Industry News

Industry News

Alternative Data News : Daily Number of Flights at Top US Airports : How to Import Historical Stock Prices Into A Python Script Using the IEX Cloud API : Master Data Management (MDM) becomes Incredible Differentiator For Countless Businesses : BDQ Big Data Quarterly: Summer 2020 Issue

Alternative Data News. 27, May 2020

Alternative Data News. 27, May 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.

Daily Number of Flights at Top US Airports

From Reddit DataIsBeautiful
Data source:
Tools used: Matplotlib.
Exponentially weighted average with a span of 5 days is shown.
The visualization created for
2020-05-22 Read the full story…
CloudQuant Thoughts : A personal favorite for tracking the impact of the Covid-19 on flights is the TSA checkpoint travel numbers.

How to Import Historical Stock Prices Into A Python Script Using the IEX Cloud API

Python is one of the world’s most popular programming languages. Specifically, Python for finance is arguably the world’s most popular language-application pair. This is because of the robust ecosystem of packages and libraries that makes it easy for developers to build robust financial applications. In this tutorial, you will learn how to import historical stock prices from the IEX Cloud API and store them within your script in a pandas DataFrame.

  1. Create an IEX Cloud Account
  2. Import Pandas
  3. Select Your API Endpoint
  4. Ping the Endpoint and Store the Data in a pandas DataFrame
  5. Final Thoughts

2020-05-24 11:01:00+00:00 Read the full story…
Weighted Interest Score: 2.6347, Raw Interest Score: 1.5103,
Positive Sentiment: 0.2014, Negative Sentiment 0.0000

CloudQuant Thoughts : Interesting but nowhere near as easy to use as CloudQuant.

Master Data Becomes Incredible Differentiator For Countless Businesses

Forward-thinking companies realize that the use of master data sets them apart from the competition. Master data management or MDM enables companies to reconcile disparate data sources, helping them avoid duplication of efforts and making company-wide data analysis possible.

Master data services provide companies with new ways to organize their efforts. This differentiation can make companies more competitive in a crowded landscape.

Advantages of Master Data Management

Experienced master data managers like Profisee are able to reconcile company databases and draw out the inf…
2020-05-21 00:04:23+00:00 Read the full story…
Weighted Interest Score: 2.3839, Raw Interest Score: 1.2968,
Positive Sentiment: 0.2928, Negative Sentiment 0.1046

CloudQuant Thoughts : MDM (Master Darta Management) has been popping up a lot in recent weeks, definitely a trend to watch

BDQ Big Data Quarterly: Summer 2020 Issue – PDF after registration

editor’s note – Joyce Wells – It All Comes Down to the Data
BIG DATA BRIEFING – Key news on big data product launches, partnerships, and acquisitions from the BDQ and DBTA websites
Insights – Jon Roskill – Avoiding Unscrupulous Data and Business Practices Among Cloud Software Vendors
Insights – Scott Zoldi – Artificial Intelligence Grows Up in 2020
Trending Now – Ethical AI: Q&A With Fractal Analytics’ Suraj Amonkar
Insights – Nikita Ivanov – The In-Memory Computing Landscape in 2020
Insights – Patrick Lastennet – Security Factors to Take into Consideration in a Multi-Cloud World
The Voice of Big Data  – Improving Database Change: Industry Leader Q&A With Datical’s Dion Cornett
8 Feature Article – Joe McKendrick – Reversing the 80/20 Ratio in Data Analytics
Big Data By the Numbers – Infographic: New Requirements Spur Data Quality and Data Integration
Data Science Playbook – Jim Scott – Advancing Data Science for Emergency Management and Public Health Response
Data Directions – Michael Corey & Don Sullivan – Pandemics Happen—AI and Machine Learning Can Provide the Cures
Governing Guidelines – Kimberly Nevala – Stemming Your Data Contagion
The Iot insider – Bart Schouw – IoT and Data Power the Next Generation of Clean Energy
2020-06-15 00:00:00 Read the full story…
Weighted Interest Score: 4.5038, Raw Interest Score: 2.5249,
Positive Sentiment: 0.1530, Negative Sentiment 0.0000
CloudQuant Thoughts : A magazine for Big Data Users! Excellent!

AllegroGraph v7 Powers Distributed Semantic Knowledge Graph

A new press release reports, “Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology for Knowledge Graph Solutions, today announced AllegroGraph 7, a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph 7 utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. Hidden connections in data are revealed to AllegroGraph 7 users through a new browser-based version of Gruff, an advanced visualization and graphical query builder.”

2020-05-27 07:15:31+00:00 Read the full story…
Weighted Interest Score: 3.4214, Raw Interest Score: 2.1046,
Positive Sentiment: 0.3007, Negative Sentiment 0.1203

Chetwood Financial hires chief data officer, head of people, and chief risk officer

Chetwood Financial has announced the appointment of a new Chief Data Officer, Head of People and Chief Risk Officer.
Jessica Rusu has been appointed as Chief Data Officer and has been brought on board to further Chetwood’s mission of making customers better off with technology. As an established analytics and data leader, Rusu has 20 years of industry experience, most recently heading up Advanced Analytics and Customer Insight teams at eBay.

