Alternative Data News. 15, January 2020

The AltDataNewsletter by CloudQuant

Finding sources and uses for alternative data can be difficult. At CloudQuant we regularly read and search the internet for new sources of data that can be used in our mission to find alpha signals and build quantitative trading strategies. We recognize that we are technology and data junkies so we wrote our own crawler that specifically seeks out web pages, posts, and news articles that give us a snapshot of what is going on in the world of Alt Data. The following is a collection of articles that we think you will find interesting from the past week.

Nasdaq Trade Talks – Quandl – Future of Data-Driven Investing

Jill Malandrino is joined by Evan Reich, Head of Data Strategy & Sourcing at Quandl, and they discuss the future of data driven investing.  Quandlt Data Conference 2020 – NYC – January 23rd 2020 #QDC2020

2020-01-09 18:53:23+00:00 Read the full story…
Weighted Interest Score: 8.1633, Raw Interest Score: 2.7211,
Positive Sentiment: 0.0000, Negative Sentiment 0.0000

CloudQuant Thoughts : With Quandle now owned by Nasdaq, the Quandl Data Conference will certainly be one to watch.

Tech roles dominate Glassdoor’s list of 50 Best Jobs in America for 2020

Glassdoor’s list of the 50 Best Jobs in America is dominated by tech in 2020, with seven of the top 10 spots and nearly half of the complete list going to tech roles. The job search site based the list on three factors: median base salary, number of U.S. job openings, and overall job satisfaction reported on Glassdoor by actual employees in these roles.

Front end engineer is the so-called “best job” in America, replacing data scientist at No. 1, a job that held the top spot since 2016 and fell this year to No. 3.

2020-01-15 07:59:47+00:00 Read the full story…
Weighted Interest Score: 3.9911, Raw Interest Score: 2.9933,
Positive Sentiment: 0.5543, Negative Sentiment 0.0000

CloudQuant Thoughts : Has Data Scientist dropped from the top spot? Or has the job simply fragmented into a set of smaller roles?

2020: The Year of the Citizen Data Engineer

2019 was the year of the “citizen data scientist,” a term that refers to individuals who utilize data science practices and tools but whose training and primary role is not that of a data scientist. The explosion in data science initiatives across departments and job functions has stirred an increasing need for streamlined and scalable access to data, a function typically handled by data engineers.

Having a strong data engineering team is important in today’s world, and more companies are taking notice. Much of the work done by data scientists proves to be very difficult without the support of data engineers. The volume, velocity, and variety of data available to data scientists increases daily, and data engineers are fundamental to ensuring their success by creating scalable, reliable, and efficient systems for processing and delivering data. However, there are simply not enough data engineers to meet the demand. To fill this void, I predict 2020 will be the year of the “citizen data engineer.”

2020-01-10 00:00:00 Read the full story…
Weighted Interest Score: 3.7037, Raw Interest Score: 2.0812,
Positive Sentiment: 0.3807, Negative Sentiment 0.0508

CloudQuant Thoughts : The demand for (and therefor subsequent dearth of) fully qualified Data Engineers means there is an opening for less qualified people to enter smaller roles surrounding the data engineer.  Most firms have already identified this and are promoting from within to fill needs as they pop up. The Data Engineer role has been very well compensated so far and so there is plenty of scope for well paying roles in the supporting structure.

ICE Data Services to Offer ESG Reference Data on U.S. and International Companies

Intercontinental Exchange, Inc. (NYSE:ICE), a leading operator of global exchanges and clearing houses and provider of data and listings services, today announced plans to launch a new data service that is designed to help investors better assess the environmental, social and governance (ESG) risks and opportunities in corporations.

Increasingly, investors across the world are including ESG risk into their investment decisions, reflecting a view that companies that maintain good metrics in this area may generate stronger returns, deliver lower risk, and adhere to sound management principles. A report by BofA Global Research last September noted there could be over $20 trillion in asset growth in ESG funds over the next two decades, equivalent to the size of the S&P 500 today.

To meet this trend with actionable data, ICE Data Services is adding ESG terms and conditions data to its existing reference data offering for U.S. and international listed corporations. ICE Data Services’ customers will be able to subscribe to receive primary ESG data points, such as greenhouse gas (GHG) emissions reported, board diversity metrics, and nearly 500 other key metrics of ESG-related data. The dataset will be flexible, growing as ESG disclosure evolves.

