Data Science and Databases

The Hadoop Distributed File System (HDFS) is a scalable, open-source solution for storing and processing large volumes of data. With its built-in replication and resilience to disk failures, HDFS is an ideal system for storing and processing data for analytics.

In this step-by-step tutorial, Toptal Database Developer Dallas H. Snider details how to migrate existing data from a PostgreSQL database into the more efficient HDFS.

Genome data is one of the most widely analyzed datasets in the realm of Bioinformatics. The SciPy stack offers a suite of popular Python packages designed for numerical computing, data transformation, analysis and visualization, which is ideal for many bioinformatic analysis needs.

In this tutorial, Toptal Software Engineer Zhuyi Xue walks us through some of the capabilities of the SciPy stack. He also answers some interesting questions about the human genome, including: How much of the genome is incomplete? How long is a typical gene?

As a language, R is strongly tied to data and is thus used mostly by statisticians and data scientists. Many who already use R for machine learning, though, are not aware that data munging can be done faster in R, meaning another tool is not required for that task.

In this article, Freelance Software Engineer Jan Gorecki explores tabular data transformations and introduces us to one of the fastest open-source data wrangling tools available.

Ever tried to create a JSON data structure that includes entities with bidirectional relationships? If you have, you know that this often results in errors or exceptions being thrown.

In this article, Toptal Freelance Software Engineer Nirmel Murtic provides a robust working approach to avoiding these errors when creating JSON structures that included entities with bidirectional (i.e., circular) relationships.

More than 60 percent of trading activities with different assets rely on automated trading and machine learning instead of human traders. Today, specialized programs based on particular algorithms and learned patterns automatically buy and sell assets in various markets, with a goal to achieve a positive return in the long run.

In this article, Toptal Freelance Data Scientist Andrea Nalon explains how to predict, using machine learning and Python, which trade should be made next on the S&P 500 to get a positive gain.

Clustering algorithms are very important to unsupervised learning and are key elements of machine learning in general. These algorithms give meaning to data that are not labelled and help find structure in chaos. But not all clustering algorithms are created equal; each has its own pros and cons.

In this article, Toptal Freelance Software Engineer Lovro Iliassich explores a heap of clustering algorithms, from the well known K-Means algorithm to the elegant, state-of-the-art Affinity Propagation technique.

When dealing with data analysis, most companies rely on MS Excel or Google Sheets, but dealing with data presented this way isn’t very eye-catching or intuitive. It’s once you add visualizations to this data that things become a little easier to manage. That’s the topic of today’s tutorial by our guest author from Adobe, Rohit Boggarapu. Join us as he guides us though the process of making interactive drill-down charts using jQuery and FusionCharts.