This Week in Data Preparation (June 15, 2020)
In this week’s post: 5 opinion articles (in Forbes, Dataconomy, BBN Times, GCN, and SD Times), 2 capital raise announcements (by SuperAnnotate and Hyperscience), and 1 survey report by IDC.
Douglas McDowell, Chief Strategy Officer for SentryOne, discusses business-driven data science. “By integrating data science more deeply into the business, and by developing a better working understanding of how data science works, including the CRISP-DM model, business people can be more effective partners and drive their data initiatives forward.” McDowell explains, in this article for Forbes.
Paul Christianson, VP of Client Success at CloudFactory, shares his insights on applying AI solutions at the startup, growth and enterprise stages. “At any stage of growth, it’s important to understand how to strategically combine people, process, and tools to maximize data quality, optimize worker productivity and limit the need for costly re-work”, Christianson comments, in this article for Dataconomy.
Naveen Joshi, founder and CEO of Allerin, discusses 5 Artificial Intelligence implementation challenges in Healthcare, with a view to help healthcare providers build appropriate strategies and quickly implement innovative solutions in a risk-free manner, in this article for BBN Times.
Robert Audet and Vasil Jaiani from Guidehouse LLP propose 5 tactics for data leaders during the pandemic. “Now is the time to refresh the data strategy and define tangible steps to ensure data quality, reduce time to get actionable insights, share data with external stakeholders and increase data literacy”, they claim, in this article for GCN.
Naval Bal, Solution Architect at Matillion, describes the four stages of cloud data journey, along with considerations for moving forward along the path to a scalable cloud data infrastructure, in this article for SD Times.
SuperAnnotate, an AI data labelling startup, raises $3 million seed from Point Nine Capital. Labeled data is key to advances in self-driving cars, retail, healthcare and other industries, but it’s extremely tedious. In a press release, the startup says data preparation and engineering tasks consume over 80 percent of the time spent in most AI and ML projects, adding that the market for data annotation tools is expected to reach $2.57 billion by 2027. “Coming from academia and seeing the pains of labeling first-hand, we work overtime to make sure our users have the right tools and are connected with the right teams to successfully complete their computer vision projects with the highest detection accuracies,” explains Tigran Petrosyan, the startup’s CEO.
Hyperscience, a New York-based data automation startup, raises $60M in Series C Funding. “Enterprises everywhere are accelerating their adoption of automation amidst changing market dynamics and economic uncertainty,” says Peter Brodsky, co-founder and CEO of Hyperscience, in a blog post. “In short, we are well-positioned to become the world’s leading automation company, but we are just getting started.”
An IDC survey finds AI adoption being driven by improved customer experience, greater employee efficiency, and accelerated Innovation. “Early adopters report an improvement of almost 25 percent in customer experience, accelerated rates of innovation, higher competitiveness, higher margins, and better employee experience with the roll out of AI solutions. Organizations worldwide are adopting AI in their business transformation journey, not just because they can but because they must be agile, resilient, innovative, and able to scale” said Ritu Jyoti, program Vice President, Artificial Intelligence Strategies at IDC.
Thank you for taking the time to read our weekly post with news items from the data preparation market.