2020-01-14 00:00:00 Read the full story…
Weighted Interest Score: 3.4991, Raw Interest Score: 1.8640,
Positive Sentiment: 0.2868, Negative Sentiment 0.0205

CloudQuant Thoughts : ESG is certainly the hot topic on the street and finding a worthwhile ESG data source is key for many firms. One of our services is supplying and validating Alternative Data Sets. These include a dataset from G&S Quotient for ESG. Head over to our data catalog to check it out.

StatsCan eyeing alternate data sources as chief says surveys just don’t cut it anymore

Canda’s chief statistician on Tuesday said the traditional ways of collecting information have become less effective in a more digital world, and that Statistics Canada is prepared to start harnessing more “alternate” sources of data.

Timely facts and data have never been more important, but conventional surveys are costly, take time and are seeing response rates decline, according to Anil Arora.

“Alternate sources of data are increasing exponentially, and we have the techniques and the mechanisms to convert them to public good with high-quality statistics,” Arora said during a speech to the Empire Club of Canada in Toronto. “Administrative sources, satellite imagery, cell phones, credit data and transactional data: they are all providing the opportunity to answer some of our deepest questions in our society and our economies.”

2020-01-14 00:00:00 Read the full story…
Weighted Interest Score: 3.4991, Raw Interest Score: 1.8640,
Positive Sentiment: 0.2868, Negative Sentiment 0.0205

New Statistics Course: Conditional Probability in R – Dataquest

Take your data science and statistics knowledge to the next level with the latest addition to our fast-growing Data Analyst in R learning path: Conditional Probability in R .

In this course, you’ll learn about the basics of conditional probability and then dig into more advanced concepts like Bayes’s Theorem and Naive Bayes algorithms. As you learn, you’ll be using your R skills to put theory into practice and build a working knowledge of these critical statistics concepts.
2020-01-14 17:11:23+00:00 Read the full story…
Weighted Interest Score: 5.3589, Raw Interest Score: 2.3817,
Positive Sentiment: 0.0331, Negative Sentiment 0.1985

Best Countries For Fixed Income In 2020

Unless you’re happy with junk bonds and 2% yield on ten-year Treasury debt, then the best place for fixed-income investors is outside of the advanced economies. That’s always been the case, but they have been avoided, for the most part, due to risk and the fact that quantitative easing made the U.S. the only game in town since 2009.

U.S. Treasury bond rates are expected to rise this year, so that’s positive for the local retail investor who is afraid about leaving the domestic front for unchartered land. But for more sophisticated individual investors, the only place to get paid in fixed income is down the credit scale at home, or buying bonds—or bond funds—holding the debt of foreign governments and corporations.

2020-01-10 00:00:00 Read the full story…
Weighted Interest Score: 4.8833, Raw Interest Score: 2.2486,
Positive Sentiment: 0.2625, Negative Sentiment 0.0685

Visa to acquire Plaid for $5.3 billion

Visa is to shell out $5.3 billion to acquire bank data sharing startup Plaid.

Plaid’s products enable consumers to conveniently share their financial information with thousands of apps and services such as Acorns, Betterment, Chime, Transferwise and Venmo. Today, one in four people with a US bank account have used Plaid to connect to more than 2,600 fintech developers across more than 11,000 financial institutions.

2020-01-14 09:15:00 Read the full story…
Weighted Interest Score: 4.6549, Raw Interest Score: 1.9663,
Positive Sentiment: 0.2006, Negative Sentiment 0.0000

Here’s why Visa made its bold play for buzzy fintech Plaid in a $5.3 billion mega-acquisition, despite knowing the risks

Visa, the world’s biggest payments provider, is set to acquire US payment infrastructure startup Plaid for $5.3 billion, in one of the largest acquisitions of a financial services startup to date and vindication for the buzzy fintech market.

Business Insider spoke to industry experts on what the deal means for both Visa and Plaid to see if the deal made sense, what it would mean, and how it could work.

Experts cited network effects as an advant…
2020-01-14 00:00:00 Read the full story…
Weighted Interest Score: 3.8396, Raw Interest Score: 1.3552,
Positive Sentiment: 0.1506, Negative Sentiment 0.1318

Visa Makes A Big Bet On Fintech With $5.3 Billion Plaid Acquisition

Visa (NYSE:V) said on Monday that it would acquire privately held Plaid, a leading financial technology provider, in a deal valued at $5.3 billion. Plaid’s platform helps consumers securely connect their financial accounts to the apps they use, while “helping them manage their financial lives,” Visa said in a press release.

