Alternative Data News. 19, August 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.


From Reddit DataIsBeautiful…

The original image is 3840 x 4860. I made the map in Gimp.
Link to 2008 Median Household Income data
Link to 2018 Median Household Income data
I converted all of the data from 2008 to 2018 Dollars so they could be easily compared, this is the calculator I used to convert 2008 Dollars to 2018 Dollars.
Nevada had a median household income of $65,766 in 2008 (Adjusted to 2018 Dollars). In 2018, that figure was $57,598.
The District of Columbia had a median household income of $67,604 in 2008 (Adjusted to 2018 Dollars). In 2018, that figure was $82,604.
North Dakota had a median household income of $53,308 in 2008 (Adjusted to 2018 Dollars). In 2018, that figure was $63,473.

2020-08-17 Read the full story…

CloudQuant Thoughts : A nice view of the data with some surprising revelations!

Setting your data science team up for success: 3 critical considerations – Anaconda

In 2012, “data scientist” was famously deemed the “sexiest job of the 21st century,” with anticipation that the demand for talent would quickly outpace supply. Organizations raced to add “data-driven” to their mission statements, and data scientists found themselves at the center of talent bidding wars, commanding formidable salaries that further fanned the flames of the hype.

Alternatively, some companies tried to jump on the big data bandwagon by rebranding their business analysts or data managers as “data scientists,” giving a new name to professionals tasked with maintaining the same dashboards and pulling the same metrics as before.

Since then, data scientists have become far more common in the business world, but many organizations still fall victim to the misconception that data science is a silver bullet for any and all business problems. Businesses that hire data scientists often neglect to establish the best practices needed to position them for success. In many cases, these organizations will try to force their data scientists into a single function –business analyst, data manager, software engineer, etc. — failing to take advantage of the hybridization that makes data science unique and valuable.

  • Data scientists seek impactful work
  • Data scientists want to explore
  • Data scientists need innovative tools

2020-08-18 00:00:00 Read the full story…
Weighted Interest Score: 3.5474, Raw Interest Score: 1.9057,
Positive Sentiment: 0.3943, Negative Sentiment 0.2464

CloudQuant Thoughts : A neat article by one of our original partners, Anaconda. Interesting observation that many companies do not know where to place Data Scientists in their Org Charts.. “…may find themselves sitting in the IT org, operating on the business side, or working in dedicated data science centers of excellence.” The final location will have a significant impact on the quality and creativity of the output.

Data Science Skills Study 2020

Analytics India Magazine, in association with AnalytixLabs, released the Data Science Skills Survey over the months of June and July 2020 so as to get an in-depth perspective into the key trends related to the tools and models deployed across sectors.

AIM has now published the findings of the survey in this report. Please access last year’s Study here.

This survey provides a direct perspective on the Data Science skills and domains that AI, Analytics, and Machine Learning practitioners are working on and how organizations and Data Science personnel stay ahead of the data science pack. This report will benefit prospective job seekers, including students, and personnel seeking to transition to the Data Science function – it will help this broad audience to understand the skills, technologies, and platforms in demand across organizations.

2020-08-17 07:30:18+00:00 Read the full story…
Weighted Interest Score: 3.3860, Raw Interest Score: 1.9308,
Positive Sentiment: 0.0585, Negative Sentiment 0.0195

CloudQuant Thoughts : “Top language preferred for Statistical Modelling is Python, favoured by 65.2%” no surprise to us there but we have also recently added R to our Alternative Data Research platform CQ AI, R comes in second with 16.7% of users preferring to use it as their primary research language. Most interesting is that 70% of respondents had 3 years or less experience!

AI researchers devise cheap data collection method to scale training robots

Researchers from Google and Columbia University came up with the idea to use a pole with a grabbing instrument on the end came, which was accepted for publication in June.

