Q&A with Tom Raftery, Global VP at SAP

Q&A with Tom Raftery, Global VP at SAP
Tom Raftery, Global VP at SAP is an Innovation Evangelist, Futurist, and international Keynote speaker. Prior to joining SAP, Tom worked for a number of companies at Group IT Manager/CTO level, and as an Industry Analyst. Tom is a global thought leader and ranks among the top 10 Internet of Things influencers in the world. 

MEDIA 7: If I were to say to a bunch of people who know you, ‘Give me three adjectives that best describe you’, what would I hear?
TOM RAFTERY: 
I would like to think that I am a good communicator, maybe smart and hopefully generous. You will have to ask people other than myself though. They would be a better judge.

M7: What is the role of a technology influencer in driving environmental sustainability?
TR: 
The role of someone like me would be to raise awareness of the issues that are happening and potential solutions to them, particularly technological solutions. A lot of people are busy in their day-to-day lives and they might not be aware of some of the more pressing environmental issues that are happening in the world and that might impact them. So, raising awareness with people, of the importance of these issues, and the potential technological solutions to them is the role I think that influencers should be playing.


"Raising awareness with people, of the importance of environmental issues, and the potential technological solutions to them is the role that influencers should be playing."

M7: SAP is celebrating the 10th anniversary of strategic sustainability this year. What are the initiatives being taken by the company to help the world run better and achieve the UN sustainable development goals by 2030?
TR:
We are involved in a lot of different projects in this front. We work for example, with Vestas Wind Systems who are the only global energy company dedicated exclusively to wind energy. We help them with their backend systems to help optimize the delivery of windfarms and turbines to windfarms, so that they are keeping their costs down and deploying the windfarms with the highest efficiency. We work with Munich Re and the European Space Agency. Munich Re are one of the largest reinsurance companies in the world and for them, they need to predict, and try and mitigate the damage of natural disasters. We use data from European Space Agency to help Munich Re do that.

We work with Brazilian company, Stara who are an agricultural company. They manufacture agricultural equipment, and the work we do with them is what’s called precision agriculture. Precision agriculture means that we can help their machines be far more precise in things like spreading fertilizers, spreading seeds to make sure that the seeds don’t overlap, the fertilizer doesn’t overlap and you’re doing it row by row. You have to sow the seeds and spread the fertilizer very accurately to avoid an overlap. Because if you have overlap with fertilizer, it can reach toxic levels and damage the plants that you are trying to help. If you have overlap in seeds, you can have excess competition between the seeds and then you get reduction in yield. Whereas if you are optimizing using precision agriculture, you are massively reducing your inputs and you are maximizing your outputs. So, you are able to feed more people with less land and less resources which obviously, as we are reaching higher population levels year-on-year, this becomes more and more important.

We work with NGOs like this one in Africa, called Elephants, Rhinos and People which was founded to preserve and protect the wild elephants and rhinos in Southern Africa. We work with local people to make sure that it’s more profitable for them to protect wildlife than it is to be poaching wildlife. We put collars on elephants and rhinos with geo-tracking in them. We use drones, to track the elephants and rhinos and if they start approaching borders of the parks that might expose them more to poaching. We send off alerts and help move them back into places where they are safer. Since we started the initiative in that area, no elephants rhinos, or humans have been harmed since the deployment of the tracking.

We work with Swiss Federal Railways, the largest energy consumer in Switzerland and they are also an energy producer - they produce electricity. So, we work with them to help reduce the peak loads, the peak demand for electricity by flattening their load which then means, they don’t need to build extra generation plants, reducing their carbon footprint and making their organization more efficient.


"Making our workforce aware of what we are doing as our external constituents is important for our employees to feel engaged and part of something important."

M7: You have been on the SmartCitiesWorld Advisory Board. How does SmartCitiesWorld help in developing smart cities of the future?
TR:
The SmartCitiesWorld is a publication. It raises awareness of smart cities initiatives that cities can take to make the cities run better, reduce their energy requirements, reduce their footprint, increase their air quality, reduce noise pollution, and lots of different initiatives like that. So, as a publication, it’s primarily responsible for raising awareness and helping cities find better ways to increase quality of life for their constituents.

