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Snowflake Unveils Your Data Exchange Potential

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Data is at the core of every business irrespective of the field of activity it is engaged in. Business success depends on how effectively it uses its multiple kinds and copious amounts of data to interact with each individual constituent from employees and customers to vendors, business associates, influencers etc. Sharing and exchanging data efficiently at minimum cost is absolutely critical to your path to competitive advantage. Snowflake is a globally recognised expert across industries, small, medium and large in establishing data exchange and managing complex data sharing in a governed and secure way with minimal risk, cost, headache and delay that have plagued traditional methods. Thus your organisation will have the most modern data sharing ability to easily and quickly forge one-to-one, one-to-many, and many-to-many relationships to share data in new and imaginative ways reducing time to a level never before possible. Data exchange is the process of sending and receiving data in a manner that the information, content or meaning assigned to the data is not altered during the transmission.


Snowflake's IPO is a bet on companies using AI for everything

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Snowflake, the buzzy cloud computing company, just delivered the biggest software IPO ever by betting on a future in which all businesses increasingly rely on big data and AI to make decisions. Its stock began trading on Sept. 16 at $245 per share--more than double the $120 price Snowflake set the day earlier--giving it an opening valuation of $67.9 billion. The startup's main value proposition is that it makes it easier and cheaper for businesses to analyze data they've shelved away on the cloud--including the massive datasets needed to train machine learning algorithms. Because Snowflake structures its software differently, it can run resource-intensive AI programs more efficiently than its competitors, including juggernauts like Amazon's AWS and Microsoft's Azure. "Snowflake is very important because they can challenge the Amazon AWS power," said Per Roman, managing partner and co-founder of investment firm GP Bullhound.


AI And Machine Learning Tech Pioneer Dataiku Scores $100M In Series D Financing

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Enterprise AI and machine learning platform developer Dataiku has raised $100 million in a Series D round of financing, the company said Monday. The funding round was led by Stripes, a growth equity and services company focused on startups in the software and consumer products industries. New investor Tiger Global Management was a major investor in the round, joined by existing investors Battery Ventures, CapitalG, Dawn Capital, FirstMark Capital and ICONIQ. Dataiku's stated goal since its 2013 launch is to move AI and machine learning beyond lab experiments into widespread use within data-driven businesses. The company's Dataiku DSS (Data Science Studio) platform is used by data analysts and data scientists for a range of self-service machine learning, data science and data analytics tasks.


H2O.ai and Snowflake Integration Accelerates Enterprise AI Adoption

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MOUNTAIN VIEW, Calif., June 4, 2020 – H2O.ai announced the availability of H2O Driverless AI integration, a leading automatic machine learning (AutoML) platform, with Snowflake, the Cloud Data Platform. This new integration enables Snowflake users to easily build and deploy ML models. Driverless AI automates the time consuming and demanding data science and machine learning workflows such as feature engineering, model tuning and model selection to achieve the highest predictive accuracy within the shortest time. The seamless integration of H2O Driverless AI with the Snowflake Cloud Data Platform is another step towards democratizing AI for all and empowering every company to be an AI company. "H2O.ai and Snowflake are in a unique position to help our customers adapt in the rapidly emergent business landscape and win with artificial intelligence on the cloud," said Sri Ambati, CEO and Founder of H2O.ai.


Global Big Data Conference

#artificialintelligence

H2O.ai, the open source leader in artificial intelligence (AI) and machine learning (ML), today announced the availability of H2O Driverless AI integration, a leading automatic machine learning (AutoML) platform, with Snowflake, the Cloud Data Platform. This new integration enables Snowflake users to easily build and deploy ML models. Driverless AI automates the time consuming and demanding data science and machine learning workflows such as feature engineering, model tuning and model selection to achieve the highest predictive accuracy within the shortest time. The seamless integration of H2O Driverless AI with the Snowflake Cloud Data Platform is another step towards democratizing AI for all and empowering every company to be an AI company. "H2O.ai and Snowflake are in a unique position to help our customers adapt in the rapidly emergent business landscape and win with artificial intelligence on the cloud," said Sri Ambati, CEO and Founder of H2O.ai.


