Data Trends for Investment Professionals

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Free DataCamp Tutorial for Quandl and R

This is a guest post from DataCamp. At DataCamp we build tools to learn data science interactively. We have an onlineR tutorial to learn R Programming and a Python For Data Science tutorial to learn Python. Some time ago we collaborated with Quandl to developHow to Work with Quandl in R, a free interactive tutorial that introduces you to the main functionality of the Quandl R package. Evidently, we hit the mark with this one because to date, this course has been taken by more than 30,000 data science enthusiasts. In the past few weeks, we’ve been updating many of...

BOOK REVIEW: Financial Analytics with R

There’s a new source in town for those who want to learn R and it’s a good, old-fashioned book called Financial Analytics with R: Building a Laptop Laboratory for Data Science.  Written by Mark Bennett and Dirk Hugen, it hits the shelves in the U.K. in September and the U.S. in November. Though designed as a graduate-level textbook, it is a highly appropriate read for practitioners in financial analysis who are new to R, or who want to improve their understanding and use of R. Be warned, however, that a sufficient background in university-level math, statistics, and computer science is...

WooTrader proves what startups can accomplish when they get the data they need

We recently spoke to Atanas Stoyanov, CEO of WooTrader, about his journey from a software programmer to FinTech founder. In 2007, Stoyanov sold his previous company, an Inc 500 firm that developed software optimization tools. He then turned his considerable programming talent to helping investors keep up with rapidly changing markets. He launched WooTrader, with the vision of becoming the only website you’ll need for asset management. With the recent release of a Wall Street-ready API, WooTrader’s client base is now expanding to hedge funds and investment banks. You’ve built a number of successful companies, including a software testing company. How...

Quandl Python Package Upgrade

2.x Series Package Notes With the release of version three of our API, we are officially deprecating version two of the Quandl Python package. We have re-written the package and will be moving forward with a 3.x.x package under the new namespace of quandl  that will rely on version three of our RESTful API. Upgrading There are numerous advantages to upgrading from the older 2.x series package including improved performance and stability. The upgrade process is fairly simple; Upgrade your package using pip and running: pip install --upgrade Quandl 2. Wherever you have: import Quandl change this to: import quandl as Quandl Additionally, if...

Bring Your Own Tool: the Latest Trend in Data Analysis

The role of the data analyst is changing. The best analysts know that different tasks require different tools. The End of Bundling Once upon a time, data purchases came bundled with data consumption software. You couldn't just buy a dataset; you had to install a proprietary data downloader. You couldn’t just view the data on your computer; you needed a custom visualizer, or even a full-fledged data terminal. And you couldn't do whatever you wanted with the data; you were forced to work within the applications provided to you by the vendor. Today, this seems absurd. In 2016, analysts don't...

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