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Learn to engineer products of the future at the University of Southern Denmark – Study International News

Ilian Pappas love for technology dates back to when he was just a boy growing up in Albania. He had always excelled in mathematics and physics. Having a mother who came from a biochemistry background helped. I have always gotten satisfaction from proofing or solving problems, he says.

Upon moving to Greece at the age of 16, Pappas love for science and electronics continued to blossom. The courses he took in high school inspired him to pursue a bachelors degree in Electronics at the Alexander Technological Educational Institute of Thessaloniki.

When the time came to look into postgraduate studies, Pappas foundation opened a variety of doors. He got accepted to institutions in Austria and the UK, but one university stood out to him for multiple reasons. The University of Southern Denmark (SDU) was not just facility-filled or a comfortable home for 1,500 international students every year, it was also far more affordable than most.

Source: University of Southern Denmark

Whats more, the university has a programme that was aptly in line with his goals. I wanted something in electrical engineering for my masters and SDUs option to combine power electronics with mechatronics sounded very attractive to me, he shares.

The programme that caught his eye? SDUs MSc in Engineering Mechatronics. This programme nurtures trouble-shooters to design and develop high-tech mechatronic products for an ever-evolving market. As consumers increasingly demand faster and more flexible products, these professionals will remain in demand creating effective products that could also save energy.

Source: University of Southern Denmark

Apart from a suite of technical skills that identify problems and optimise production, students are set to graduate with crucial leadership skills. This know-how produces engineers that work across disciplines transforming product ideas into practical solutions for everyday life. In short, its a programme that nurtures development engineers with special competencies in mechanics, electronics, and software.

Those who decide on this route become part of a project-based study environment that focuses on problem-solving. Real-world problems ensure students graduate career-ready. The programme accomplishes this by receiving project outlines from companies looking for solutions. Alongside hands-on teachings and a student-centred approach to learning, Pappa thoroughly enjoyed classes in control systems, electromechanics, switch mode converters, grid connected converters, and VHDL during his studies. He also considers the MDB projects to have been extremely useful.

I believe having a masters degree helps to some extent in finding a job. On the other hand, SDU is a university that companies in the region both know and appreciate, he explains.

Source: University of Southern Denmark

At SDU, immersion opens doors. Graduates often enjoy a range of job opportunities both within Denmark and abroad. Many succeed as development engineers with managerial responsibility, specialists in specific technologies, consultants, educators, researchers, entrepreneurs or even project managers.

We find the study programme really interesting, because we envision great opportunities for engineers who master multiple disciplines, says INFOCOM A/S CEO Bent Kristensen. Especially here at INFOCOM we can easily picture an engineer with a degree in mechatronics as a project manager.

The First Job Guarantee scheme ensures SDU graduates hit the ground running. The joint effort by the university and Southern Denmarks vast array of local companies offers fresh grads six months of employment, if they have yet to acquire a position on their own.

Pappa landed a rewarding role of his own just days away from graduating. Now a hardware engineer at Danfoss Power Solutions in Nordborg, he credits the knowledge he gained at SDUH for his present success. The top three SDU offerings that have prepared him for the rigours of the workforce? Exposure to research, collaboration, and lessons in todays engineering tools. Industry knowledge was an added bonus. SDUs Department of Engineering gave him the chance to job shadow in Danfoss Silicon Power in Flensburg and visit FORCE Technologys EMC lab in Aarhus with the rest of his class.

Both were very good in giving me an impression of a company while gaining in-depth knowledge on new technologies or projects, he enthuses. I am currently practising EMC testing as a professional and Ive had the chance to meet the same people I did when visiting as a student.

If youre ready to network with leading industry figures, join a vibrant multinational campus, take part in a comprehensive programme, and ultimately learn the fundamentals of engineering products of the future, click here to begin your SDU journey.

Follow SDU on Facebook, Twitter, Instagram, YouTube, Pinterest and LinkedIn

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Off to a busy start, data institute responds to COVID and seeks director – University of Wisconsin – University of Wisconsin-Madison

The American Family Insurance Data Science Institutes first two years have been nothing if not eventful.

Last spring, as the campus and state shut down in response to the COVID-19 pandemic, AFIDSI responded to the need for mathematical modeling to guide policy decisions and public health outreach. Within weeks, the institute had convened a team of leaders and experts from across the U.S. The COVID-19 Research Group met daily in the early weeks of the pandemic, creating models and sharing findings as quickly as possible.

The institute has shown strong leadership during the pandemic, pulling together a team of more than a hundred people to further understanding of COVID-19 and inform campus mitigation efforts, says Amy Wendt, associate vice chancellor for research.

Leadership is the next big project for the institute, which is recruiting a permanent director. Applications are due April 15.

Meanwhile, AFIDSI staff are working with the School of Medicine and Public Health to identify potential hotspots for virus transmission, using natural language processing techniques with testing and contact tracing data. With the Wisconsin State Lab of Hygiene, research group members are supporting efforts to detect and measure COVID-19 variants through wastewater surveillance.