To train the model, they attached a GoPro camera to the reacher pole via a 3D-printed mount and recorded 1,000 attempts to move objects or complete tasks. Once they collected the videos, the researchers used them to train a convolutional neural network, which was applied to a robotic arm fitted with a camera and the same kind of two-finger grasping clamp as a reacher-grabber. Finally, they added data augmentation such as random jitters, crops, and rotation to training data to achieve higher rates of success when tested in a lab setting. They used behavioral cloning and supervised learning to train the model’s policy settings.

“Given these visual demonstrations, we extract tool trajectories using off-the-shelf Structure from Motion (SfM) methods and the gripper configuration using a trained finger detector. Once we have extracted tool trajectories, corresponding skills can be learned using standard imitation learning techniques,” the paper reads.

At the end of the process, the system achieved success rates of 87.5% in pushing objects across a table to a target spot and 62.5% in stacking performance. Humans intervened in some instances at testing time to attempt to trick the robot into failing at its task.

2020-08-13 Read the full story…

CloudQuant Thoughts : The range and variety of data that the researchers could have gathered in the lab environment would have been extremely limited. Using a little lateral thinking, a 3d printed part, a $10 grabber and a GoPro they were able to gather hours of useful images going about their everyday lives. Just goes to show how important creativity is in Data Science/AI/ML roles.

Vela, IPC Expand Market Data Partnership

Vela, a leading independent provider of trading and market access technology for global multi-asset electronic trading, today announced the expansion of its strategic partnership with IPC, a leading global provider of secure, compliant communications and networking solutions for the global financial markets.

The partnership will provide IPC customers with access to Vela’s award-winning market data solution, SuperFeed, via Connexus Cloud, IPC’s flagship financial ecosystem that interconnects more than 6,600 capital market participants across the globe. It will also enable IPC customers, utilizing Connexus Labs, to access an on-demand market data solution to support trading application testing along with third-party product evaluations.

2020-08-10 Read the full story…

Groundbreaking internet insights available to Bloomberg clients

KASPR Datahaus PTY LTD, a Melbourne-based alternative data company that provides real-time information about the world’s internet infrastructure, has announced today that its Global ICT Intel Daily Data products are now available to Bloomberg Data License clients via the Bloomberg Enterprise Access Point.

“We are thrilled to arrive on Bloomberg’s Enterprise Access Point, globally recognised for its high quality alternative data offerings, especially to the financial industry,” noted Co-Founder and Director of KASPR Datahaus, and Associate Professor of Economics at Monash Business School, Dr Paul Raschky, on the news.

“The Bloomberg Enterprise Access Point provides a powerful, additional, way for our clients to discover and integrate our global datasets into their applications, in close to real time.”

KASPR Datahaus measures daily the internet connectivity and latency of a universe of over 380 million fixed, geo-spatially identified, internet-connected end-points, covering 136 countries and 2000 sub-national regions. This enables KASPR Datahaus to provide unique, close-to-real time insights about the availability and quality of ICT infrastructure at the country, province, and city level, worldwide.

2020-08-18 00:00:00 Read the full story…

Register For Webinar: How To Accelerate Your Career In Data Science

Demand for trained data scientists has witnessed massive growth in recent years. Data analysis is not only essential but indispensable for meeting the challenges of making the most efficient strategies as well as tactical decisions for organisations today.

Analytics India Magazine in association with Indian Institute of Management, Calcutta (IIM Calcutta) is organising this webinar to help Professionals who are keen to build a career in Data Science or those seeking to accelerate their career in Data Science with leading techniques & industry-relevant curriculum and gain through the knowledge & skills of the finest faculties at IIM Calcutta. This session will also give you insights to IIM Calcutta’s Advanced Programme in Data Sciences.

Register for the webinar here.

2020-08-11 08:11:48+00:00 Read the full story…
Weighted Interest Score: 3.4471, Raw Interest Score: 2.0753,
Positive Sentiment: 0.1055, Negative Sentiment 0.0352

Things To Consider Before Hiring A Data Scientist Amid The Crisis

COVID-19 is a tormenting time for businesses and their financial stability, where companies are looking not to make any wrong investment to keep up their sustainability. And at this time, if any organisation is taking a plunge into data and planning to transform its business strategies with data science, it is critical to keep a few things in mind.