The company said that the acquisition of Plaid represents both an entry into new businesses and complementary enhancements …
2020-01-14 22:37:58-05:00 Read the full story…
Weighted Interest Score: 3.6293, Raw Interest Score: 1.4702,
Positive Sentiment: 0.4127, Negative Sentiment 0.0000

Data Modeling Trends in 2020: A Year of Optimization

This next year demands quicker data-driven decisions, better automation, more integration, and more data, requiring optimized Data Modeling. Data Modeling refers to documentation describing core business rules and definitions around data. Business and technical shareholders benefit from Data Modeling by seeing complex data concepts in an intuitive, visual way.

Throughout 2020, Data Modeling will need to do more, faster, with less. Economic and political uncertainties will flatten IT spending while newer technologies process information at higher speeds. Add to this situation greater data volumes from a multitude of systems, including cloud computing and theInternet of Things (IoT). Plus, put in a low tolerance for activities that can cause bottle-necks and executives who want bold artificial intelligence results in automating business tasks. This leaves data modelers to solve the highest number of complex business problems, with the most data points in the shortest time frame.

2020-01-07 08:35:47+00:00 Read the full story…
Weighted Interest Score: 4.5878, Raw Interest Score: 2.8120,
Positive Sentiment: 0.2463, Negative Sentiment 0.0924

London Stock Exchange appoints Arne Staal as Head of Research and Product Management, ISD

In this newly created role, Arne Staal will lead the two complementary areas of the Information Services Division.

London Stock Exchange Group (LSEG) today announces the appointment of Arne Staal as Head of Research and Product Management, Information Services.

In this newly created role, Mr Staal will lead the two complementary areas of the Information Services Division, linking up research and thought leadership to product strategy and produc…
2020-01-06 15:19:18+02:00 Read the full story…
Weighted Interest Score: 4.3429, Raw Interest Score: 2.2286,
Positive Sentiment: 0.4571, Negative Sentiment 0.0571

Why responsible AI needs to disrupt your org from the bottom up (VB)

Black box AI has been getting some attention in the media for how it has produced undesirable, even unethical results. But the conversation is so much more complex, says Rumman Chowdhury, managing director at Accenture AI. When technologists or data scientists talk about black box algorithms, what they’re specifically referring to is a class of algorithms for which we don’t always understand how the output is achieved, or non-understandable systems.

“Just because something is a black box algorithm, it doesn’t necessarily mean it’s irresponsible,” Chowdhury says. “There are all sorts of interesting models one can apply to make output explainable — for example, the human brain.” This is why black box AI systems actually have an important relationship with responsible AI, she explains. Responsible AI can be used to understand and unpack a black box system, even if it’s inside that black box algorithm.

2020-01-15 00:00:00 Read the full story…
Weighted Interest Score: 4.2553, Raw Interest Score: 1.2244,
Positive Sentiment: 0.1807, Negative Sentiment 0.2007

The top 5 industries AI will affect the most

Artificial intelligence is one of the fastest moving and least predictable industries. Artificial Intelligence (AI) has the peculiar ability to simultaneously amaze, enthrall and intimidate. The possibilities of AI are innumerable and beyond the scope of our imagination.

Looking ahead to 2020, CIOs will need to better assess the value of their AI bots. And also prove that ROI to the business. By 2020 companies will become laser-focused on AI value. They’ll leap out of experimentation mode, and ground themselves in reality to accelerate adoption. AI has the potential to become the new operating system for the enterprise. “Over the last decade, organizations have been picking up AI know-how and started working with the technology. This year will be a tipping point for the infrastructure needed to support effective deployments, providing integrated learning environments and data ecosystems that support adaptive decision making by AI.

2020-01-14 09:21:09+00:00 Read the full story…
Weighted Interest Score: 4.1345, Raw Interest Score: 1.6999,
Positive Sentiment: 0.3245, Negative Sentiment 0.1854

Trading Technology in 2020 and Beyond

In this third blog in the Views on 2020 series from #Refinitiv, we look at how advances in trading technology have made financial markets more efficient in 2019, such as through rules-based automation or greater use of artificial intelligence. What are the #SmarterTrading trends set to enhance workflows in 2020 and beyond?