In partnership with AFIDSI, Michael Ferris and Corey Jackson, both with the School of Computer, Data and Information Sciences, are supporting vaccine logistics with the Wisconsin Department of Health Services and the Wisconsin National Guard. To overcome disparities that stem from health, economic and educational inequities, as well as discrimination, Jackson and Ferris have begun work on a recommendation engine to ensure vaccines are allocated fairly.

In addition to campus collaborations, the institute is working closely with American Family Insurance to create the American Family Funding Initiative.

The American Family Funding Initiative is supporting fundamental data science research, including third-wave AI systems and a variety of novel machine learning research projects, with researchers from multiple campus departments, said Whitney Sweeney, AFIDSI assistant director. The initiative also supports applied research. To date, more than $2 million has been awarded through this initiative to 16 data science research teams.

Jon Eckhardt, associate professor in the Wisconsin School of Business, heads one of these teams. With support from the American Family Funding Initiative, his team at the Entrepreneurship Science Lab is using data-based insights to better prepare student entrepreneurs for successful careers that add to the economic prosperity of their communities.

Support from American Family Insurance is crucial to the success of the lab, says Eckhardt. We are excited to be working with Dan Reed, Glenn Fung, and other innovators at AmFam to create opportunities for our students, graduates and communities.

The American Family Funding Initiative is also supporting fundamental data science research, including third-wave AI systems and a variety of novel machine learning research projects, with researchers from multiple campus departments.

The future of data science will be driven by insights from all disciplines and AFIDSI is committed to working across campus. Iain McConnell, a data scientist at the institute, is collaborating with the Institute for Research on Poverty to improve cross-referencing of data from multiple social service programs, so researchers can better understand how people use the services offered through these programs. The ultimate goal of this work is to reduce poverty in Wisconsin.

The American Family Insurance Data Science Institute embodies the Wisconsin Idea, that the impacts of UWMadison must ripple beyond our classrooms and labs into the community, says Steve Ackerman, vice chancellor for research and graduate education. Data science is a high priority for campus because of its potential to move our cutting-edge research toward the goal of solving societys most difficult problems. The institute is actively leading work that brings people together to achieve this goal.

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Alteryx Global Inspire 2021 Conference to Showcase New Products and Innovations in Analytics and Data Science – Yahoo Finance

Luminary Thought Leaders Fareed Zakaria, will.i.am, Billy Beane and DJ Patil Join Alteryx Executives to Headline Inspire 2021

IRVINE, Calif., April 6, 2021 /PRNewswire/ -- Alteryx, Inc. (NYSE: AYX), a leader in analytic process automation (APA) that automates analytics, data science and processes to accelerate business outcomes, today announced its annual conference, Inspire, will take place May 18-21 and will be broadcasted across the U.S., EMEA and APAC. Virtual Global Inspire 2021, centered around the theme United We Solve, includes participation from thousands of citizen analysts, data scientists and business leaders from across the globe. Luminaries and industry experts will discuss the state of the market, the role of analytics in digital transformation, ethics in artificial intelligence (AI) and the future of analytics and data science in a post-pandemic world.

Alteryx logo (PRNewsfoto/Alteryx, Inc.)

"Inspire has always been a roaring success, and this year, it will be the biggest global experience we've hosted. Our global conference is designed to educate and unite our customers, partners and the global analytics community around our mission to enable every person to transform data into a breakthrough," said Mark Anderson, chief executive officer of Alteryx. "This year's conference will feature numerous innovations, all of which will be focused on enhancing cognitive diversity and fostering collaboration to solve some of the biggest challenges of our time with data science and analytics automation."

The three-day event centers around several core themes: Innovation to Transformation, Analytics and Data Science Automation for Breakthrough Outcomes and Learning and Community. The event will feature industry-leading voices global thought leaders, business leaders, data science experts and select Alteryx executives, including:

Fareed Zakaria, journalist, political commentator and author of "Ten Lessons for a Post-Pandemic World"

Dr. DJ Patil, former chief data scientist of the United States Office of Science and Technology Policy

Dr. Hannah Fry, associate professor in the Mathematics of Cities at the Centre for Advanced Spatial Analysis at University College London

will.i.am, musical artist, producer, actor and entrepreneur

Billy Beane, executive vice president of baseball operations for the Oakland A's and subject of Moneyball

Jake Porway, machine learning expert and co-founder and executive director of DataKind

Alteryx Executives: Mark Anderson, Sharmila Mulligan, Suresh Vittal, Matthew Stauble, Alan Jacobson and Olivia (Libby) Duane Adams

"Inspire is the premiere analytics automation event that brings together organizations and people of all skillsets to leverage analytics and data science for transformational business outcomes," said Sharmila Mulligan, chief strategy and marketing officer of Alteryx. "This year, we will announce major innovations across analytics automation, data science, machine learning and AI and the Alteryx Community platform. Attendees will also hear from Alteryx customers and a host of new strategic partners that are an integral part of our fast-growing partner ecosystem."

