expected to grow by 20% annually, reaching a value of ₹1200 billion by the end of the decade. The increasing availability of affordable smartphones and internet access will drive this growth, making OTT platforms a primary source of entertainment for many viewers.
How MJ Global Leads the Packaging Industry.pdfMJ Global
MJ Global's success in staying ahead of the curve in the packaging industry is a testament to its dedication to innovation, sustainability, and customer-centricity. By embracing technological advancements, leading in eco-friendly solutions, collaborating with industry leaders, and adapting to evolving consumer preferences, MJ Global continues to set new standards in the packaging sector.
B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
buy old yahoo accounts buy yahoo accountsSusan Laney
As a business owner, I understand the importance of having a strong online presence and leveraging various digital platforms to reach and engage with your target audience. One often overlooked yet highly valuable asset in this regard is the humble Yahoo account. While many may perceive Yahoo as a relic of the past, the truth is that these accounts still hold immense potential for businesses of all sizes.
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
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
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.
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.
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujarat’s DholeraAvirahi City Dholera
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isn’t just any project; it’s a potential game changer for India’s chipmaking aspirations and a boon for investors seeking promising residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
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.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
The Influence of Marketing Strategy and Market Competition on Business Perfor...
Sumyag profile deck
1. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 1
SUMYAGInsights
Prescient Data and Data Science Services
2. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 2
Sumyag Insights
Sumyag Insights – Solutions
DataStreaming,IOTSensors,Datapipeline,
DataWrangling,DataQuality
PatternAnalysis,AnomalyDetection
Prescience– ExtractValuefrom databefore
Model & Insights
Text, NLP and knowledgeGraphs- Sentiment
Sumyag has a diverse set of products which can be applied to a wide range of businesses with very specific outcomes. Our products
help customers get maximum value out of structured and unstructured data
Insight
generation
Data
Prescience
Text
Processing
Advanced
Models
DATA SCIENCE – BIG DATA DIGITAL – AUTOMATION IOT – SOLUTIONS
Web and MobileApplications
RPA, Automationsolutions
User Experience andDesign
DesignSprintWorkshops
Hack-a-thonevents for Rapid Development
ProductManagementandAgiledelivery
IOT SensorsandlocationbasedControllers
Cloudbased Web Services and API
ML & AI basedintelligenceonaudio,Images
and log –streams
Web based Bi – Dashboards
Digital playoutsatlocationfor user interaction
and nudgepropagation
3. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 3
Sumyag Insights
Data Science – Use Case Retail Smart Store IOT
Business First: Prescience + Framework + Curation
Analytics As-A-Service
Data + Wrangling +Modeling + ML
R, R-Studio, Python, Python-
notebook, Spark , Hadoop –MR,
HIVE, Hbase, Postgres-SQL, Talend,
OpenRefine
Agile – Iteration
India Advantage =Skill , Thrift, Cost
4. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 4
Sumyag Insights
Analytics Services Model
Capabilities, Applications Mapping & Target Clients
The following capabilities and opportunities can be addressed for retail clients through theSUMYAG association
Data Prescience Sand-box.
Engineer, Wrangle, Characterize
Text /Doc Processing pdf, eml,
Doc, vectors, Entity models, Apps
Image Classification CNN, GAN X
Facial. Emotions. attention
Specialty Applications IOT –
Invisiblecustomer [<10% footfalls
convert into sales ]
Entity Research public
information ++generate insights on
entities like companies.
