Apr 2018


The world of marketing products and services has changed dramatically almost overnight before many of us even managed to take notice of how deep the change actually was. Suddenly we opened our eyes to the reality in which reducing any business activity to sheer manufacturing of goods and offering services is a ready-made recipe for disaster! Nowadays any project must be preceded by a detailed Customer Profiling process in order to provide detailed and accurate information concerning customer’s needs and expectations. The right decision, which carries the probability of success has to be a customer-centered one, with possibly all these needs and expectations to be met.

Mar 2018

Natural language processing – never-ending story

At the first sight the issue of language processing seems to be the one which an average user of a computer/smartphone and the like, simply takes for granted given the constantly developing technology we already have at our disposal and, at the same time, provides seemingly unlimited possibilities. However, even a casual look at the brief Wikipedia (translated) definition proves the fallacy of such thinking: “Natural Language processing (NLP) – the interdisciplinary scientific field which joins the issues of natural intelligence         and linguistics, dealing with the automatization of language analysis, understanding, translation and generating the natural language by computer.”

Jan 2018

Sql vs NoSql – Which one is for you?

As old as it is, we still have the debate: what kind of database should be used for my system? The most common answer is usually: “it depends”. We know that it does depend on many different factors. Therefore I would like to cover some of them, which can help you in identifying and selecting the proper one, based on the requirements for your project.

Dec 2017

Which front-end framework to choose for your application? Angular , Ember js or React.js

It goes without saying that the JavaScript environment with its huge number of tools, libraries and frameworks, makes an impressively rich but at the same time quite sophisticated world. Yet, such variety might be at times tricky and confusing. Moreover, the vast space ruled by imagination and creativity might be easily interfered by a simple fact of being unsure about which library or framework to select. It is by no means a straightforward task as the scene of JavaScript is volatile with new frameworks seeing the light almost every month while the existing ones are constantly updated, the example of which being AngularJS. Keeping in mind that the right choice of the front-end framework might either make or break our project, let us have a look at the most popular JavaScript frameworks.

Nov 2017

It is here to stay! (un)comfortingly about fraud detection

„Our experience has taught us that if your organization hasn’t created and thoroughly tested, repeatedly, a cyber incident response plan across all business areas and personnel, as well as performed simulations of cyber attacks, you won’t do a good job of responding when it occurs for real. We see over and over that it is very difficult to make good decisions when you’re responding to a real attack in the heat of the moment.” /David Burg, Cyber Security & Privacy Leader PwC/

Sep 2017

Spark vs. Hadoop – a settled dilemma?

It goes without saying that for the last decades a vast majority of institutions, companies, firms and the like, have dealt with the Big Data reality, which required or just forced the urgent necessity to create processing platforms capable of storing and analyzing this vast amount of data. Here is why Hadoop and Spark, later on, around the year 2008, came into picture.

Aug 2017

An Apache Spark application for big data processing in a real estate market software system.

High-volume data streams and a great number of reports for the real estate market was what we were confronted with on one of our client’s projects. More specifically, the client faced a tough scalability problem: the property market reports generated from such a big data set took up to 3 hours to produce (just for 100 markets). Worse, this time was increasing as each day a few million new records were fed to augment the data set. In a step to resolve the problem, the client decided to invest in a new system architecture.

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