AI deployments are steadily migrating to retail applications as commercial brands seek to get a better handle on supply chains along with marketing and sales.
Increased demand for embedded AI software used to guide those decisions is on the rise, benefitting early movers offering automation tools designed to inform decisions on logistics and marketing. Among them is U.K.-based Peak AI, which this week announced a $21 million Series B venture round, bringing its total investor funding to $43 million.
Tag: data-analytics
AI Tool emerges to accelerate COVID-19 Vaccines that battle new virus mutations
A growing list of global COVID-19 variants is prompting disease researchers to employ AI models trained using bioinformatics data to speed up vaccine development in the critical search to find improved vaccines that can effectively fight the virus mutations.
Read MoreIBM, Palantir partner on AI Apps
IBM and data analytics software vendor Palantir Technologies Inc. will release a cloud data platform in March designed to deploy AI-based applications built around Watson. The service, dubbed Palantir for IBM Cloud Pak for Data, will run on Red Hat OpenShift, enabling hybrid cloud deployments, the partners said Monday (Feb. 8). It also integrates Palantir’s Foundry operations platform designed to integrate data management with analytics.
Read MoreCloud data analytics service Phocas raises $34 million to grow AI, global footprint
Phocas Software‘s cloud data analytics tools might be best known in Australia, where they’re used by Thermo Fisher Scientific, Fiskars Royal Doulton, and Burson Automotive to streamline employee access to key financial data, but the company is planning to become more aggressive globally in 2021. Today, Phocas announced that it raised $34 million to bolster its AI capabilities and reach new customers across the world, while expanding its data tools to reach new verticals.
Read MoreAI to transform Healthcare of the future in the shadow of COVID-19
AI technologies are already in place in many retail stores and other industries, but a July 2020 study by chipmaker Intel Corp. found that 84% of the respondents — made up of 234 senior decision-makers inside U.S. healthcare organizations — have already deployed or expect to deploy AI within their healthcare operations. That’s up from a previous Intel study in 2018, when a little more than one-third of the respondents said they were using or planning to implement AI.
Read MoreDremio raises $135 million to help companies rapidly analyze data
Dremio, a startup offering tools to help streamline and curate data, today announced that it raised $135 million in series D funding at a post-money valuation of $1 billion. The company says it’ll use the funds, which come nine months after a $70 million round, to invest in cloud data lake technologies that could benefit businesses looking to connect, analyze, and process data while accelerating database queries.
Read MoreAI-based Recycler AMP Robotics gains $55M in new funding from Investors
AMP Robotics Corp., an AI startup developing technology that sorts recyclable materials, has raised an additional $55 million in its latest funding round. The Denver-based AI startup launched in 2015 has so far raised more than $71 million in two funding rounds.
Read MoreTrends in Data Science that will change Business Strategies
From individual skills to business development, data professionals have many opportunities in the next few years. Although there are many challenges ahead, the same research reported that more than half (52%) of companies and organisations are looking to foster a data-driven culture.
Read MoreData quality from First Principles
The right way to think about Data Quality, from Kimball and Uber’s points of view. If you’ve spent any amount of time in business intelligence, you would know that data quality is a perennial challenge. It never really goes away. For instance, how many times have you been in a meeting, and find that someone has to vouch for the numbers being presented?
Read MoreAI partners seek ‘Engine of Scientific Discovery’
A research effort built around an automation platform that connects data and analytics applications will focus on advancing the use of AI and machine learning in bioscience and medical applications.
Read MoreThe role of AI and ML in enhancing the ability of Multiplying Wealth
Landing a good job is generally considered the purpose of education today. But not everyone subscribes to that. American educator and businessman Stephen Covey, said, “Your economic security does not lie in your job; it lies in your own power to produce—to think, to learn, to create, to adapt. That’s true financial independence. It’s not having wealth; it’s having the power to produce wealth.”ce.
Read MoreIntroducing “Lux” for faster Data exploration
Most of the time spent by data scientists is in data cleaning , data exploration . A detail EDA (exploratory data analysis) is very much important and significant in the data science life cycle. In the year 2020 , there has been lot of automatic EDA libraries have been developed to save the time for the data scientist. Some of the most commonly used automatic EDA are listed in the following blog.
Read MoreUnderstanding the Data Analytics Life Cycle (DALC)
Industries are changed a lot since the data became the most popular ingredient to generate better insights. Be it eCommerce, Health Care, Transport-Logistic, or any. Companies are more inclined towards the data and identifying the consumer patterns to increase their revenue by investing money in different sources.
Read MoreStock trend prediction from News Sentiment
Companies sell their shares on the stock market, putting the company squarely in the public domain. While the impact on stock value has various causes and effects, a big factor in price change is the way a company is perceived. Sentiment from news can be used as an predictive indicator of trend. In tis article we give a brief overview of how we analyze sentiment.
Read MoreThe importance of monitoring Big Data analytics pipelines
In this article, we first explain the requirements for monitoring your big data analytics pipeline and then we go into the key aspects that you need to consider to build a system that provides holistic observability.
Read MoreGather your Data: The “Not-So-Spooky” APIs!
When python plays with the internet files. A data analytics cycle starts with gathering and extraction. In this blog, I’ll focus on extracting the data from files that are not so common but has the most real-world applications.
Read MoreReal Estate: Data as a competitive advantage
The past five months have exposed a worrying lack of resilience across traditional real estate. The juxtaposition between what is currently on offer and how people want to live, work and use space is undeniable.
Read MoreThe ultimate guide to relational operators in R
Relational operators help us see how objects relate to one another.
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