Data scientists are indeed in much demand and hard to find amid the crowd; thus, companies need to be on a constant lookout as well as cautious to avoid missteps. Although it is interesting to witness the benefits of data science, creating a data-driven organisation and hiring a team of data science is no easy task. Not only does it require the right infrastructure but also the right mindset to embrace it on all levels.

While some non-traditional ways have emerged to hire data scientists amid this crisis, here are a few things organisations need to consider before actually hiring one.

2020-08-18 12:30:47+00:00 Read the full story…
Weighted Interest Score: 3.0506, Raw Interest Score: 1.7750,
Positive Sentiment: 0.2988, Negative Sentiment 0.2460

IIT Madras Invites Applications For Post-Doctoral Fellowship In Data Science & AI

The Robert Bosch Centre for Data Science and Artificial Intelligence (RBC DSAI) at IIT Madras has invited applications for its Post-Doctoral Fellowship. It is open to candidates across the country with PhD Degrees in Research Topics related to Data Science, Artificial Intelligence or allied application domains.

The areas of research include Deep Learning, Network Analytics, Theoretical Machine Learning, Reinforcement Learning and Multi-armed Bandits, Natural Language Processing, AI on the edge, System Architecture for Data Science and AI, Ethics, Fairness and Explainability in AI, Systems Biology and Healthcare, Smart Cities and Transportation, and Financial Analytics.

The Research Fellowship also allows you to carry out independent research for PhDs who want to mature towards an independent research career. It also includes a monthly stipend that is significantly higher than typical institute Post-Doctoral Fellowships.

2020-08-17 08:55:14+00:00 Read the full story…
Weighted Interest Score: 3.0471, Raw Interest Score: 1.8661,
Positive Sentiment: 0.1647, Negative Sentiment 0.0549

Python, R: Languages Key to Jobs at Consultancies Like McKinsey & Co.

Getting your foot in the door at one of the top consulting firms is no easy task. At McKinsey, for example, more than 750,000 people apply in given year. Fewer than 1 percent are accepted. That trumps the lowest acceptance rate at top investment banks such as Goldman Sachs (~ 4 percent) by a wide margin.

So how do you stand out from the crowd? One pathway: Learn how to program with R and target these consulting firms’ growing analytics teams.

As with banks and hedge funds, consulting firms are on the hunt for data engineers and data scientists who can design algorithms and build complex models. All the MBB firms (McKinsey & Co., Bain and Boston Consulting) have dedicated analytics teams that work alongside their consultants to analyze huge datasets to help drive business decisions for clients. McKinsey also has the spin-off Quantum Black, while BCG has BGC Gamma.

These firms are all hungry for junior- and senior-level engineers to work in their analytics departments. And they’re particularly hungry with engineers experienced in a particular language: R.

2020-08-14 00:00:00 Read the full story…
Weighted Interest Score: 2.9769, Raw Interest Score: 1.7626,
Positive Sentiment: 0.1567, Negative Sentiment 0.0392

Liberated Data Can Power Your Company Through a Crisis and Beyond It

The staggering implications of the current pandemic have entirely changed today’s business landscape, leaving leaders looking for solutions that will help them thrive or even just survive this unprecedented environment.

While the COVID-19 crisis poses many challenges — and there are indeed significant problems on many fronts — it also provides the impetus for long-needed organizational changes when it comes to data-driven decision-making. More specifically, today’s organizations need information and insights more than ever before, and big data will play an important role in helping companies navigate today’s altered business landscape.

However, unlike before this crisis, when data was defined by abundance and was siloed in isolated segments, post-pandemic companies will liberate data, pairing it with powerful new technologies, like artificial intelligence (AI), to achieve the accurate and real-time insights necessary to successfully navigate this unique time.