Business analytics Customer
Analytics , Market basket, Next Best
Actions, Segmentation and affinity
Capabilities Application Areas Potential Targets
Prescience Automation
Data Curation & Pre-Science
Technology Familiriaty
Spark,Kafka, Hadoop, Hive,
TensorFlow, Hbase, Python, R,
D3, Node.js, Storm,
ML. Advanced models
UnStructured data NLP, Text,
Images, Video, Voice
Agile Delivery
Outcomes at speed & Cost
Iterate. Co-Create. Outcome
Virtual COE
Confluence of strategy, Change,
DevOps, Cloud, Digital,
Analytics in the right Quanta
Startup Mindset
Build. Measure. Learn. Scale
Multiple domains, solve fast,
and nimbly
Lea d
Skill A Skill B
Skill C Skill D
Peers & Reports
Public Data
Standards
Knowledge Base
Lea d
Skill A Skill B
Skill C Skill D
Peers & Reports
Public Data
Standards
Knowledge Base
Banking-Finance
Risk Analytics, Co-Research,
Customer Management
INSURANCE
Claims, Customer
Management, Risk & Pricing
RETAIL
Smart store networks,
Content. Interact. Insights
5. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 5
Sumyag Insights
Understand what makes Customer Tick,
Profile - customer behaviour and demographics
Complex web of data –mobile, social media, transaction data
Deliver - Customer Retention, Customer profiling and Segmentation,
Cross Sell and Upsell to Customers, & Customer lifetime value
Customer
Management
Pricing & Risk
Management
Targeted pricing based on segments, Customer credit risk analysis, fraud
protection, discounttargeting. Life time Risk Value, Actuarial Riskand
compliance
Process
Optimization
Triaging and STP in Process, Skill based allocation, Understanding
Machines, Devices and Human Interactions
Marketing &
Brand Mgmt.
Single view of the customer, Market Basket & Mix Analysis, Brand Spend
Management, Web clickstream Analysis, leading to better positioning ,
targeting and brand Spend and thereby next best action for the customer
Supply Chain
Optimization
, Industrial Monitoring and Failure Prediction. Inventoryand Logistics
optimization. Capacityplanning & Demand mgmt
Banking Insurance Retail MFG - CG
Use Cases & Business Application
6. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 6
Why Sumyag?
THOUGHT PARTNER
• Digital – IOT – Data Science
• Insurance. Banking, Retail
• Operations Management
• Right Technology Mix
• Data Pipeline / prescience
• Text – Document Structuring
• NLP / Semantics
• IOT – Digital – Insights
• Network / eco-system of skills
• Work on all leading platforms
• Strong Data Science
• Insights thru Code
• Research / POC
• Agile Iterative Organization &
Delivery
• Relationship Driven Execution
• Offshore vCOE delivery Model
Experienced
Leadership
Product
Innovation
Technology
Networks
Flexibility
8. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 8
Sumyag Insights
Typical Data Science SandBox - Technical Architecture
9. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 9
High Level Architecture
Principles of Design
9
Business Domain
» Simplicity > Driven by Business Needs , not over
featuring. Prioritise the most relevant
» Traceability > Transparency > Intuitive Reporting[
logging, traces, interim states ] [ LHR = RHR ]
» Interactive > Focus on intuitive design for users
minimal effort / learning interfaces using digital
Engineering
» Abstraction: Avoid Hardcoding enhance Flexibility ,
De-Couple processingbetweensystems,stateless
» Data Driven Intelligence > use Data based
configuration to make systemadapt to new
requirements
» Algorithmic Process > Noise Cancellation, [eg]
» Re-usability > modular, re-use within and for outside
use-cases
» Interoperability > standards based data and state
interchange
» Maintainability > easy to manage and sustain
Environment
» Cloud > Prefer cloud deployment
» Cost Optimization > long term low cost, through
standard simple infrastructure,re-use
» Tech-Debt > Avoid techobsolescence throughuse of
prevalent, non-proprietary frameworks
Execution
» Agile –Framework. Fixed time Frame, Manifesto
» Use Case - Business driven , focus on requirements
» Iterative > Feedback Driven , quick and learn fast
» Balanced Term > Short Term + long Term
10. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 10
SUMYAG Insights
Team and profiles
11. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 11
Sumyag Insights
Milind [Data Sci]
Technologist with 16 years of experience in
Infrastructureand firmwaredesign. Milind
has been leading Data science initiatives for
the past 3 years in AIG and currently in the
startups that hehas founded. Milind has
worked with brands like AIG, VMWare.
Milind consults on data center design,
Model Engineering and Validation and
designing insights for theenterprise.
Manish [ Org Change]
Manish brings 20+years of experience in
Agile, Lean transformationhaving worked
with WIPRO and other organizations.
Consults on Self Development
workshops, ChangeManagement,
Disruptiveinnovation
Sudip [Digital – Java]
21 Yrs. Of experience in Management
Consulting, Delivery and Innovation
expertise. Proficiency in Retail, Airlines,
Hospitality and Capital Markets.
