Nowadays, companies are besieged by information and the possibilities of new IT solutions. With the rapid advancements in information technology and high speed Internet, companies now have access to huge amounts of information, processing and sharing systems regarding customers, their demographics, and their…

Missing data present significant challenges to trend analysis of time series. Straightforward approaches consisting of supplementing missing data with constant or zero values or with linear trends can severely degrade the quality of the trend analysis, which significantly reduces the reliability of the trend analysis. …

Summary:  The addition of AI capabilities to our personal devices, applications, and even self-driving cars has caused us to take a much deeper look at what we call ‘User Experience’ (Ux).  A more analytical framework identified as Cognitive Ergonomics is becoming an important field for data scientists to understand and implement.

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Introduction

Business ventures based on existing or disruptive business models taking on the route of Initial Public Offering are always a challenge to investors who want to profit from early investment into those would be “unicorn IPO”. A good investment may get worse before it gets better. Others may get worse and never recover. Aside from the macroeconomics and consumer trends that could affect the outcome of such investments, the fundamentals of these new public offerings…

Understanding Data Roles

By Michael Burke

With the rise of Big Data has come the accompanying explosion in roles that in some way involve data. Most who are in any way involved with enterprise technology are at least familiar with them by name, but sometimes it’s helpful to look at them through a comprehensive lens that shows us how they all fit together. In…

We all know the phrase “with great power comes great responsibility”, what most people are unaware of is that data is the new world power.

All over the world, across multiple industries, businesses and individuals alike are beginning to harness the power that good data can…

Much like Dr. Frankenstein’s creation, the modern Data Scientist is made up of different parts to fully create an unstoppable data science Prometheus. To get ahead, you must exhibit both technical and soft skills; a smorgasbord of different technical, personal and business skills. 

Frankenstein made a monster of different body parts, so let's have a bit of fun this Halloween, and see what his Data Scientist be made…

The difficulty to migrate a stored procedure to other databases is always a subject of criticism. This is seldom forgotten every time when the shortcomings of the stored procedure are listed.

The migration of a stored procedure for handling the complex business logic is particularly problematic because its coding depends on the unique features and syntax of different databases and thus it needs to be recoded with the database changed. The cost won’t be very high if…

What is SAP Fiori? Well, in simple words, the Fiori buzz can be defined as newly written series of apps by SAP which is meant to address most frequently and broadly practiced SAP functions- like information lookups, workflow approvals & self-service tasks. It’s to stress here that SAP is building the Fiori applications on its state of the art SAPUI5 user-interface framework.

Earlier business software programs often lacked a smooth user experience but Fiori is claimed to change all…

To read my most recent article about chaotic systems, click here. 

The logistic map is the most basic recurrence formula exhibiting various levels of chaos depending on its parameter. It has been used in population demographics to model chaotic behavior. Here we explore this model in the context of randomness simulation, and revisit a…

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Featured Resources and Technical Contributions

• Naive Bayes - Video Tutorial …

A person will ordinarily search the contents of a database using matching keywords and tags.  Sophisticated databases might allow for filtering:  for example using NOT, AND, OR on a number of keyword strings such as both titles and product descriptions.  It is not normally possible to submit, say, a personality profile to a database - or a personality profile and a setting.  Searching for “serial murders subway terminals” might lead to event information about precisely this, apparent serial…

This article was written by Dallin Akagi.

What is deep learning?

I like to use the following three-part definition as a baseline. Deep learning is:

1. a collection of statistical machine learning techniques
2. used to learn feature hierarchies…

With the world changing so rapidly, every company or organization that adapts to the changes becomes an example for all others. One very recent example for all companies to learn from and implement in their own decision making is the transformation of RELX Group to a leading global information and analytics…

When I was beginning my way in data science, I often faced the problem of choosing the most appropriate algorithm for my specific problem. If you’re like me, when you open some article about machine learning algorithms, you see dozens of detailed descriptions. The paradox is that they don’t ease the choice.

In this article, I will try to explain basic concepts and give some intuition of using different…

Research fields usually follow the practice of categorizing continuous predictor variables, and they are the same who mostly use ANOVA. They often do it through median splits, the high value above the median and the low values below the median. However; this it seems is not that good an idea, and enlisted are some of the reasons to it:

• Median tends to vary from sample to sample. This makes the categories in various samples have various…

And what we can do about it…