Advances in trading technology in 2019 delivered new solutions for streamlining processes, reducing costs and improving the customer experience.
A 2019 survey by Greenwich Associates found that 61 percent of respondents are either using artificial intelligence now or expect to be within 12-24 months.
Refinitiv trading workflow solutions include pre-trade research in Eikon, and at-trade and post-trade capabilities in Refinitiv REDI EMS, and our order management system, AlphaDesk.

2020-01-15 00:00:00 Read the full story…
Weighted Interest Score: 4.0608, Raw Interest Score: 1.9179,
Positive Sentiment: 0.4312, Negative Sentiment 0.1338

Agilence Introduces AI and All New Mobile Capabilities in Latest Software Release

According to a recent press release, “Agilence, Inc., the leading provider of predictive data analytics & reporting solutions to the retail, restaurant, and convenience industries, today announced it’s 2.8 release of the Agilence Data Analytics Platform. The release adds new Artificial Intelligence (AI) features and a dedicated app-based user experience to shorten the analytics learning curve for enterprise businesses. ‘Innovative retail & restaurant organizations are adapting to the evolving consu…
2020-01-15 08:10:07+00:00 Read the full story…
Weighted Interest Score: 3.5088, Raw Interest Score: 1.7005,
Positive Sentiment: 0.6034, Negative Sentiment 0.1097

How AI Is Helping The Gaming Industry And Its Key Players Thrive

In July, Towards Data Science published a compelling article on the state of AI in the modern gaming industry. The article highlighted how the role of AI in gaming has evolved over the years. As the range of games expands, AI will become more significant.

Make no bones about it – artificial intelligence (AI) is already delivering intelligent solutions for the thriving iGaming industry, helping to improve the trust of customers by providing fair and transparent gameplay for all.

AI might seem like the future, but it’s already having a transformational effect on the scene as we speak. Just like in several other sectors, there are many interesting trends occurring in the marketplace thanks to AI. Consider the following your proof that it’s not just Elon Musk that can have all the automated fun.

2020-01-07 07:00:16+00:00 Read the full story…
Weighted Interest Score: 3.4892, Raw Interest Score: 1.4409,
Positive Sentiment: 0.3051, Negative Sentiment 0.0339

The Norwegian National Strategy for Artificial Intelligence Has Launched!

This day is special to me, because I have been covering most of the AI strategies in Europe, and today my home country has released their own national strategy. The Norwegian national strategy was released on the 14th of January, the very day this article was written. I will attempt m…
2020-01-15 04:06:02.215000+00:00 Read the full story…
Weighted Interest Score: 3.2912, Raw Interest Score: 1.6105,
Positive Sentiment: 0.3277, Negative Sentiment 0.1000

Energy markets are in transition, and investors are retreating. Here’s why

While the stock market has boomed, energy stocks have not. Indeed, they have been the worst-performing sector over the last decade. Moreover, energy has dropped from 15% in 1990 to only 5% of the S&P 500 sector weightings in 2019. This is particularly ironic, since U.S. oil and gas production has boomed over the same period, making the United States the world’s largest producer of oil and gas — and making the country virtually self-sufficient.

2020-01-13 00:00:00 Read the full story…
Weighted Interest Score: 3.1567, Raw Interest Score: 1.6017,
Positive Sentiment: 0.1092, Negative Sentiment 0.1820

This PG Diploma By upGrad & IIIT-B Lets You Upskill In Data Science With 5 Specialisations To Choose From

The ‘teen’ decade saw data science transitioning from an industry buzzword to being adopted across various enterprises and applications on a giant scale. More and more Indian businesses are now using data science to understand how they can make their processes more efficient.

One of the key reasons behind this is also the generation of big data. As companies are becoming competitive and are wary of being left behind, this has driven the demand for professionals skilled in data science and analytics. The trend is clear — professionals who are skilled in data science are being rewarded, along with a rising emphasis on upskilling keeping data, artificial intelligence and machine learning in the centre.

As analytics and machine learning reach deeper into organisational operations, it can be clearly seen that there is significant disruption at the workplace with data scientists and data analysts preferring to experiment with newer tools. Skills are evolving and are constantly being aligned according to the industry standards and requirements.