Story continues

Across three days and 100-plus product and innovation sessions, thousands of global attendees will come together to learn and share successes and solutions geared toward improving the global economy and society. The event also includes training and product sessions, interstitial segments, a live news desk and the Alteryx Grand Prix, a highly popular competition designed for the most advanced Alteryx users who will compete to solve a series of analytics challenges.

For more information about Virtual Global Inspire 2021, please visit inspire.alteryx.com and please register here to attend.

About AlteryxAs a leader in analytic process automation (APA), Alteryx unifies analytics, data science and business process automation in one, end-to-end platform to accelerate digital transformation. Organizations of all sizes, all over the world, rely on the Alteryx Analytic Process Automation Platform to deliver high-impact business outcomes and the rapid upskilling of their modern workforce. For more information visit http://www.alteryx.com.

Alteryx is a registered trademark of Alteryx, Inc. All other product and brand names may be trademarks or registered trademarks of their respective owners.

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The 9 Best Data Wrangling Courses and Online Training for 2021 – Solutions Review

The editors at Solutions Review have compiled this list of the best data wrangling courses and online training to consider.

Data wrangling is the process of cleaning, structuring and enriching raw data into the desired format. The practice has become increasingly important as data volumes and varieties continue to grow larger. Data wrangling typically involves six iterative steps, including data discovery, structuring, data cleaning, data enrichment, data validation, and publishing. The end-result of this time-consuming process is curated data sets that are easy to access, analyze and generate insights from.

With this in mind, weve compiled this list of the best data wrangling courses and online training to consider if youre looking to grow your data management or analytics skills for work or play. This is not an exhaustive list, but one that features the best data wrangling courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well. Click Go to training to learn more and register.

Platform: Coursera

Description: This course allows you to apply the SQL skills taught in SQL for Data Science to four increasingly complex and authentic data science inquiry case studies. Students will learn how to convert timestamps of all types to common formats and perform date/time calculations. Youll also select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls.

Related path/track: Process Data from Dirty to Clean

Platform: DataCamp

Description: The real world is messy and your job is to make sense of it. Toy datasets like MTCars and Iris are the result of careful curation and cleaning, even so, the data needs to be transformed for it to be useful for powerful machine learning algorithms to extract meaning, forecast, classify, or cluster. This course will cover the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Related path/track: Interactive Data Visualization with rbokeh

Platform: Edureka

Description: Edurekas Machine Learning Certification Training using Python will help you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Nave Bayes, and Q-Learning. This module will also help you understand the concepts of statistics, time-series, and different classes of machine learning algorithms like supervised, unsupervised, and reinforcement algorithms.

Related path/track: Data Science Certification Course using R

Platform: edX

Description: This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Related paths/tracks: Excel for Everyone: Data Analysis Fundamentals, Excel for Everyone: Data Management, Data Science: R Basics, Data Analytics Basics for Everyone, Learning Analytics Fundamentals, Data Science: Wrangling

Platform: Experfy

Description: This course will teach you from start to finish how to get your data into R efficiently and polish it up so that it is as good as it can be. This will let you or your team focus after this step on the statistical modeling, visualization, reporting, sharing, or any other post-processing task you wish to perform. Confidence, reliability, and reproducibility in your data acquisition and preparation are the kingpins to being able to maximize your datas value.

Related paths/tracks: Data Pre-Processing, Data Curation for Decision Making

Platform: LinkedIn Learning

Description: In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibblestransforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wranglingthe data cleaning and data transformation tasks that consume a substantial portion of analysts time.

Related path/track:R Essential Training: Wrangling and Visualizing Data

Platform: Pluralsight

Description: This course, Data Wrangling with Python, is aimed at helping you do exactly that. First, youll see how to merge data from different sources using the methods concat, append, and merge. Next, youll discover how to combine data into groups. The primary function used here is groupby. In the next two sections, youll explore how to transform and normalize data. Youll learn why these processes are necessary, and then proceed to see how they work in practice.

Related paths/tracks: SQL Data Wrangling in Oracle: Table Data, Data Wrangling with Pandas for Machine Learning Engineers

Platform: Udacity

Description: Advance your programming skills and refine your ability to work with messy, complex datasets. Youll learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Finally, youll learn to use your data skills to tell a story with data.

Related paths/tracks: Predictive Analytics for Business, Data Wrangling with MongoDB, Learn Spark

Platform: Udemy

Description: This course enables learners to acquire the knowledge and statistical data analysis wrangling and visualization skills that are most important. The module will take you (even if you have no prior statistical modeling/analysis background) from a basic level to performing some of the most common data wrangling tasks in Python. It will also equip you to use some of the most important Python data wrangling and visualization packages such as seaborn.

Related paths/tracks: Data Wrangling in Pandas for Machine Learning Engineers, Complete Data Wrangling & Data Visualisation in R

Tim is Solutions Review's Editorial Director and leads coverage on big data, business intelligence, and data analytics. A 2017 and 2018 Most Influential Business Journalist and 2021 "Who's Who" in data management and data integration, Tim is a recognized influencer and thought leader in enterprise business software. Reach him via tking at solutionsreview dot com.