Sarah Hosker joins as Head…
2020-05-27 09:50:00 Read the full story…
Weighted Interest Score: 3.0257, Raw Interest Score: 1.5129,
Positive Sentiment: 0.5043, Negative Sentiment 0.0000

Indonesian startup Delman raises $1.6 million to help companies clean up data – TechCrunch

Delman, a Jakarta-based data management startup, has raised $1.6 million in seed funding. The round was led by Intudo Ventures, with participation from Prasetia Dwidharma Ventures and Qlue Performa Indonesia, and will be used to establish a research and development center and hire software engineers and data scientists.
Delman was founded in 2018 by chief executive officer Surya Halim, chief product officer Raymond Christopher and chief technology officer Theo Budiyanto, who were classmates at the University of California, Berkeley. After graduation, they worked at tech companies in Silicon Valley, including Google and Splunk, before deciding to focus on the Indonesian market. Originally launched as an end-to-end big data analytics provider, Delman shifted its focus to data preparation and management after talking to clients in Indonesia, said Halim. Many companies said they had budgeted for expensive data analytics solution, but then realized their data was not ready for analysis because it was spread across multiple formats. Delman’s mission is to make it easier for data engineers and scientists to do their jobs by cleaning up and preparing data. Halim says many large companies in Indonesia typically spend up to $200,000 to clean and warehouse data, but Delman gives them a more cost-efficient and faster alternative.

2020-05-26 00:00:00 Read the full story…
Weighted Interest Score: 2.6913, Raw Interest Score: 1.6329,
Positive Sentiment: 0.2419, Negative Sentiment 0.0302

Scaling the Analytics Team: Developing Key Roles

n an enterprise analytics team, different roles exist to fill different needs, and those needs must be met in order to be successful. Launching an analytics program doesn’t necessarily require a massive influx of personnel before producing usable insights from data, yet it’s important that critical roles are filled, whatever the size of the team. Multiple options exist for starting small and scaling up an analytics program, according to Evan Terry, VP of Operations at CPrime and co-author of Beginning Relational Data Modeling, in his presentation titled Roles in Enterprise Analytics at the DATAVERSITY® Enterprise Analytics Online Conference.
Data scientists often explore data independently, but the reality is that an entire support team is necessary for this type of exploration, he said. Data Science operates less like a rock climber and more like a baseball team, where all nine individuals with different specialized roles are on the field at the same time working together, all necessary to compete successfully.
2020-05-26 07:35:09+00:00 Read the full story…
Weighted Interest Score: 2.2438, Raw Interest Score: 1.2350,
Positive Sentiment: 0.1791, Negative Sentiment 0.1508

How Cinelytic is using AI to help Hollywood reboot for the streaming wars

While Hollywood giants have plunged into the streaming wars with massive vaults of content, they still face a yawning consumer data deficit as they try to catch up to industry leader Netflix. Cinelytic wants to help them level the playing field.
The L.A.-based startup has compiled a broad array of data to fuel its platform that helps studios understand in real time how choices ranging from scripts to actors could impact a project’s risk profile and revenue potential. While Hollywood studios have been making bets based on box office data and audience surveys for decades, they still have nowhere near the audience insight that Netflix has at its fingertips.
With subscription-based streaming set to become the primary way consumers discover and experience Hollywood’s content, traditional film and TV producers will eventually be awash in new forms of behavioral data. Studios are starting to turn to AI to help manage and analyze the data in a way that can actually drive more effective and profitable decisions.

2020-05-26 00:00:00 Read the full story…
Weighted Interest Score: 2.0964, Raw Interest Score: 1.0125,
Positive Sentiment: 0.1997, Negative Sentiment 0.1569

The Four Data Management Mistakes Derailing Your BI Program

If there’s one thing I’ve learned as a BI consultant, it’s that Data Management problems, like speeding tickets and jury duty, are terribly common but somehow still feel unlikely to happen to you.
I can’t tell you how many times I’ve seen BI implementations drag on for months and months because issues around data extraction, modeling, aliasing, and stewardship weren’t resolved or even considered at the onset of the project. It’s never fun to put in the time upfront, but it’s a lot less painful than having to backtrack.
That said, I’ve also seen companies give serious consideration to their Data Management strategy from the start and get their BI implementation in front of customers well within their deadline. Data Management may sound like optional busy work for paper pushers, but let me assure you, it’s critical to your success, especially if you offer BI.

2020-05-25 07:35:40+00:00 Read the full story…
Weighted Interest Score: 1.3680, Raw Interest Score: 0.9155,
Positive Sentiment: 0.1473, Negative Sentiment 0.3788

This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. We used natural language processing (NLP) to determine an interest score, and to calculate the sentiment of the linked article using the Loughran and McDonald Sentiment Word Lists.

If you would like to add your blog or website to our search crawler, please email We welcome all contributors.

This news clip and any CloudQuant comment is for information and illustrative purposes only. It is not, and should not be regarded as investment advice or as a recommendation regarding a course of action. This information is provided with the understanding that CloudQuant is not acting in a fiduciary or advisory capacity under any contract with you, or any applicable law or regulation. You are responsible to make your own independent decision with respect to any course of action based on the content of this post.