Consults Strategy, Optimizations, Product
Management and Digital Transformation.
Aims at bringing valuedriven innovation
and transformation through Digital and
emerging technologies.
Data Science
Sumyag Insights our sister firm
forms the talent pool andservices
arm for Data Science,Digital and IOT.
The team is currently7resources
with a networkpool of10+
resources
Digital –Web Apps
SumyagInsights has tiedup
companiesthat bringDigital we b
development capabilities at scale,
and this will be led by Venkyand
Sudip
DEVOPS
SunyagInsightshas signed up 2
companieswith deep resource pools
for DevOps Maintenance and
Infrastructure Management
Sanjay [ Process Change]
18 Yrs. of experience in IT consulting, ITIL
implementation, program management,
transition management, and quality
assurance.
Worked in Defense,BFSI,Auto,and
Energy& Climate Change areas.
ConsultedCIOs and CXOs on IT
operations andbusinessservice
management.
Graduatein Mechanical Engineering.
Sandeep [Process Change ]
12 Yrs. of experience in developing and
implementing valuebased strategic
initiatives in various industries to improve
human and process performance. Played
COO role in e-commerce and IP licensing
industries.
Post Graduatein Management with
graduation in Engineering.
Venkat [ IO T – Firmware ]
21 years experience in deep embedded
and firmwareengineering for hardware
and electronics solutions for IOT and
industrial purposes. Venkat has worked as
the Lead product engineering at Ingersoll
Rand for the past 13 years.
Venkat has been a technology evangelist
and consults on Agile, Product Innovation,
IoT – Technology Strategy, Coaching
Our Team of Senior Leaders
Cumulatively bring 150 Y of experience across the top leaders in the organization
12. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 12
Sumyag Insights
Data Science , Technologists
Abhishek K
Lead Data Scientist with 4 years
Experience
Work: Facial Detection & Emotional
Analysis,NLP Framework, PDF
Vectorisation, Deep Learning frameworks
Areas: Collibra, REST services , Text
Processing & Mining
Skills: Python, Unix, Collibra, Statistics,
Groovy, JavaScript, HTML5, CSS
Clients: Walmart, AIG, Icicle
Mukesh K
8 years experience in Java, Hadoop, Data
Work: Engineering, & Microservices.
Engineer data scientist. Currently
working on Master Data Management,
NLP Platform using Tika, UIMA. GLobal
Data Sync. for Best Buy. Big Data -
marketplace in AIG
Areas: NLP - Text processing, TIKA -
UIMA, Auto data Characterization
Skills: Web Software using Java, Micro-
services, Restful - bootstrap, Agile,
DevOps, hadoop - Eco System
Clients: Sapient, AIG, IBM, Bestbuy,
Nestle
Umesh K
7 years Data Science & Advanced
Analytics
Work: Insurance Customer Insights, Text
Processing Engine ,Enterprise Swipe
Analysis , InsuranceClaims NPS Analysis ,
Fraud Analytics, Market Basket Analysis,
Areas: Hypothesis Testing,
ARIMA/ARIMAX, Fixed effects model,
Linear/Logistic Regression, CHAID, ML
(KNN, Naïve Bayes, Random forest), Tf-
idf, Association Mining
Skills: R, Python,SAS -eMiner, Hive,,
Teradata, SQL Tools
Clients: AIG, WNS, MuSigma, Retail,
Accenture
13. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 13
Sumyag Insights
Data Science , Analysts
Milind K
Data Science with ~2 years experience
Work: Individual surrender Analytics -
porting to Spark, Data Quality & profiling
large Insurance data-sets. Used regex and
algorithms to characterize data-sets
automatically
Areas: regression models, Random
forest, Regression and Classification
algorithms using ML, Regular expressions
based parsing, active on kaggle
Skills: Python,hadoop - Hive,SQOOP,
Spark, Web Apps using Spring, Oracle
PL/SQL, MySQL, SQL Server, SQLite, JSON
Clients: TCS, AIG
Herat K
Data science with ~2 years experience
Work: document similarity, document
classification, clustering, string matching,
web scraping, text cleaning
Areas: Apriori, Linear Regression,
Decision trees, K-means clustering
String, text matching - Levenshtein ,
prediction using Interpolation, Linear
regression, text cleaning
Skills: Python, C, Java, , postgresql, My
Sql, Java script, Ajax
Clients : Embibe , IBM, OpenStream