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CrowdAI Unveils New Platform for Customized Computer Vision Models and Announces a Series A Round of Financing – PRNewswire

SAN FRANCISCO, April 8, 2021 /PRNewswire/ -- CrowdAI, the leading platform to build customized vision AI, today announced the launch of their next-generation AI platform, which enables anyone to create high-quality solutions to analyze imagery and video. CrowdAI also announced it has raised over $10 million to support the launch of its platform - most recently via a Series A led by Threshold Ventures. Other participating investors include Susa Ventures, Ron Conway's SV Angel, Jerry Yang at AME Cloud, and Y Combinator. With this round, Mohammad Islam, Partner at Threshold Ventures, joins the company's Board of Directors.

CrowdAI provides custom computer vision solutions to customers in the manufacturing, property insurance, finance, and technology markets, and works extensively with the U.S. government. The company's initial platform focused on cutting the time-to-value for custom computer vision projects in half for developers and data scientists familiar with AI integrations and workflows.

With CrowdAI's new platform, no data science background or coding is required to make data-driven operational decisions. The full-stack solution provides all the tools necessary to go from raw pixels to structured insights relevant to a user's specific needs. CrowdAI provides the support and strategy for determining if and how to implement an AI solution into the enterprise.

CrowdAI has developed a powerful product that not only makes computer vision widely accessible, but also enables more intelligent automation in theenterprise," said Mo Islam, Partner, Threshold Ventures. "We were immediately impressed with Devaki and the team and are excited to support the company on its journey to becoming the leading visual AI platform."

CrowdAI offers both a free, web-based version, as well as a subscription version with custom enterprise-based assets. The new platform allows anyone within an organization to tap into the benefits of intelligent automation. Technology advancements in the enterprise, including artificial intelligence and smart technology, have pushed the market forward over the last few years. Despite security and privacy concerns, artificial intelligence continues to prove to be a critical asset if implemented correctly and efficiently. CrowdAI has seen a 200% increase in its customer base in the past year, indicating a broader shift in the industrial and large commercial sectors towards more intelligent automation.

"At CrowdAI, we work alongside managers, engineers, marketers, and data scientists at every level to learn how our tools and AI workflows can make an impact in their organization," said Devaki Raj, CEO and founder of CrowdAI. "Our goal is to empower the workforce to better understand how AI can help them do their job. I'm incredibly proud of the team for what we've built. With our new, next-generation platform, we're able to make vision AI approachable and intuitive to anyone in the enterprise."

CrowdAI is currently being utilized by numerous organizations throughout the government, the education sector, and the technology industry. CrowdAI's vision is to lead the next industrial transformation with AI by empowering anyone to create and deploy custom AI solutions for maximizing value from visual data.

About CrowdAICrowdAI, the leading platform to build customized vision AI, enables anyone to create high quality solutions to analyze imagery and videono data science background or coding required. Our full-stack solution provides all the tools necessary to go from raw pixels to structured insights relevant to your specific needs. With CrowdAI, you can build your own vision AI bespoke to your specific needs, without writing a single line of code.

Based in San Francisco, the company was founded in 2016 and is backed by leading Silicon Valley venture capital, including Threshold Ventures, Susa Ventures, and Y Combinator.

Media Contact:Cliff Massey[emailprotected](818) 208-4443

SOURCE CrowdAI

https://www.crowdai.com

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Graphistry and Pavilion Partner to Accelerate Graph Analytics Using RAPIDS and NVIDIA GPUs – Business Wire

SAN JOSE, Calif.--(BUSINESS WIRE)--Pavilion Data Systems, the universally unmatched leader in data storage, announced today its partnership with Graphistry to support large-scale, multi-GPU, and NVIDIA Magnum IO GPUDirect technologies to supercharge how data analysts investigate event and entity data.

Pavilion and Graphistry will showcase their joint capabilities at NVIDIA GTC in session # SS33029 - Visually Investigating Patterns in Logs at Scale with Graphistry, RAPIDS, and Pavilion - using the most performant, dense, scalable, and flexible data storage platform in the universe.

Attendees will learn how to make big log volumes (including multi-petabytes) easily explorable by simple low-coding of GPU and graph interfaces. The session will walk attendees through how Graphistry has integrated friendly data UI tools like Jupyter notebooks, Streamlit dashboards, and Graphistry visual analytics with the NVIDIA RAPIDS GPU ecosystem (Dask_cuDF, GPU Direct storage, DGX A100) and with the Pavilion HyperParallel Data Platform. The combined result is attendees will learn how to adapt their existing familiar workflows to a style where they can now see and explore their entire dataset.

The presenters will also provide recommendations to optimize log collection and GPU storage optimization while guiding attendees regarding how they can run and fork the open-source reference architecture providing attendees with new insights that will be shared with the RAPIDS accelerated data science community.

There are just a few visualization tools that take full advantage of NVIDIA GPUs with Magnum IO GPUDirect to deliver real-time graph analytics across petabytes of incoming and stored data. Graphistry's breakthrough software and pipeline technology, combined with NVIDIA GPUs and Magnum IO GPUDirect along with Pavilion's universally unmatched storage, enable the next generation of interactive visualization for incident response, SIEM optimization, and threat hunting across market segments, including financial services, federal agencies, and data science.