M7: How does SAP embrace an innovative culture in the company?
TR:
Obviously, as a technology company it is very important for SAP to embrace an innovative culture in the company and what the company typically does is, it spends a lot of money on research and development and it does a lot of communication internally and externally highlighting the innovative solutions that we have come up with for our customers. And making our workforce aware of what we are doing as our external constituents because it’s important for our employees to feel engaged and part of something important. And as a consequence, every time, every year, we run this survey internally on how happy our employees are working for SAP. And our rate of employee retention is extremely high.

It’s not unusual in Europe to talk to SAP employees who have been working for the company for 10 or more years, which in the technology industry is unusual. So, that’s how we embrace the innovative culture and we talk of the things that we do, we work closely also with our customers because we do a lot of co-innovation projects with our customers where we take our customers into our co-innovation centers and we talk through their problems with them and come up with innovative ways to solve any particularly gnarly issues that they might have.


"A lot of people are busy in their day-to-day lives and they might not be aware of some of the more pressing environmental issues that are happening in the world and that might impact them."

M7: What is your favorite part of working at SAP?
TR:
I started working for SAP in September 2016, so it’s just over 3 years ago now. And, prior to working with SAP, I had worked primarily with startups and small companies. I have never worked with a global mega vendor before. So, I was wondering what it would be like and I had my doubts, and if you would ask me in 2016, I would have said, “Yeah, I’ll probably last about three months with SAP”. But, three years later, here I am. And, a lot of that is down to the fact that the company is so big, and it has close to 100,000 employees, it means there are always people I can approach, if I need help in any country or in any industry. Because my role is across industry. So, if I need to talk to somebody who is in the transportation industry, I can just go straight to the transportation business unit and talk to people there. If I need to talk to people in the hospitality industry, same story. If I need to talk to people in the airline industry, the mining industry, the electricity industry, we cover all industries, we cover all regions globally. And, there’s a culture within SAP of helpfulness which is great. Apparently, it’s unusual. For me, it’s the norm if people bring up and ask me for help, I would say, “Yeah sure, absolutely, no problem.” And that’s the way most people in SAP are! You pick up the phone or send an email, and they are happy to help, no matter what. Apparently, that’s not the norm for big companies, but it is the norm for SAP which is great and that’s why I love working for SAP.  

M7: When did you start working, how old were you, and what was it?
TR:
My first job was when I was 14. I worked on a building site where I was a builder’s mate, helping raise the scaffolding on the building and also help ferry bricks that were delivered to the site from the ground up to the brick layers on the top floor. So, that was my first job.

ABOUT SAP

SAP is a global software application vendor. SAP is the market leader in enterprise application software, helping companies of all sizes and in all industries run at their best: 77% of the world’s transaction revenue touches an SAP system. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers’ businesses into intelligent enterprises. Our end-to-end suite of applications and services enables our customers to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, SAP helps the world run better and improves people’s lives.

More THOUGHT LEADERS

Q&A with Charles Southwood, Vice President, N. Europe and MEA at Denodo

Media 7 | September 15, 2021

Charles Southwood, Regional VP at Denodo Technologies is responsible for the company’s business revenues in Northern Europe, Middle East and South Africa. He is passionate about working in rapidly moving and innovative markets to support customer success and to align IT solutions that meet the changing business needs. With a degree in engineering from Imperial College London, Charles has over 20 years of experience in data integration, big data, IT infrastructure/IT operations and Business Analytics....

Read More

Q&A with Vishal Srivastava, Vice President (Model Validation) at Citi

Media 7 | September 8, 2021

Vishal Srivastava, Vice President (Model Validation) at Citi was invited as a keynote speaker to present on Fraud Analytics using Machine Learning at the International Automation in Banking Summit in New York in November 2019. Vishal has experience in quantitative risk modeling using advanced engineering, statistical, and machine learning technologies. His academic qualifications in combination with a Ph.D. in Chemical Engineering and an MBA in Finance have enabled him to challenge quantitative risk models with scientific rigor. Vishal’s doctoral thesis included the development of statistical and machine learning-based risk models—some of which are currently being used commercially. Vishal has 120+ peer-reviewed citations in areas such as risk management, quantitative modeling, machine learning, and predictive analytics....