Suraj J
Work: 5 years python, analytics Modeling
Areas: Python development,
Implementing & Automating Data
Science frameworks , Data warehousing,
big data, data mining, text analytics,
Reporting using Python Django platform,
Model Automation
Skills: Python, Linux, SQL,HTML, GITHUB
Client: Anheuser Busch, Big Basket, AIG ,
Hitachi
14. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 14
Showcase and work Areas
The Work underway
15. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 15
Sumyag Insights
Proposal for Setting up Analytics
• Three modes of play, Research, Develop, Maintain
• Seamless transition to dynamically optimize budget,
• Transparency on capacity , utilization and transfer benefits
• Drive ,Deliver or Support in all the outcome areas – End to End
Tri-modal delivery
Research
Low ~ 0 Cost
Discover solution
Propose / Go-NoGo
Define commercials
Design Dev
Core Technology
Agile – iterate
2 Week Sprints
New and Change
Capacity based Price
Maintain Operate
Reduce Cost
Reduce Capacity
Ensure Upkeep
Time
Cost/BurnRate
Cost & Effort
Data Prescience
1. Data Wrangling - readiness
for modeling
2. Univariate – Bivariate models
and Reports
3. Data Characterization
Model Development
1. Use-Case development of
models
2. Affinity & Association
3. Regression /Classify
4. Clustering – KNN
Business Application
1. Reports and end user design
2. Need for BI or Integration
3. Need for API or Mobile App?
Cloud Analytics Infrastructure
1. Provision Setup Cloud
Analytics Infrastructure
2. Configure and Setup all the
relevant applications and
frameworks for Data Science
Document Retrieval
1. Share-point Policy system
document Retrieval
2. Setup Manual or Automated
Retrieval for future periods
Doc to Data Extraction
1. Extract Data into Tables
2. Parsing document to fields
and tables
3. Validate and cleanse data
Outcomes and Deliverable Areas
1 2 3
4 5 6
Engagement Duration [W] Resources Cost
Develop/Design 2 weeks 3
Maintain/Op 2 weeks 2
Research 2 weeks 1
Onsite 1 week 1
16. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 16
Approach for Research & Discovery - POC
Research Funnel What Clients get?What we do?
Data &
Business Problems
Solution / Model
Framing
Business
Outomes
Engagement
Preliminary Research / Screening
• Define Metrics, Analytics Pathways
• Formaland quantitative methods
• Modelling , Simulation, Solution Discovery
• Showcasepossibilities & Skills of the team
• Mashup outcomes
Data & Scrambling
• Get Sample Data Sets, & Wrangling
• Gauge Business context& Issues
• OutcomeExpectations
Client – Workshops – Finalization
• Risks and Costs Definition
• Deeper insights and options for decisioning
• Client Workshops and finaliseEngagementModel
• Define Commercials & Benefits
Rapid Setup
Short timeframe
1-2 weeks
Low Cost Multiple Pathways
Understand Risk ControlGo or No
17. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 17
Approach – Agile Scrums
17
Onsite
Connect
(discovery)
Sprints – Bi-weekly timeframe
T+1wT T + 13w T + 14w
Onsite
Connect
Operations
& Maintenance
T + x mo
Product Planning &
Agreements
User Experience and
Connect
Systems and Tech
Teams Connect
Understand the
Business Case
Back log development
Maintain outputs emerging from
development
Iterative Agile – Sprints
India Skill and price Advantage
On-location as required
Technical excellence, across Data
Science, Digital, DevOps
Lean, Virtual , Flexible
Back-logs, work to max potential
Onsite presence 1W/Q
Product Development
Review
Customer feedback
Solution & Business
requirements
Further Agile – plan &
Backlog
Technical excellence, across
Analytics, Digital, DevOps
Lean, Virtual , Flexible
Back-log, team executes to
maximum potential
India Skill & price
On-location as required
Low cost – 0 Cost research in
parallel to Development
Research is a Funnel for new
ideas and areas of pursuit
Tech feasibility & research
Separate backlog from Dev
Proposal, Sign off
Research and
Solution Dev
Build and Develop solutions and ModelsNo Deliverable Sprint
R Research – Activities 1
(1) Cloud Infrastructure 1
(2) Document Retrieval 2-4
(3) Document Extraction 2-3