Historically, teams have been excited to analyze logs at speed-of-thought by trying GPU acceleration, but bigger-than-memory datasets have always been difficult to connect to, said Leo Meyerovich, CEO and founder of Graphistry. Now that we can connect GPUs to Pavilion's HyperParallel Data Platform, we can automatically keep the GPUs running at high rates on large data sets without waiting on the storage tier, so analysts can focus more on investigating and less on massaging queries.

Just about every enterprise has a vast ocean of data at its fingertips, and most companies need a way to process those volumes of data into insights more quickly so that they take action, said Rob Davis, Vice President of Storage Technology at NVIDIA. Running data science workloads on analytics solutions like Graphistry with multiple NVIDIA GPUs powered by NVIDIA MagnumIO GPUDirect storage enables enterprises to effectively leverage high-performance storage and process massive amounts of data at scale.

The Pavilion HyperParallel Data Platform can hold over 2 petabytes of usable capacity in 4 rack units, making it an ideal fit for data-intensive applications like Graphistry, said Costa Hasapopoulos, Field Chief Technology Officer of Pavilion. With Graphistry bringing automated queries across Splunk, Elasticsearch, Apache Spark, and CSVs, delivering the highest fidelity at scale requires NVIDIA GPUs and Magnum IO GPUDirect to enable analysts to visualize key relationships, patterns, and anomalies in real-time.

To learn more about the solution with Graphistry and Pavilion, see the latest blog.

Pavilion is also presenting three other sessions at GTC21, including with partner OmniSci, as the two companies jointly showcase the power of Accelerated Analytics within a Data Science Platform. It is GTC # SS33294. You can also read the blog - How to respond to rapidly scaling Geospatial-Intelligence with OmniSci and Pavilion.

Attendees looking to understand how to virtualize, share and aggregate GPUs will find this session of particular interest: GTC # SS33026 and associated blog - How High-Performance NVMe-oF Storage Accelerates CPU & GPU-Powered Virtualized Environments Demonstrated by Pavilion.

Attendees wanting to understand the competitive advantage of a multi-controller, parallel architecture will find this session quite informative: GTC # SS33030 and associated blog - How a multi-controller storage architecture shatters expectations for modern applications.

About Pavilion

Pavilion shatters customer expectations and resulting organizational outcomes by revolutionizing data processing for modern AI/ML, HPC, Analytics, Enterprise Edge, and other data-driven applications. The Pavilion HyperParallel Data Platform, powered by Pavilion HyperOS, delivers unmatched performance and density, ultra-low latency, unlimited scalability, and flexibility, providing customers unprecedented choice and control. Learn why Fortune 500 companies and federal government agencies choose Pavilion. Visit http://www.pavilion.io or follow the company on LinkedIn.

About Graphistry Inc.

As a spinout of UC Berkeleys Parallel Computing Lab, Graphistry, Inc. is supercharging how organizations interact with their data. Powered by NVIDIA GPUs, Graphistrys investigation platform creates visual fast paths through complex investigations by transforming diverse data into interactive graphs that visually answer complex questions like correlations, scope, progression, root cause, patterns, and outliers. Ideally suited for investigations in areas like cybersecurity incident response, threat hunting, retail anti-fraud, and anti-money laundering, Graphistry enables analysts to find hidden connections, pivot on the fly easily, and share their findings with other teams. Graphistry, Inc's investors include Bloomberg Beta, Nvidia, In-Q-Tel, Greylock Partners, and angel investors, including Prof. Kurt Keutzer (UC Berkeley, ex-CTO Synopsys), Andy Chou (founder & ex-CTO Coverity), and Patrick OMalley (CFO Seagate). The company's headquarters are in San Francisco, California, with a satellite team in Austin, Texas. More information can be found at http://www.graphistry.com.

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TetraScience and IDBS Partner to Connect Data in R&D – PRNewswire

BOSTON and GUILDFORD, United Kingdom, April 7, 2021 /PRNewswire/ --TetraScience, the world's first and only open R&D Data Cloud for scientific discovery, and IDBS, a leading R&D technology and solutions provider, announce a strategic partnership to integrate the IDBS E-WorkbookTMand Tetra Data Platform into a common ecosystem to provide end-to-end R&D data automation.

This partnership provides seamless connectivity between instrumentation and informatics solutions in life sciences R&D to enable the automatic collection, centralization, and harmonization of data in the Cloud. Users will benefit from bidirectional instrument control that streamlines workflows and enhances laboratory connectivity.

"E-WorkBook is a market-leadingplatform for the planning, execution, and reporting of scientific workflows across the R&D value chain. With over 30 years of expertise, IDBS understands the need for seamless integration of our platform within a customer's ecosystem of laboratory instruments, informatics tools and data pipelines. However, it is no longer enough to simply improve laboratory efficiency or intra-lab collaboration; our customers are demanding easy access to well-managedand contextualized data to power advanced analytics that accelerate the pace of innovation. This partnership will dramatically improve systems' interoperability and will offer the best possible digitization experience to mutual customers of IDBS and TetraScience", notes Scott Weiss, VP of Product Strategy, IDBS.

