Category : Big Data & Analytics

Big Data & Analytics

Observations, thoughts and knowledge generated by our experience in big data and predictive analytics industries.

How telecommunication companies utilize data analytics

For just a decade, the telco sector is nothing like what it was like. Telecommunication companies faced transforming changes and data is the centerpiece. First, mobile telecom companies shifted their focus from voice vendors to data carriers. Fixed services became obsolete and experience downfall. Competition became more fierce than ever because a market maturity means a limited amount of end users even though IoT are percepted as a potential booster. So, such situation should be examined more as an opportunity than like a dangerous threat.

Actionable Data Analytics: 3 Different Approaches in Strategy Optimization

Strategy optimization (SO) is a key process, which provides a substantial growth for retail and utility companies.

Generally the application of SO is directed to campaign management – helping the organizations to interact in a better way with their customers. The most popular optimization goals are increase of the revenue, popularity or customer loyalty, reducing the taken risk and so on. The multi-strategy optimization is also an option, where a balance between contradictory objectives is investigated, like the fine tuning between profit and loss.

How Predictive Analytics Knows When You Are Going to Quit Your Job

Predictive analytics is full of tools and approaches enabling it to reveal key insights in almost any area. We already discussed the impact of Data Analytics in HR and we are delivering further.
Recent blog post by Toshi Takegushi, part of MathWorks team reveal in an interesting and comprehensive way how a predictive analytics model can be triggered on job-related data sets for scoring which employee is planning to quit its position. He relied on machine learning algorithms for predicting future events by utilizing historical data.

Artificial neural networks and credit risk modeling

In this blog post, our chief scientist Alexander Efremov PhD. is discussing the application of direct and recurrent artificial neural networks (ANN) in some methodologies for credit risk models.

Inputs of ANN could be the available individuals’ characteristics, like age, income, marital status, credit bureau data, etc. The outputs are the probability the applicants to have a good performance as loan-holders, the individuals’ response to some actions, etc.

Google Data Studio Now Available for (Almost) Everyone

Google just surprised the data savvy community by withdrawing the limitation of 5 reports created within the free trial in their Data Studio product. The change was announced by Nick Mihailovski, product manager for Google Data Studio, in a recent blog post and via the official Google Analytics Twitter account.

Chatbots Powered by A.I.

The first contribution of an artificial intellect, known today as A.I. is the hacking of Enigma coding machine. The story of Alan Turing was intriguingly impersonated by Benedict Cumberbatch in The Imitation Game drama movie. It is acknowledged that Turing`s success with creating an algorithm and machine that managed to break the Enigma code has saved millions of lives during the WWII.