(4) Data Prescience 3-5
(5) Model Development 4-6
(6) Business applications 5-7
18. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 18
Proposed – Relationship Structure
DATA &BI TEAM
Data ingestion, Storage
Data Wrangling – Engineering
Data Characterization –metadata
BI - Reporting
SCIENCE– APPLICATION TEAM
Model Development & Validation
ML & AI
API – Apps
COE LEAD
ProductManagement
Back log, Scrumand Delivery
Manage client Expectation and
Relationship
Bridge between business and
Technology
Consult and Transform
THB –STAKEHOLDERS
Business Heads and Leads
Business Direction, Strategy
Requirement and priorities
Controls , Authorization, Approvals
Coordination with other entities
THB SPONSOR/LEAD
Delivery Model
vCOE Plug & Play delivery model { <12 weeks commitments }
Pricing per Sprint, [burn rate per Sprint ] with options to book sprints in
advance
Communication Channels
Sprint based allocation – implementation & innovation
Measure outcomes
Review “Actionability” – fine tune
19. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 19
Our Current Book of Work
InfrastructureData Science Infrastructure
Design Deploy and Deliver
for Education Services
Robotic Process
Automation in Insurance
Policy Management
Document extraction and
Intelligencein Insurance
IoT Sensor PipelineDesign
Deploy and Intelligence–
Large Indian Customer
Smart Spaces – IOT
Intelligencesolutions
Responsive Digital
Application – Insurance
20. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 20
Sumyag Insights
Showcase: Automating- Data & Prescience
BUILD
MODELS
STREAMING ALGOS
CLASSIFICATION
SIMULATION
ASSOCIATION
REGRESSION
Visual Outputs to
analyse and generate
insights
INGEST DATA TYPE CHARACTER QUALITY TRANSFORM INTERACTIONS
UNDERSTAND YOURDATA
• Connect to a DB
• File , read and
store
• API to pull
streaming data
• Metadata and data
detection
• Most logical join
between tables
• Distribution / Uni-
variate
• Pattern Detection
• Missing and Junk
• Outlier Analysis –
Uni-variate
• Missing at Random
• Data Quality
Recommendation
• Log , Expo ,
Standardise ,
Normalise
• Primary key
summary / Pivots
and Filters
• Categorical to
Numeric
• Data Sampling
• Correlation -
Numerical and
Categorical
• Variable Reduction
• Feature
Importance
GENERATEINSIGHTS
Insight
generation
Data
Prescience
Text
Processing
Advanced
Models
• Outcomes First
– Practical Business Insights
– Deep support Where Operations
meets Business
– Agile – Iterate – Innovate
• Automate First
– Pre-built code /modules that
eliminate manual efforts
– Code Driven Analytics
• Platform First
– Standard Deployment
– Open Architecture / Inter-
Operability
– Configurable,Flexible
• Virtual – COE
– Flexible Operations
– Flexible Skills
– Flexible Capacity–PAYG
21. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 21
Sumyag Insights
Showcase: Science on the Cloud – Science Research Sandbox
• Node on the Cloud
– StandardLarge vendors like GCE,
AWS,Azure
– Rapid Lab Setup
• Technology Stack
– Scrape
– Ingest – kafka, SQOOP, Hive
– Process – MR, SPARK
– Model – R, Python,
TensorFlow, H2O
• Leverage the Ecosystem
– ML-API
• Flexible Scale
– Deploy as you grow
– DevOps
• Consumable Insights
– BI
– API – Web Mobile, Hybrid
– Apps
22. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 22
Sumyag Insights
Showcase: Document – Text Analytics In Insurance
20%
80%
80% enterprisedata is
unstructured, In the
form of Documents,
Email, Text, Logs
FORMATS
1. Legal - Contracts
2. Communication
3. Information
4. Research – Reports
5. Machine Logs
6. Interactions –Chats
Media
Not even considered for Business Information
Complex natureof the
data and the challenges ,
achieving accuracy and
costs in processing has
lead Enterpriseto under
leverage unstructured
Data for the enterprise
Our framework, we a collection of documents and extracts content
retaining the original information, structure and context. A pipeline of
frameworks then extract, objects, Data- Types, meta-data & dictionary
driven Entities finallyDeriving Key-Value pairs. These individual text
fragments are then processed for NLP – for sentiment and Association.