This partnership will help save time in the lab, enabling scientists to focus more on drug discovery. TetraScience and IDBS are committed to creating FAIRdata to encourage the growth of biopharma collaborations and innovations.

"As an open platform, TetraScience has built a large network of integrations, partners, and best-of-breed solutions to drive the future of life sciences R&D. We are committed to connecting every single data source and target in the biopharma R&D lab landscape, to accelerate innovation and scientific discovery," says Siping "Spin" Wang, CTO and President of TetraScience. "We are delighted to welcome IDBS as a valued member of the Tetra Partner Network."

"In order to unlock the potential of life science R&D labs and dramatically accelerate discovery, we must capitalize on the power of AI and data science. A precondition to enabling these capabilities is moving the industry away from a legacy data model of silos and point-to-point integrations, to a native and unified cloud-based data paradigm," explains Patrick Grady, Chief Executive Officer, TetraScience. "Our partnership with IDBS is an example of what can now be done to enable the life sciences industry to accelerate discoveries that can help improve lives."

About IDBS

IDBS helps research and development (R&D) teams around the world make discoveries that have the potential to transform the lives of populations worldwide. Our diverse customer list includes 22 of the top 25 global pharmaceutical companies, and other R&D-driven organizations in biotechnology, agricultural sciences, chemicals, consumer goods, energy, food and beverage, and healthcare serving over 50,000 researchers in 25 countries. Privately held since 1989, IDBS joined Danaher's Life Sciences platform at the end of 2017. IDBS will help provide the foundation for a portfolio of life sciences informatics and knowledge management solutions, within Danaher, that will accelerate the speed of discovering, developing, and producing new drugs and therapies. To learn more, visit http://www.idbs.com.

About TetraScience

TetraScience is the leading global R&D Data Cloud company with a mission to transform life sciences R&D, accelerate discovery, and improve human life. The TetraScience R&D Data Cloud provides life sciences companies with the flexibility, scalability, and data-centric capabilities to enable easy access to centralized, standardized, and actionable scientific data and is actively deployed across enterprise pharma and biotech organizations. As an open platform, TetraScience has built the largest integration network of lab instruments, informatics applications, CRO/CDMOs, analytics, and data science partners, creating seamless interoperability and an innovation feedback loop that will drive the future of life sciences R&D. For more information, please visit tetrascience.com.

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Data Science Platform Market 2021 Industry Challenges Business Overview And Forecast Research Study 2025 | IBM Corporation,BRIDGEi2i Analytics…

Global Data Science Platform Market Research Report Covers, Future Trends, Size, Share, Past, Present Data and Deep Analysis, And Forecast, 2021-2027 market published by Adroit Market Research provides a close watch on current market trends, opportunities, and revenue growth. The report on the Data Science Platform market through its overview section facilitates qualitative analysis of estimation and dynamics of prevailing market opportunities during the forecast period. The report is curated into understandable formats. Experts have included pie charts, data tables, illustrations, and other stats charts to enable users to understand the market patterns easily.

The Data Science Platform market research report provides a complete analysis of the fundamental information about the market overview, market size, and market growth prospects that are impacting the growth of the market. Moreover, this report offers broad information about the technological expenditure over the forecast period which offers a unique perspective on the global Data Science Platform market across several segments covered in the report.

The Worldwide Global Data Science Platform Market is deliberately investigated in the report while to a great extent focusing on top players and their business strategies, geological extension, market sections, serious scene, assembling, and estimating and cost structures. Each segment of the exploration study is exceptionally set up to investigate key parts of the Data Science Platform market. For example, the market elements area dives profound into the drivers, limitations, patterns, and chances of the Data Science Platform market.

Top Key Players Profiled in this report are: Major Companies CoveredIBM CorporationBRIDGEi2i Analytics Solutions Pvt. LtdSAS InstituteInc.KNIME AGDataikuAnacondaIncMicrosoft CorporationWNS Global Services Pvt. Ltd.TIBCO Software India Pvt. LtdClouderaInc.H2O.aiWolfram ResearchRapidMinerInc.AlteryxInc.Teradata CorporationDomino Data LabInc.GoogleInc.

Besides presenting notable insights on Data Science Platform market factors comprising above determinants, the report further in its subsequent sections of this detailed research report on Data Science Platform market states information on regional segmentation, as well as thoughtful perspectives on specific understanding comprising region specific developments as well as leading market players objectives to trigger maximum revenue generation and profits.

In addition to all of these detailed Data Science Platform market specific developments, the report sheds light on dynamic segmentation as well as optimum understanding on primary and secondary research proceeding further with in-depth SWOT and PESTEL analysis to guide optimum profits in Data Science Platform market. This section of the report specifically illuminates the core functional areas and various data compilation and triangulation practices followed by research experts to derive vital statistical inference specific to the growth story of the target market.

