Analytics Vidhya: 10+ Simple Yet Powerful Excel Tricks for Data Analysis

Analytics Vidhya: 10+ Simple Yet Powerful Excel Tricks for Data Analysis. “I’ve always admired the immense power of Excel. This software is not only capable of doing basic data computations, but you can also perform data analysis using it. It is widely used for many purposes including the likes of financial modeling and business planning. It can become a good stepping stone for people who are new to the world of business analytics.”

The Atlantic: How Virginia Juked Its COVID-19 Data

The Atlantic: How Virginia Juked Its COVID-19 Data. “The United States’ ability to test for the novel coronavirus finally seems to be improving. As recently as late April, the country rarely reported more than 150,000 new test results each day. The U.S. now routinely claims to conduct more than 300,000 tests a day, according to state-level data compiled by the COVID Tracking Project at The Atlantic. But these rosy numbers may conceal a problem: A lack of federal guidelines has created huge variation in how states are reporting their COVID-19 data and in what kind of data they provide to the public.”

First Draft: How to analyze Facebook data for misinformation trends and narratives

First Draft: How to analyze Facebook data for misinformation trends and narratives. “There is a mountain of data that can help us examine topics such as the spread of 5G conspiracy theories or where false narratives around Covid-19 cures came from. It can help us analyze cross-border narratives and identify which online communities most frequently discuss certain issues. While Twitter’s public data is accessible through its Application Programming Interface (API), it can be much more complicated for researchers to access platforms such as Facebook and Instagram. Facebook-owned platform CrowdTangle is the most easily accessible tool to handle three of the most important social networks — Facebook, Instagram, and Reddit — and it is free for journalists and researchers.”

Harvard Gazette: Real-time data to address real-time problems

Harvard Gazette: Real-time data to address real-time problems. “Called the Opportunity Insights Economic Tracker, the tool was created as a public resource to help policymakers assess the effects of the downturn in different regions of the U.S. with the most up-to-date information possible. With a more complete and current picture of the nation’s economic standing, policymakers should then be able to make evidence-based decisions as they move to reopen the nation. The tool provides lawmakers real-time analysis of data such as consumer spending and job postings, which normally takes them several weeks to get.”

Expert Tips for Data Analytics: COVID-19 to Dark Data (Datamation)

Datamation: Expert Tips for Data Analytics: COVID-19 to Dark Data. “Register for this live video webinar – Thursday, May 7, 9 AM PT Ask the experts – get your Data Analytics questions answered by two industry experts. In a wide ranging conversation with two of data analytic’s top thought leaders, we’ll delve into some key questions in analytics today.” I’m pretty sure this is free, but not 100% positive.

FierceBiotech: Life science companies combine to form COVID-19 research database

FierceBiotech: Life science companies combine to form COVID-19 research database. “A group of major CRO, life science, data analytics, publishing and healthcare companies joined forces to release a pro bono research database to build up and integrate a central hub on the latest data out for COVID-19. On the technical side, it’s a secure repository of HIPAA-compliant, de-identified and limited patient-level data sets that will be ‘made available to public health and policy researchers to extract insights to help combat the COVID-19 pandemic,’ according to the group.”

Analytics India: A Beginner’s Guide To Using Google Colab

Analytics India: A Beginner’s Guide To Using Google Colab. “We are all familiar with the pop-up alerts of ‘memory-error’ while trying to work with a large dataset of machine learning (ML) or deep learning algorithms on Jupyter notebooks. On top of that, owning a decent GPU from an existing cloud provider has remained out of bounds due to the financial investment it entails. The machines at our disposal, unfortunately, do not have the unlimited computational ability. But the wait is finally over as we can now build large ML models without selling our properties. The credit goes to Google for launching the Colab – an online platform that allows anyone to train models with large datasets, absolutely free.”