These then can be useful for intelligence or downstream models.
1 Content. Entity Extraction
Document Classification
Document Comparison
Time Series – Sequence
Sentiment Analysis
2
3
4
5
23. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 23
Sumyag Insights
Showcase: IOT . Digital . Insights in Retail
Invisible Customer
Ghost Customer - >90% of customers Who
Don’t Buy
Currently retail have no way of tracking
these customers
Understanding customers Better Where
they walk, Attention, Expression,
Demographics
Applying Technology + Nudges towards
purchase
Smart RetailStore
• Sensors & Controllers
• LED Panels for playout
• Cloud Services
• Data.Ai -Intelligence
• Web Applications
• PresentationBI
• ControlAdmin
24. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 24
Insurance Value Chain – Our Experience
Customer Management Claims Management Actuarial Pricing / Risk
Customer Retention, CLV, Market Basket Analysis,
Segmentation & Targeting, Digital marketing
Claims Triaging – STP, Claims Fraud,
Claims litigation, Subrogation,
Loss models, Catastrophe Risk, Price optimization
Surrender/Lapsationmodel tounderstand
customerpropensitytosurrenderbasedon
demographics, Psychographics,
US – Personal 5 MM Customers,4 Bn USD Portfolio
LogisticRegressionwithSplinesonPythonRSpark
on HadoopClusters
CustomerretentionModel forP&C,life multiple
regions
IndianInsurer4 Regions,500 Mn GWP and 10 Mn
customers.Complete endtoendutility,paidbased
on premiumcollected.
Clusteringandlogisticregressions
ClaimsLitigation– Propensitytolitigate and
sensitivitytoclaimsvalue
US – Worker compensationservices,TPA.
LogisticRegressionsdevelopedonR andPython
ClaimsAllocationandstraightthroughprocessing–
liningupclaimstoagentsbasedon skills
ProximitybasedonlinearClustering
Telematics,AutoInsurance Scoringof Driversfor
Risk valuationandtherebypricingandcustomer
segmentation
2 projects,inUSA on AWS andPython/ Java and
the otherwithPartnerMyDrive on Hadoop
Year to date Loss prediction functionforP&C
insurance onHadoop
Simple calculatortosummarize YTDlossby various
products,regions,clients,speededupusing
Hadoop/ HIVE
Finance / IR InvestorReportsDashboardwith
sentimentandentityExtraction
130 Analysts,perQuarter,,siftingthrough~ 1500
Documents.ExtractEntities& sentimentusingNLP
to understandanalystviewsforCFOperusal
MarketingSpendOptimizationandMarketChannel
Management– Market basketAnalysis
Time Series, LinearCorrelationbetweenSpendand
Sales
ClaimsSubrogation–what isthe possibilityof
counterparty Insurance claimsbasedon
Time Series,LinearCorrelationbetweenSpendand
Sales
24
25. Sumyag Insights
Private & ConfidentialTransformation: Analytics, IOT, Digital 25
Other Verticals & Solutions worked on..
• Banking : HSBC :2014 AML / FCC compliance, built a scoring framework for Correspondent banking
transactions passing through USA, Hong Kong, SNG, UK covering ~ 60T USD / 70 Mn Transactions volume through
the bank networks. The objective was to red flag suspect transactions based on value, frequency, transaction
details and source and destination banks
• Insurance: AIG :2015 model Engineering and deployment of 23 Insurance Models built by actuarial teams
on R and Python on to production with execution automation. Worked on worker compensation, lapsation and
other use case
• Insurance: AIG :2016 Mobile Visual Quote: Mobile application front end for visual policy generation using
Image deep learning in the back end to recognize objects through smartphone camera and then responding with a
Amazon like offer to the customer. The solution would snag an image, recognize the object, and provide pricing
options to the customer
• Insurance: AIG: 2015 IT Security Blue-coat analysis to index and score based on red Flagged logs from
global blue coat devices to identify frequent offenders, outbound destination and content type
• Insurance: AIG :2016 Dataquality platform on Hadoop to replace IBM Infosphere and pilot the execution
of Talend DQ on Hadoop .. This was very successful in automating a lot of the DQ processing at large scale.