Global Data Science Platform market is segmented based by type, application and region.

Based on Type, the market has been segmented into: Major Types CoveredOn-PremisesOn-Demand

Based on application, the market has been segmented into: Major Applications CoveredBFSIRetailHealthcareITTransportationEnergy and utilitiesGovernment and defense

It offers an analysis of changing competitive scenario.

For making informed decisions in the businesses, it offers analytical data with strategic planning methodologies.

It offers seven-year assessment of Data Science Platform Market.

It helps in understanding the major key product segments.

Researchers throw light on the dynamics of the market such as drivers, restraints, trends, and opportunities.

It offers regional analysis of Data Science Platform Market along with business profiles of several stakeholders.

It offers massive data about trending factors that will influence the progress of the Data Science Platform Market.

1. What will be the Market Size and Growth Rate in the forecast year?

2. What are the Key Factors driving Data Science Platform Market?

3. What are the Risks and Challenges in front of the market?

4. Who are the Key Vendors in Data Science Platform Market?

5. What are the Trending Factors influencing the market shares?

6. What are the Key Outcomes of Porters five forces model?

7. Which are the Global Opportunities for Expanding the Data Science Platform Market?

Chapter 1: Data Science Platform Market Overview

Chapter 2: Economic Impact on Industry

Chapter 3: Market Competition by Manufacturers

Chapter 4: Production, Revenue (Value) by Region

Chapter 5: Supply (Production), Consumption, Export, Import by Regions

Chapter 6: Production, Revenue (Value), Price Trend by Type

Chapter 7: Market Analysis by Application

Chapter 8: Manufacturing Cost Analysis

Chapter 9: Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10: Marketing Strategy Analysis, Distributors/Traders

Chapter 11: Market Effect Factors Analysis

Chapter 12: Data Science Platform Market Forecast

Continued

About Us

Adroit Market Research is an India-based business analytics and consulting company incorporated in 2018. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a markets size, key trends, participants and future outlook of an industry. We intend to become our clients knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps.

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Data Science Platform Market 2021 Industry Challenges Business Overview And Forecast Research Study 2025 | IBM Corporation,BRIDGEi2i Analytics...

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The best in AI appointed at Norwich Research Park – The John Innes Centre

Scientists across Norwich Research Park are part of a major integrated UK research-industry programme led by The Alan Turing Institute, seeking out the best talent in AI and data science, developing bioscience leaders and supporting the UK economy.

The 600,000 Fellowship programme is funding six fellows to support life science researchers from the Earlham Institute, the John Innes Centre, Quadram Institute and The Sainsbury Laboratory. Each fellow has been paired with a project that could benefit from data science approaches.

The fellowships are funded through The Alan Turing Institutes AI for Science and Government Strategic Priorities Fund award and a strategic award from the Biotechnology and Biological Sciences Research Council (UKRI-BBSRC) to the Earlham Institute and John Innes Centre.

Data science uses complex machine learning algorithms to build predictive models. With the ever-increasing amount of data being produced from biological research, the projects will help drive forward AI research and innovation in the UK. Developing capability and capacity to bring together industry and academia, the fellowship programme aims for AI practices to be adopted by trades through inter-sector career paths.

The year-long collaborative research projects, fellows and lead Institutes include:

James Maas, John Innes Centre

Investigating plant development by exploiting the vast amount of data at our disposal to uncover patterns in gene regulation that aims to help understand genetic behaviour during flowering time an adaptive and agronomic trait of major importance for food security.

Bethany Nichols, John Innes Centre

A major challenge in crop research is to achieve a sufficient understanding of mapping the genotype to phenotype to design crops behaviour to sync with their environment. This project develops genetic and phenotypic resources in Brassicas through computational approaches to identify genetic regulators that control important developmental transitions.

Connor Reynolds, Earlham Institute

The circadian clock is life on earths internal molecular timer, orchestrating day/night cycles and seasonal changes. The project will explore the vital role of the circadian clock in developing gene expression and regulating genetic traits associated with fitness and survival to improve key crop species.

Vladimir Uzun, Earlham Institute

Current genegene and geneprotein interaction networks which are the cornerstone of fulfilling their biological function are very poorly characterised. This project aims to apply the latest developments in machine learning to reconstruct regulatory networks across human tissues in order to predict and quantify the functional impact of genetic variation.

Odin Manuel Moron Garcia, Earlham Institute and Quadram Institute

Environments spanning from the human gut to the open oceans, hundreds of thousands of large-scale metagenomes have accelerated our understanding of the genomic diversity of the prokaryotic world. This has also brought a deluge of genomic data and the pressing need to develop new data interpretation methods through phenotypic machine learning.

Ruth Veevers, The Sainsbury Laboratory

Developing deep learning computational models to detect plant pathogen immunity by rendering recognisable visual patterns to identify interacting proteins that trigger plant pathogen immunity responses, with increased accuracy of over 90%.