2020-01-13 04:40:47+00:00 Read the full story…
Weighted Interest Score: 3.1364, Raw Interest Score: 2.0015,
Positive Sentiment: 0.3487, Negative Sentiment 0.0910

Ten 2020 Visions for Data Modelers

2020 is a nice number and sounds comforting. And it is about vision(s). Are there any foresights of importance for data modelers? Well, here are 10 suggestions. No warranties, I suggest you use them as lighthouses, hopefully plotting your course from 2020 onwards.

2020-01-13 08:35:04+00:00 Read the full story…
Weighted Interest Score: 3.1148, Raw Interest Score: 1.6734,
Positive Sentiment: 0.2391, Negative Sentiment 0.0580

BMLL names industry heavyweight Paul Humphrey as CEO

BMLL Technologies, the data engineering and analytics firm, today announced the appointment of Paul Humphrey as Chief Executive Officer.

A senior executive with decades of experience in leading positions across the brokerage, banking, data and exchange world, Paul Humphrey joins BMLL Technologies to drive the scale up of the business and realise the firm’s mission to democratise access to granular market data and analytical products at speed and scale.

2020-01-15 09:06:00 Read the full story…
Weighted Interest Score: 3.0615, Raw Interest Score: 1.3539,
Positive Sentiment: 0.2708, Negative Sentiment 0.1083

MLDS 2020: Top 10 Talks You Should Definitely Attend This Year

The second edition of the Machine Learning Developers Summit (MLDS 2020) has already started to create a significant excitement and buzz in the industry. The event, which is to be held on 22-23 Jan in Bengaluru and on 30-31 Jan in Hyderabad, is set to be one of the biggest gatherings of developers in India.

With over 1,500 attendees expected to attend the event, MLDS will see innovators from leading tech companies gathering together to discuss the latest software architecture of ML systems, producing and deploying the newest ML frameworks, addressing the challenges faced and more.
2020-01-09 13:30:00+00:00 Read the full story…
Weighted Interest Score: 3.0537, Raw Interest Score: 1.5435,
Positive Sentiment: 0.2715, Negative Sentiment 0.1858

Top Paper Presentations You Must Not Miss At MLDS 2020

Just a few days away now, Machine Learning Developers Summit, which is to be held on 22-23 Jan in Bengaluru and on 30-31 Jan in Hyderabad, has created a buzz around the tech community. With MLDS, Analytics India Magazine aims to bring in researchers and innovators together on one platform, where they will be presenting their research papers on various topics like machine learning, deep learning, and robotic process automation (RPA).

In this article, we list down the top paper presentation at MLDS that the attendees should not miss:

  1. A Novel Approach For Product Recommendation Engine Using Graph Database
  2. Emotional Stress Detection Using Deep Learning
  3. Revolutionalising Safety In Railways Using Computer Vision
  4. A Heuristic Optimisation Solution For The Selection Of The Transformation Functions For Media Channels In Marketing Mix Modelling (MMM)
  5. NLP Driven Qualitative Assessment Of Product Description
  6. Artificial Intelligence For Simplified Deployments
  7. Measuring Digital Marketing Effectiveness Using Incrementality
  8. Automated Short Answer Grading Using Conventional And Modern NLP Techniques
  9. Building An AI-driven Logistics Platform
  10. Predicting Product Success Using AI In Video And Audio Analytics
  11. Leveraging BERT + Deep Learning For Impactful Analysis On Streaming News And Events
  12. Partitioning Nearest Neighbour Approach To Regression Variation Improvement In Tree-Based Approaches
  13. Algorithm To Recommend Corrective Actions For Yaw Misalignment In A Wind Turbine
  14. Detecting and Predicting Price Change Acclimation
  15. Approaches For Predicting Potential Cancerous Cell Formation in the Fetus
  16. Content And Author Identification In Indian English, Hindi and Bangla
  17. Machine Learning Application To Create Experimental Learning Models For Personal Finance
  18. Smart Job Order Prioritization with AI
  19. Domain-Specific Word Segmentation and Hierarchy Detection using NLP Algorithm

2020-01-15 12:32:51+00:00 Read the full story…
Weighted Interest Score: 2.9309, Raw Interest Score: 1.8117,
Positive Sentiment: 0.1220, Negative Sentiment 0.1126

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