Data Science and Databases

Bitcoin created a lot of buzz on the Internet. It was ridiculed, it was attacked, and eventually it was accepted and became a part of our lives. However, Bitcoin is not alone. At this moment, there are over 700 AltCoin implementations, which use similar principles of CryptoCurrency.

Google’s new cloud code platform does not appear to be taking on GitHub head on. Instead, Cloud Source Repositories (CSR) will allow users to connect to repositories hosted on GitHub or Bitbucket. However, everything is automatically synced to the Google Cloud Source Repository.

The good news is that a Google CSR can be connected to another Git repository hosted on GitHub or Bitbucket. All changes will be synchronised on both platforms, as you can set Google CSR to automatically mirror from GitHub and Bitbucket.

In-memory data collection manipulation is something that we often need to do in data-centric reporting and visualization applications. When needed, we often tend to resort to complex loops, list comprehensions, and other suboptimal means, which can easily end up being a huge mess of hard-to-maintain spaghetti code. Supergroup.js is an in-memory data manipulation library that can be used to solve some common data manipulation challenges on limited datasets.

Microsoft Bond is a modern data serialization framework. It provides powerful DSL and flexible protocols, code generators for C++ and C#, efficient protocol implementations for Windows, Linux, and Mac OS X. This article is a quick guide of the features and use of this framework.

Analysts have come to recognize social network data as a virtual treasure trove of information for sensing public opinion trends and groundswells of support. In this article, Toptal Engineer Elder Santos describes the techniques he employed for a proof-of-concept that effectively analyzed Twitter Trend Topics to predict, as a sample test case, regional voting patterns in the 2014 Brazilian presidential election.

Machine learning has changed the way we deal with data. Data driven problems, that are difficult to solve using standard methods, can often be tackled with much more ease using machine learning algorithms. In this article, we will explore Azure Machine Learning features and capabilities through solving one of the problems that we face in our everyday lives.

In today’s data-driven world, researchers are busy answering interesting questions by churning through huge volumes of data. Some obvious challenges they face are due to the sheer size of the dataset they have to deal with. In this article, we take a peek at a simple business intelligence platform implemented on top of the MongoDB Aggregation Pipeline.

In this post, Toptal engineer Radek Ostrowski introduces Apache Spark—fast, easy-to-use, and flexible big data processing. Billed as offering “lightning fast cluster computing”, the Spark technology stack incorporates a comprehensive set of capabilities, including SparkSQL, Spark Streaming, MLlib (for machine learning), and GraphX. Spark may very well be the “child prodigy of big data,” rapidly gaining a dominant position in the complex world of big data processing.

Although the most wide-spread and supported way of running Django is on a Linux system (e.g., with uwsgi and nginx), it actually doesn’t take much work to get it to run on IIS. In this article, Toptal Engineer Ivan Voras walks you through a step-by-step tutorial, clearly explaining how to install Django on IIS.

When coming across the term “text search,” one usually thinks of a large body of text which is indexed in a way that makes it possible to quickly look up one or more search terms when they are entered by a user. This is a classic problem in computer science to which many solutions exist.

But how about a reverse scenario? What if what’s available for indexing beforehand is a group of search phrases, and only at runtime is a large body of text presented for searching?

Bitcoin blockchain is the backbone of the network and provides a tamper-proof data structure, providing a shared public ledger open to all. This article provides insight in blockchain technology, current status and its potential.

Since almost all smartphones today are equipped with location sensors, motion sensors, bluetooth, and wifi, today’s mobile apps can use context awareness to dramatically increase their capabilities and value. This article walks you through building a context aware app that employs complex event processing.

ESA’s Rosetta mission soft-landed its Philae probe on a comet, the first time in history that such an extraordinary feat has been achieved. Closely after that, Microsoft Open Sourced .NET.

The first event is a great step for mankind, and the latter is even greater for Microsoft!

There are thousands of different Android powered devices, with different screen sizes, chip architectures, hardware configurations, and software versions. Unfortunately, segmentation is the price to pay for openness, and there are thousands ways your app can fail on different devices.

Regardless of such huge segmentation, the majority of bugs are actually introduced because of logic errors. These bugs are easily prevented, as long as we get the basics right!

Here’s a quick rundown of the 10 most common mistakes Android developers make.

How do we understand and interpret the huge amounts of data coming out of simulations? How do we visualize potential gigabytes of datapoints in a large dataset? In this article I will give a quick introduction to VTK and its pipeline architecture, and go on to discuss a real-life visualization example.

React.js is a fantastic library. It is only one part of a front-end application stack, however. It doesn’t have much to offer when it comes to managing data and state. Facebook, the makers of React, have offered some guidance there in the form of Flux. I’ll introduce basic Flux control flow, discuss what’s missing for Stores, and how to use Backbone Models and Collections to fill the gap in a “Flux-compliant” way.