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Soda monitors data and helps you fix issues before it’s too late

Meet Soda, a data monitoring platform that is going to help you discover issues with your data processing setup. This way, you can react as quickly as possible and make sure that you keep the full data picture.
If you’re building a digital-first company, you and your customers are likely generating a ton of data. And you may even be leveraging that data to adjust your product itself — think about hotel pricing, finding the right restaurant on a food delivery website, applying for a loan with a fintech company, etc. Those are data-heavy products.
“Companies build a data platform — …

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Intermittently Connected IoT Devices for Logistics Quality Assurance

Illustration: © IoT For AllSupply chain stakeholders have extolled the virtues of data loggers for some time now, but most of the off-the-shelf options currently on the market are designed to be constantly connected to the Internet. Everything from RF interference to network strain can cause these devices to suddenly stop functioning, which is a serious issue for those who depend on them to provide needed information.Worst of all, most logistics companies that need this kind of technology aren’t able to afford such extravagances. Most of these firms would be better off with data loggers that only have …

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Blue Sky Compliance – Fixed Income

News surrounding the financial markets is often equity-focused, as the volatility and name recognition of stocks make for more interesting headlines.  However, today’s market professionals understand that fixed income markets dwarf equity markets in terms of size and importance. 

This paradigm is further evidenced when looking at OTC Market Group’s Blue Sky Compliance Data.  As Blue Sky rules for secondary trading apply to all securities not listed on a national exchange, our product covers key OTC fixed income products: Corporate Bonds and Equity Linked Notes along with the complete universe of OTC equities.  Within the Blue Sky Compliance …

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Python–The Perfect Language for Machine Learning

Illustration: © IoT For AllMachine Learning, in simple terms, is the ability of computers to learn on their own without the need to program new skills. Machine learning is really about advanced algorithms that, after processing certain data, can learn new things that can be very useful in making decisions. In turn, Python is one of the most popular high-level programming languages, which is characterized by high readability and clarity of the source code. Thanks to its clear and concise syntax, it is an ideal language for beginner programmers. The biggest advantages of the language are its simplicity, multiplicity of …

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ESG Impact Is Hard to Measure — But It’s Not Impossible

Around the globe, a third of all professionally managed assets, or roughly $30 trillion, are now subject to ESG criteria. That’s a remarkable sum, one that represents an increase of more than 30% since 2016. Between April and June of 2020 alone, investors poured more than $70 billion into ESG equity funds, vastly exceeding recent annual flows.
These numbers reflect a growing awareness — among companies, investors, and shareholders alike — that to remain viable, businesses must think about and manage their impact on the planet in new ways. Sustainability is the new aspiration, and the key to achieving it, according to a rapidly emerging consensus, …

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Gretel announces $12M Series A to make it easier to anonymize data

As companies work with data, one of the big obstacles they face is making sure they are not exposing personally identifiable information (PII) or other sensitive data. It usually requires a painstaking manual effort to strip out that data. Gretel, an early stage startup, wants to change that by making it faster and easier to anonymize data sets. Today the company announced a $12 million Series A led by Greylock. The company has now raised $15.5 million.

Gretel co-founder and CEO Alex Watson says that his company was founded to make it simpler to anonymize data and unlock data sets that were previously out of reach because of privacy concerns.

“As a developer, you want to test an idea or build a new feature, and it can take weeks to get access to the data you need. Then essentially it boils down to getting approvals to get started, then snapshotting a database, and manually removing what looks like personal data and hoping that you got everything,”

Watson, who previously worked as a GM at AWS, believed that there needed to be a faster and more reliable way to anonymize the data, and that’s why he started Gretel. The first product is an open source, synthetic machine learning library for developers that strips out personally identifiable information.

“Developers use our open source library, which trains machine learning models on their sensitive data, then as that training is happening we are enforcing something called differential privacy, which basically ensures that the model doesn’t memorize details about secrets for individual people inside of the data,” he said. The result is a new artificial data set that is anonymized and safe to share across a business.

The company was founded last year, and they have actually used this year to develop the open source product and build an open source community around it. “So our approach and our go-to-market here is we’ve open sourced our underlying libraries, and we will also build a SaaS service that makes it really easy to generate synthetic data and anonymized data at scale,” he said.

As the founders build the company, they are looking at how to build a diverse and inclusive organization, something that they discuss at their regular founders’ meetings, especially as they look to take these investment dollars and begin to hire additional senior people.

“We make a conscious effort to have diverse candidates apply, and to really make sure we reach out to them and have a conversation, and that’s paid off, or is in the process of paying off I would say, with the candidates in our pipeline right now. So we’re excited. It’s tremendously important that we avoid group think that happens so often,” he said.

The company doesn’t have paying customers, but the plan is to build off the relationships it has with design partners and begin taking in revenue next year. Sridhar Ramaswamy, the partner at Greylock, who is leading the investment, says that his firm is placing a bet on a pre-revenue company because he sees great potential for a service like this.

“We think Gretel will democratize safe and controlled access to data for the whole world the way Github democratized source code access and control,” Ramaswamy said.

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