The unmistakable impact of AI on agencies Federal News Network

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We are using machine learning to control situations where there are a lot of variables. Data democratization means everyone has access to these data and tools. There are a ton of great tools out there that help folks who maybe aren't data scientists, but are data science-y and make better decisions at work. The growth of artificial intelligence and machine learning over the last few years is unmistakable. Agencies have realized the potential and real benefits of using the advanced technologies to improve decision making, analyze large databases and address mission challenges.


SodaStream deploys RPA, data warehouse, AI to streamline operations

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SodaStream, an Israeli manufacturer of fizzy drink devices, gained visibility in the U.S. and Europe as a healthy and environment friendly alternative to carbonated giants like Coca Cola. But soon after relocating from a controversial site in the occupied West Bank to a new facility in southern Israel, executives realised that the company is facing a new challenge: streamlining operations in order to stay competitive with low-cost manufacturer rivals from China while quenching a fast-growing thirst for its bubbly beverages. To rein in costs and make SodaStream's four manufacturing lines more efficient, executives decided to automate assembly lines with robots, computerise production, and connect all manufacturing processes under one control system. The multi-year project was aimed at boosting output to keep pace with 30 percent yearly sales surges, while utilising artificial intelligence, machine learning and cloud computing to get a better handle on optimising production. "We continued to grow rapidly and were packed with endless employees. The dining room was full. The production side was full. We knew that we wouldn't be able to allow ourselves to keep operating the same way… whether in terms of space, efficiency, or in terms of costs," said Kfir Suissa, chief operation officer at SodaStream, which was acquired by PepsiCo in 2018 for US$3.2 billion.


The More I Know about the Company Data Robot, the More I Like

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Until recently, I had heard of the company Data Robot, but I wasn't sure what they did. Due to a series of coincidental events, in the last two weeks, I have really gotten to know the company, and I'm finding the more I know, the more I like. This week, I learned the answer to that question when I attended Snowflake's "Data for Breakfast" in Boston and saw a speaker from Data Robot present – check out my blog post about it here. Essentially, you take your big data, put it in some storage area (like Snowflake), and point Data Robot's platform to it. Next, you specify your dependent variable, and your independent variables, and any other parameters (like transformations).


Snowflake furthers AWS integration with AI/ML certification

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Snowflake, a cloud data platform, is deepening its relationship with AWS to provide a seamless customer experience. The company recently achieved the Amazon Web Services (AWS) Machine Learning (ML) and Artificial Intelligence (AI) Competency status. The AWS Competency Program highlights AWS Partner Network (APN) members that have passed a rigorous audit of their security, architecture and customer adoption, and have exhibited proven success supporting customers in specialised solution areas. Achieving AWS Competency status in these categories differentiates Snowflake as an APN member that delivers highly specialised technical proficiency. This announcement is the latest example of Snowflake's relationship with AWS, which has yielded many important milestones for customers.


Snowflake Expands AWS Partnership, Achieves AWS ML, AI Competency Status

#artificialintelligence

As a testament to this, Snowflake recently achieved the Amazon Web Services (AWS) Machine Learning (ML) and Artificial Intelligence (AI) Competency status. The AWS Competency Program highlights AWS Partner Network (APN) members that have passed a rigorous audit of their security, architecture and customer adoption, and have exhibited proven success supporting customers in specialized solution areas. Achieving AWS Competency status in these categories differentiates Snowflake as an APN member that delivers highly specialized technical proficiency. This announcement is the latest example of Snowflake's relationship with AWS, which has yielded many important milestones for customers. Customers like Yamaha Corporation, the Japanese multinational enterprise with a wide range of products focused on sound and music, benefit from Snowflake's relationship with AWS.