Consolidated 7000 Data Marts on Hbase
27. 27
Unmithy Services
virtualCOE
COE As A Service | Virtual COE without Scale or Large Investment or Long-term Commitment |
Flexible Engagement Options
Key Features
» Get a standard Pod with fixed number of
resources having required skills to support
your initiatives
» Lead resource plays Product Mgr. or
Project Mgr. or Scrum Master
» Flexibility to add niche skills or other skills
as required
Value to Clients
» Access to COE without scale or major
investment or commitment
» ‘Engage-as-you-need’ mode
» A mix of related and complimentary skills
in a box as a service
» Reduced workforce sourcing and mgmt.
costs
Engagement Options Pricing
» Fixed for a given duration and for a given
resource mix (or)
» Per Pod-sprint. A sprint is around 4wks (or)
» Utility based [measured in terms of volume
of output]virtualCOE Pod
Lead
Skill A Skill B
Skill C Skill D
Inputs
Peers & Reports
Public Data
Standards
Knowledge Base
Deliverables
» Source virtual COE Pods – base pod with
4 ~ 6 resources with a mix of skill sets –
for as minimum duration as 3 months
» Engage virtual COE, but measure delivery
in terms of output
28. Unmithy Services
virtualLeadership
Virtual and Part-time Staffing of Leadership Roles | On-demand Skills | Advisory | Virtual BOD
for SMBs | Independent Review and Validation of Strategies and Execution Plans
Key Features
» Business change for a Network Economy
» Neutral perspective on businessdecisions/ /
plans& strategy
Value to Clients
» Access to high quality leadership skills on
demand without a need to hire a full time
employee or contractor
Engagement Options
» ‘Hire-as-you-need’ – Senior leadership and
SME capabilities to support transformation
programs
» Retainership model for continued
leadership support
» Co-create strategy realization [Ideate,
Mentor, Skill, Execute]
Pricing Options
» Per-hour pricing
» Retainership fee
virtualLeadership
29. Unmithy Services
Transformation
Transformation Programs Design | Solution Design Workshops | Program Execution | Value
Delivery | SME Support | Innovation Workshops | Independent Reviews
Key Features
» SMEs with over 20 years of avg.
experience in delivering large
transformation initiatives
» Unique confluence of skills [domain,
functional, and change management]
» Proventransformationframeworkandagile
executionmethodology
Value to Clients
» Accelerate value from transformation
programs
Engagement Options
» Full ownership for end-to-end
engagement
» ‘Internal start-ups’ model
» Time and material model
» On-demand engagement of required skills
Pricing
» Per-hour based
» Fixed for engagement
» Outcome-based
» Hybrid of above
TR!Z
Lean
Practices
SIGN
TH!NK!NG
ED
30. Unmithy Services
Insights
Big Data Science | Code-centred Insights | Pre-built Data & Insight Framework | Open Source
Applications and API | DevOps | Modelling & Simulation | Prediction | Machine Learning
Key Features
» Singled-mined focus on delivering relevant
and right insights
» Code-driven analytics combined with
SMEs with deep domain and functional
knowledge to build narratives
» Leverage Open Source software,
platforms, and knowledge base
Value to Clients
» From numbers to narratives as well for
faster, timely, and effective decisions
» Extract insights fast wide variety of data
[structured / unstructured] in short timed
iterations / sprints
» Reduced TCO [cost of ownership] with
code-driven big data science
Engagement Options
» On-going capability within a “virtualCOE”
wrapper
» Project-based engagement
Pricing
» Mixed pricing on Resources & outcomes
» Baselined on a combination of [data type,
volume, complexity, and use cases]
Impact
Decisions
Narrative
Numbers
Context