Read More

Q&A with Sadiqah Musa, Co-Founder at Black In Data

Media 7 | September 1, 2021

Sadiqah Musa, Co-Founder at Black In Data, is also an experienced Senior Data Analyst at Guardian News and Media with a demonstrated history of working in the energy and publishing sectors. She is skilled in Advanced Excel, SQL, Python, data visualization, project management, and Data Analysis and has a strong professional background with a Master of Science (MSc) from The University of Manchester....

Read More

Q&A with Charles Southwood, Vice President, N. Europe and MEA at Denodo

Media 7 | September 15, 2021

Charles Southwood, Regional VP at Denodo Technologies is responsible for the company’s business revenues in Northern Europe, Middle East and South Africa. He is passionate about working in rapidly moving and innovative markets to support customer success and to align IT solutions that meet the changing business needs. With a degree in engineering from Imperial College London, Charles has over 20 years of experience in data integration, big data, IT infrastructure/IT operations and Business Analytics....

Read More

Q&A with Vishal Srivastava, Vice President (Model Validation) at Citi

Media 7 | September 8, 2021

Vishal Srivastava, Vice President (Model Validation) at Citi was invited as a keynote speaker to present on Fraud Analytics using Machine Learning at the International Automation in Banking Summit in New York in November 2019. Vishal has experience in quantitative risk modeling using advanced engineering, statistical, and machine learning technologies. His academic qualifications in combination with a Ph.D. in Chemical Engineering and an MBA in Finance have enabled him to challenge quantitative risk models with scientific rigor. Vishal’s doctoral thesis included the development of statistical and machine learning-based risk models—some of which are currently being used commercially. Vishal has 120+ peer-reviewed citations in areas such as risk management, quantitative modeling, machine learning, and predictive analytics....

Read More

Q&A with Sadiqah Musa, Co-Founder at Black In Data

Media 7 | September 1, 2021

Sadiqah Musa, Co-Founder at Black In Data, is also an experienced Senior Data Analyst at Guardian News and Media with a demonstrated history of working in the energy and publishing sectors. She is skilled in Advanced Excel, SQL, Python, data visualization, project management, and Data Analysis and has a strong professional background with a Master of Science (MSc) from The University of Manchester....

Read More

Related News

Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

Read More

Big Data Management

data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

Read More

Data Visualization

SensiML Unveils Data Studio - Next-Generation Sensor Data Management for AI / ML

SensiML | December 20, 2023

SensiML Corporation, a leader in AI software for IoT and a subsidiary of QuickLogic, announced the launch of Data Studio, a ground-breaking platform designed to redefine the landscape of sensor data management. With a focus on practicality and efficiency, Data Studio empowers engineers and data scientists by offering an integrated solution that addresses the most time-consuming tasks in AI engineering projects - creating high-quality datasets for evaluating and developing ML models. According to Cognilytica, a well-respected AI / ML consulting firm, approximately 80% of the total time for machine learning (ML) projects is allocated to data preparation. These tasks include data identification, aggregation, cleansing, labeling, and augmentation – all of which are supported in SensiML's collaborative development environment. SensiML Data Studio significantly improves productivity and simplifies dataset management for anyone working on sensor data ML projects. With real-time connectivity, intuitive visualization tools, sensor data video synchronization, and robust support for large-scale collaborative projects, it offers a seamless experience for developers on edge devices, gateways, PCs, and cloud platforms. A comprehensive overview of all the features of Data Studio can be found on the SensiML website. The primary features are highlighted below: Effortless Data Capture and Import - Capture live sensor data, analyze it instantly, and label any data for seamless insights. Collaboratively Label Sensor Data - Employ flexible labeling methodologies for sensor data, including manual, AI-assisted, and custom – and sync video for effortless complex labeling. Store and analyze data locally on your computer or remotely. Data Analysis and Model Evaluation - Visually compare ML models, filter, transform, and fuse sensor data – all with built-in tools and your own Python expertise. Label and Data Versioning – Keep track of your labels and model results with versioned labels. Easily export your project to an open format. "SensiML Data Studio makes sensor data management and analysis more accessible and efficient, empowering developers to build better, more impactful applications using sensor data across a wide range of industries," said Chris Knorowski, CTO of SensiML. SensiML Data Studio is poised to transform sensor data analysis, offering a valuable resource for researchers, engineers, and data scientists across diverse sectors from agriculture and consumer wearables to medical devices, smart buildings, and factory maintenance. About SensiML SensiML, a subsidiary of QuickLogic (NASDAQ: QUIK), offers cutting-edge software that enables ultra-low power IoT endpoints that implement AI to transform raw sensor data into meaningful insight at the device itself. The company's flagship solution, the SensiML Analytics Toolkit, provides an end-to-end development platform spanning data collection, labeling, algorithm and firmware auto-generation, and testing. The SensiML Toolkit supports Arm® Cortex®-M class and higher microcontroller cores, Intel® x86 instruction set processors, and heterogeneous core QuickLogic SoCs and QuickAI platforms with FPGA optimizations.