2020-08-18 07:30:41+00:00 Read the full story…
Weighted Interest Score: 2.9587, Raw Interest Score: 1.6383,
Positive Sentiment: 0.1843, Negative Sentiment 0.4710

So You Want to Be a Data Modeler?

There is a always a need for data modelers, however, the job description of this career field varies, depending on the needs of the organization. For example, a data modeler working for a startup would coordinate with data scientists and data architects in designing a new system — one that included the goals of the organization, and the steps needed to achieve them, within its architectural design. This “model” represents the organization and promotes understanding through the use of core data, such as attributes, entities, and relationships regarding customers, staff, products, and other factors.

A data modeler working for an organization with an already established system would be more focused on model maintenance, integrating data from multiple sources for purposes of presentations and decision making, and implementing changes to make the organization more efficient.

A data modeler working for an established organization should be technically skilled in the administration of databases, but may also need to assist in developing presentations, and should be comfortable dealing with both staff and customers.
2020-08-11 07:35:51+00:00 Read the full story…
Weighted Interest Score: 2.8873, Raw Interest Score: 1.6824,
Positive Sentiment: 0.3638, Negative Sentiment 0.1250

Margin Reform, SteelEye Partner on Compliance Solutions

Margin Reform partners with SteelEye to offer clients best–of–breed compliance solutions

London, 13 August 2020: SteelEye, the compliance technology and data analytics firm, has today announced a partnership with Margin Reform, a management and information technology consultancy in the margin, collateral, and legal space, to support the consultancy’s clients with best-of-breed compliance and regulatory reporting solutions. Margin Reform will offer  SteelEye’s  RegTech suite  to  its financial  clients as  they address the challenges of  the evolving  regulatory landscape.

2020-08-17 13:20:31+00:00 Read the full story…
Weighted Interest Score: 2.5915, Raw Interest Score: 1.4412,
Positive Sentiment: 0.5071, Negative Sentiment 0.1068

India’s Revived Space Race, Smarter Phones And More In This Week’s Top News

The UK’s visa application process has come under scanner for implementing algorithms that are institutionally racist. According to BBC, the screening system took some information provided by visa applicants and automatically processed it,and gave a colour code to each person based on a “traffic light” system – green, amber, or red.

“This streaming tool took decades of institutionally racist practices, such as targeting particular nationalities for immigration raids, and turned them into software.”

2020-08-15 12:30:53+00:00 Read the full story…
Weighted Interest Score: 2.4132, Raw Interest Score: 1.0573,
Positive Sentiment: 0.2194, Negative Sentiment 0.1197

Machine learning groups form Consortium for Python Data API Standards to reduce fragmentation

Deep learning framework Apache MXNet and Open Neural Network Exchange (ONNX) today launched the Consortium for Python Data API Standards to improve interoperability for machine learning practitioners and data scientists using any framework, library, or tool from the Python ecosystem.

ONNX itself was formed by Facebook and Microsoft in 2017 to encourage interoperability between frameworks and tools. Today, ONNX includes nearly 40 organizations with influence in AI and data science, including AWS, Baidu, and IBM, along with hardware makers like Arm, Intel, and Qualcomm.
2020-08-17 00:00:00 Read the full story…
Weighted Interest Score: 2.3540, Raw Interest Score: 1.3208,
Positive Sentiment: 0.1887, Negative Sentiment 0.0000

SQL for data scientists: learning it easy way

As you do with your favorite programming library such as pandas , the first thing you need to do is loading the dataset in the SQL environment.

And like basic exploratory data analysis (EDA) in a typical data science project, you are able to check out the first few rows, count the total number of rows, see column names, data types etc. Below are a few commands.

2020-08-18 23:23:21.270000+00:00 Read the full story…
Weighted Interest Score: 2.2484, Raw Interest Score: 0.9101,
Positive Sentiment: 0.0803, Negative Sentiment 0.0000


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