We are excited to announce that Alberto Artasanchez, AI Intelligence Lab Director at Knowledgent, Part of Accenture, will be speaking alongside Mark Roy, Partner Solutions Architect at AWS, at the Data Science New York event taking place on January 23rd and 24th at the Westin in Jersey City, NJ! Continue reading Informationist Alberto Artasanchez to Speak at Upcoming Data Science New York Event
Our very own Informationist, Alberto Artasanchez, has been featured in KDnuggets for an article he authored, entitled “9 Reasons Why Your Machine Learning Project Will Fail.” Continue reading Informationist Alberto Artasanchez Featured in KDnuggets
IDC estimates that big data and advanced analytics will be a $200b market by 2020[i] . Revenue from ‘data-driven’ products will double revenue from traditional products for 1/3rd of the Fortune 500 according to New Vantage Partners’ latest executive survey. Fifty percent of the world’s GDP will be digitized within the next three years[ii]. The economy seems fully dependent on data-driven innovation – and companies are investing at break-neck speed. Continue reading Are You Getting Real Value from Analytics? Can You Prove It?
Rachel Sholder, Data Science Intern, Analytics and Visualization
Data analysis is the process of collecting, inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and then communicating your results to have the biggest possible impact. According to Merriam-Webster, a process is a series of actions or steps taken in order to achieve a particular end. While the “particular end” of data analysis might be a presentation to a client, my “particular end” I have been working towards achieving is a successful end to my summer internship. Continue reading Data Science 101: Three Takeaways from My Internship
Editor’s Note: This is the fifth post in our new series introducing our rockstar summer interns! This post is from Jack Hickey, Healthcare & Life Sciences Intern.
I am currently a student at Northwestern University and will be going into my junior year in the fall. At Northwestern, I am pursuing my Bachelor of Science in Chemical Engineering with a specialization in Environmental Engineering and Sustainability. As part of my engineering curriculum, I have taken many math and statistics classes such as Probability and Statistics, Multivariable Calculus, Linear Algebra, and one computer science class learning Python. Continue reading Meet the Interns: Jack Hickey, Healthcare & Life Sciences Intern
Editor’s Note: This is the second post in our new series introducing our rockstar summer interns! This post is from Rachel Sholder, Data Science intern for Health and Life Sciences.
I am excited to be working as a Data Science Intern at Knowledgent. I just completed my junior year at Lehigh University in Bethlehem, Pennsylvania, where I am pursuing a Bachelor’s Degree in Mathematics with a Probability and Statistics concentration (along with a minor in Actuarial Science and a minor in Psychology). Continue reading Meet the Interns: Rachel Sholder, Health and Life Sciences Data Science Intern
In case you missed it, Knowledgent’s Data Scientist Dr. Mitchell Shuster recently served as a panelist on a round table webinar. Titled “The Business Potential of Machine Learning and Cognitive Computing,” the webinar featured expert insights on the next phase of machine learning, including deep learning, analytics, and cognitive computing.
“Machine learning and cognitive computing are becoming a critical portion of our technology infrastructure,” said Mitchell. “As with the rise of the Internet and social media, businesses that embrace these technologies will reap tremendous rewards and gain significant competitive advantage over those who fail to adapt to the changing landscape.”
Here are our major takeaways from the webinar: Continue reading “Beware the Hype!” And 4 Other Lessons in Machine Learning
What questions should I be asking to get the most out of my data with machine learning? What are best practices for using machine learning in my organization?
Our own Informationist and Data Scientist Mitchell Shuster will be tackling these questions and more on an IEEE-sponsored round table webinar tomorrow. Titled “The Business Potential of Machine Learning and Cognitive Computing,” this webinar will cover the next phase of machine learning, including deep learning, analytics and cognitive computing. Click here to register for the webinar.
Prior to the webinar, I sat down with Mitchell to talk about the hype and reality around machine learning: Continue reading Q&A: Mitchell Shuster on Machine Learning Hype vs. Reality
Our client, a global biotechnology organization, was struggling to perform basic-level analysis and script analysis. They also needed to build patient timelines to understand treatment pathways and disease progression across their product portfolio and areas of interest.
To accomplish these goals, they wanted to use big data analytics to leverage real-world evidence and observational medical outcome information. The insights gleaned from this data would support commercial and clinical operations, medical affairs and, ultimately, expand coverage to drug safety (and resource and learning development). Continue reading Case Study: How a Global BioTech Organization Leveraged RWE to Enhance Commercial and Clinical Operations
Editor’s Note: This week, we’re launching our new series: “Ask the Informationist.” Every month, one of our Informationists will answer relevant and thought-provoking questions on a wide range of topics in data and analytics. Continue reading Ask the Informationist: 5 “New” Types of Advanced Analytics