Data Science and Databases

Twitter is a goldmine of data. Unlike other social platforms, almost every user’s tweets are completely public and pullable.

In this tutorial, Toptal Freelance Software Engineer Anthony Sistilli will be exploring how you can use Python, the Twitter API, and data mining techniques to gather useful data.

Social networks are among the biggest sources of data today, and this means they are an extremely valuable asset for marketers, big data specialists, and even individual users like journalists and other professionals. Harnessing the potential of real-time Twitter data is also useful in many time-sensitive business processes.

In this article, Toptal Freelance Software Engineer Hanee’ Medhat explains how you can build a simple Python application to leverage the power of Apache Spark, and then use it to read and process tweets to identify trending hashtags.

Security has always been a primary concern for database experts, and with the advent of new, decentralized services, it’s become even more crucial. Microsoft addressed the need for an added level of security in SQL with the introduction of Always Encrypted functionality in SQL Server 2016.

In this blog post, Toptal Freelance Software Engineer Josip Saban explains how Microsoft’s Always Encrypted concept works, how it’s implemented, and why developers can’t afford to ignore it.

Consistent Hashing is a distributed hashing scheme that operates independently of the number of servers or objects in a distributed hash table. It powers many high-traffic dynamic websites and web applications.

In this tutorial, Toptal Freelance Software Engineer Juan Pablo Carzolio will walk us through what it is and how hashing, distributed hashing and consistent hashing work.

Limited SQL scalability has prompted the industry to develop and deploy a number of NoSQL database management systems, with a focus on performance, reliability, and consistency. The trend was driven by proprietary NoSQL databases developed by Google and Amazon. Eventually, open-source systems like MongoDB, Cassandra, and Hypertable brought NoSQL within reach of everyone.

In this post, Senior Software Engineer Mohamad Altarade dives into some of them and explains why NoSQL will probably be with us for years to come.

With the rise of big data and data science, storage and retrieval have become a critical pipeline component for data use and analysis. Recently, new data storage technologies have emerged. But the question is: Which one should you choose? Which one is best suited for data engineering?

In this article, Toptal Data Scientist Ken Hu compares three prominent storage technologies within the context of data engineering.

Nobody wants to leave valuable customer data behind. Unfortunately, though, the hardest part of data migration to a complex CRM system, such as Salesforce, is the handling of legacy data.

In this article, Toptal Software Engineer Marian Paul provides 10 tips for successful legacy data migration to Salesforce.