Professor Richard Morris, Group Leader at the John Innes Centre, said: This initiative is a fantastic opportunity to accelerate the application of AI across the Norwich Bioscience Institutes. We were excited to see such an excellent set of projects being put forward that demonstate the huge potential for and interest in AI at the institutes and were delighted to have attracted such outstanding fellows.

The fellows will receive specialist training from their host lab, latest training in state-of-the-art AI and data science from the Turing Institute and take part in a tailored mentoring programme. We hope that this initiative will strengthen our links with the Alan Turing Institute and promote the embedding of AI into our research to tackle key biological challenges.

Professor Neil Hall, Director of the Earlham Institute, said: Modern life science research produces huge amounts of data at an exponential rate. The only way to make sense of this magnitude and complexity is for biologists to upskill themselves in the latest data science techniques, which makes this initiative hugely exciting.

Its not just about learning how to use a computer; its about choosing the right tools and techniques to spot patterns and generate valuable biological information. Another key part of data science is how we manage and curate our data so that its accessible and useful for others carrying out their own research, which will also be a critical aspect of this partnership.

Professor Jonathan Rowe, Programme Director of Data Science For Science at The Alan Turing Institute, said: The amount of data being produced in biological research is only increasing data science techniques offer the opportunity to harness and utilise this data. The appointment of these new Fellows offers an exciting opportunity to combine the Turings expertise in machine learning and artificial intelligence with the knowledge of the Norwich Biosciences Institutes to help solve some of the real-world problems in bioscience.

Professor Ian Charles, Director of the Quadram Institute, said: AI will be a key component for the future of healthcare and the prediction and prevention of disease. It is great to see these fellowships bringing further expertise in the understanding and exploitation of the complex datasets that are generated by modern bioscience.

Professor Nick Talbot, Executive Director of The Sainsbury Laboratory says: AI is set to revolutionise life sciences research, enabling predictions to be made about complex biological questions, which can then be tested by experiment. This is hugely exciting for our investigations of plant immunity and crop diseases at The Sainsbury Laboratory. The Research Fellows funded by this initiative with The Alan Turing Institute will be true pioneers in applying AI to plant and microbial sciences, working across the Norwich Research Park

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The best in AI appointed at Norwich Research Park - The John Innes Centre

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Encryption Has Never Been More Essentialor Threatened – WIRED

Given the global nature of the internet, the decisions some countries make affect us all. Foreign powers have already stolen personal data tied to half of all Americans. In the last six months, weve seen devastating attacks on the servers of major companies and governments that continue to use unsecure email. The consequences of these attacks can play out over the course of a lifetime.

For most of human history, we have felt free to confide in one another about our families, our work, our hopes, and our fears. That sense of freedom comes from the knowledge that once our words left our lips, they werent recorded.

But if nothing online is private, and every conversation today is online, then no conversation is private. That would leave us with two choices: Either we communicate face-to-face, or we surrender any expectation that were alone.

Thats not a realistic way to live. We carry and check our phones from the moment we wake up to the moment we go to sleep. In an emergency, your phone is probably one of the first things youd grab.

Just because we have vastly improved the technology that lets us communicate with people far away doesnt mean our privacy should go away. Machines today might make it possible for someone else to see and hear what were doing and what weve said, but that doesnt mean they should.

Thats what makes end-to-end encryption so valuable. As complex and advanced as it is, the idea behind it is thousands of years old. Early cryptography made it possible for people to communicate securely, but only if they had already exchanged a secret key ahead of time.

But thats not practical in todays world. Exchanging secret keys with everyone you know ahead of time and tracking those keys yourself would be tedious at best. Modern technology has made this seamless. The end-to-end encryption WhatsApp uses automatically exchanges the key directly on the senders and recipients physical devices and nowhere else. Every single message has its own separate lock and key.

Its no surprise, then, that many technology companies have added end-to-end encryption, and that since the pandemic started, several more have scrambled to upgrade their systems to protect the growing volume of critical communication happening digitally.

Knowing that you can communicate confidentially beyond the sound of your voice matters. It makes it possible for doctors to see patients remotely, helps militaries protect operational secrets, supports people building businesses, and protects journalists bringing important information to light. It also makes it possible for us to have the most private conversations with the people we care about, confident that we can speak our mind to the people closest to us without fear that someone is listening in.

End-to-end encryption locks tech companies out of particularly sensitive information, and for good reason. In 2019, the Justice Department filed charges in a case where people connected to Saudi Arabia were allegedly spying on dissidents using internal access tools. With end-to-end encryption, even employees do not have the ability to access private messages, for any purpose. This has caused frustration with governments who want tech companies to provide private messages under legal process.

Some governments are honestly trying to fight crime and looking to the dramatic increase in technology in our lives as a potential source of new evidence. Their criticism is that end-to-end encryption makes it harder for law enforcement to find evidence of a crime, and harder for companies to monitor peoples calls and messages to refer to law enforcement. But this is looking at a problem in isolation. It was never possible or easy to access most peoples private conversations when they were happening physically instead of digitally. We should not assume that just because technology makes something easier to do, we should do it.

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Encryption Has Never Been More Essentialor Threatened - WIRED

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