Read More

Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

Read More

Big Data Management

data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

Read More

Data Visualization

SensiML Unveils Data Studio - Next-Generation Sensor Data Management for AI / ML

SensiML | December 20, 2023

SensiML Corporation, a leader in AI software for IoT and a subsidiary of QuickLogic, announced the launch of Data Studio, a ground-breaking platform designed to redefine the landscape of sensor data management. With a focus on practicality and efficiency, Data Studio empowers engineers and data scientists by offering an integrated solution that addresses the most time-consuming tasks in AI engineering projects - creating high-quality datasets for evaluating and developing ML models. According to Cognilytica, a well-respected AI / ML consulting firm, approximately 80% of the total time for machine learning (ML) projects is allocated to data preparation. These tasks include data identification, aggregation, cleansing, labeling, and augmentation – all of which are supported in SensiML's collaborative development environment. SensiML Data Studio significantly improves productivity and simplifies dataset management for anyone working on sensor data ML projects. With real-time connectivity, intuitive visualization tools, sensor data video synchronization, and robust support for large-scale collaborative projects, it offers a seamless experience for developers on edge devices, gateways, PCs, and cloud platforms. A comprehensive overview of all the features of Data Studio can be found on the SensiML website. The primary features are highlighted below: Effortless Data Capture and Import - Capture live sensor data, analyze it instantly, and label any data for seamless insights. Collaboratively Label Sensor Data - Employ flexible labeling methodologies for sensor data, including manual, AI-assisted, and custom – and sync video for effortless complex labeling. Store and analyze data locally on your computer or remotely. Data Analysis and Model Evaluation - Visually compare ML models, filter, transform, and fuse sensor data – all with built-in tools and your own Python expertise. Label and Data Versioning – Keep track of your labels and model results with versioned labels. Easily export your project to an open format. "SensiML Data Studio makes sensor data management and analysis more accessible and efficient, empowering developers to build better, more impactful applications using sensor data across a wide range of industries," said Chris Knorowski, CTO of SensiML. SensiML Data Studio is poised to transform sensor data analysis, offering a valuable resource for researchers, engineers, and data scientists across diverse sectors from agriculture and consumer wearables to medical devices, smart buildings, and factory maintenance. About SensiML SensiML, a subsidiary of QuickLogic (NASDAQ: QUIK), offers cutting-edge software that enables ultra-low power IoT endpoints that implement AI to transform raw sensor data into meaningful insight at the device itself. The company's flagship solution, the SensiML Analytics Toolkit, provides an end-to-end development platform spanning data collection, labeling, algorithm and firmware auto-generation, and testing. The SensiML Toolkit supports Arm® Cortex®-M class and higher microcontroller cores, Intel® x86 instruction set processors, and heterogeneous core QuickLogic SoCs and QuickAI platforms with FPGA optimizations.

Read More

Spotlight

Sap

SAP is a global software application vendor. SAP is the market leader in enterprise application software, helping companies of all sizes and in all industries run at their best: 77% of the world’s transaction revenue touches an SAP system. Our machine learning, Internet of Things (IoT), and advanced...

Events

Resources

Events