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The Importance of Data Strategy for Startups

Data strategy is the one thing many companies need, especially startups, but they don't know it. So, what is a data strategy? How can we define it?

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Data Science: The Art of Communication

This is a follow-up to the three-part series on 'How to Become a Data Scientist’. It is effectively Part 2a, because it became apparent that the second instalment on ‘Learning’ did not encompass sufficient detail on how to improve the essential, and often overlooked skill of communication.  

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Industrial Machine Learning: Where are We Now?

The rapid growth of Machine Learning and Artificial Intelligence applications is not only in the software domain. As the use of sensors in industrial applications becomes more mainstream, the large amount of data gathered can be used to train algorithms. This, in turn, results in rapid increases in efficiency.

In this article, chemical engineer and researcher Hermes Ribeiro Sant Anna gives an overview of how Machine Learning and Artificial Intelligence are used in industrial production facilities. 

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How to Become a Data Scientist (Part 3/3)

This is Part Three in a three-part series examining how to become a data scientist. Supported by extensive research and expert opinions, it aims to provide a comprehensive guide to anyone interested in this field, irrespective of background and level of experience. The topic of Part Three is: 'The Job Market'.

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How to Become a Data Scientist (Part 2/3)

This is Part Two in a three-part series examining how to become a data scientist. Supported by extensive research and expert opinions, it aims to provide a comprehensive guide to anyone looking to move into this field, irrespective of background and experience. The topic of Part Two is: "Learning".

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How to Become a Data Scientist (Part 1/3)

This is Part One in a three-part series examining how to become a data scientist. Supported by extensive research and expert opinions, it aims to provide a comprehensive guide to anyone looking to move into this field, irrespective of background and experience. The topic of Part One is: "What is Data Science?".

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Creating a Data-driven Culture Within an Organization: Sports Clubs

This fun-to-read post describes the similarities between implementing a data-driven culture within a sports team and within a company. 

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Moneyball: Sports Analytics in Soccer to Predict Performance and Outcomes

Soccer's dynamic nature makes it a notoriously difficult game to predict. But if you have enough data and attributes, you can increase the accuracy of your predictions by using advanced machine learning and artificial intelligence methods.

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Talent Analytics: The Art of Predicting Employee Retention

As the volume of employee data at organizations' disposal increases, novel ways to make use of this data can be defined. By using simple metrics to define your current, past and potential employees, you can increase retention and make sure you hire people who are a good fit culturally. 

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BI on Steroids! Providing Value to Barcelona Residents

This post gives an extensive overview of the development process and the capabilities of Infobarris, a tool developed to support the analysis of health and its determinants in the neighborhoods of the city of Barcelona. 

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Are Businesses Ready To Take Advantage of The Growing Number of Data Scientists?

There's significant growth in the number of data scientists in the past four years, but this growth is not matched with a growth in the number of data-savvy managers. Will this mismatch lead to problems in the near future?

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The Case for Using Data Simulators to Drive Big Data Success

Data simulators can be an important asset to a company because they can emulate the data you don't have access to, and help you gauge the compatibility of your tools accordingly.

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Practical Text Analytics

This post dives into different types of text analytics and gives three different examples from the industry to better convey the ideas behind these methods.

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Time Series in Atmospheric Sciences

Predictive analytics can save lives, and Majid Khattak demonstrates how to do just that by using an index of the El-Nino-Southern Oscillation phenomenon to predict weather patterns that lead to severe storms. 

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Suggestion and Opinion Mining from Qualitative Surveys

Analyzing traveler feedback on a newly opened airport in Asia, Ravi gives us a walkthrough of his approach to a specific sentiment analysis problem.

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Short-Term Forecasting of Electricity Demand

Forecasting demand for electricity is of immense importance both for researchers and for industry experts. By accurately forecasting demand, power suppliers can prevent overloads, and can operate more efficiently with a higher profit margin.

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Bringing HR Analytics to Life - Unleashing the Power of Your Organization

A detailed article on HR Analytics, explaining what it is, how it works, and how organizations can leverage it to improve their culture and effectiveness.

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Piecewise Linear (Affine) Programming

Linear programming is a mathematical problem solving technique widely used in various industries to optimize operations and is widely recognized as one of the core concepts of Operations Research. In this post, Professor Lahiri gives a summary of the technicalities of this method. 

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Demystifying Facebook's Ad Match Algorithm

How Facebook's Ad Matching algorithm works and how marketers can use this knowledge to their advantage.

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Predicting the 2016 Presidential Election

A Predictive-Descriptive Artificial Intelligence-based expert computer system predicts a Democratic landslide victory in the race for the White House in 2016.

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K Means Clustering in Text Data

K means clustering is a method that is often used in sentiment analysis. This post gives an overview of how to implement this method.

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Data Products in 2016

Machine learning is becoming a ubiquitous characteristic in all industries.  As the world makes this transition, we explore the role of services, the applications of open algorithms, and the creation of IP in developing data products for diverse markets.

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Digital Analytics: Let’s Make It Simple

A brief overview of digital analytics and steps that digital analytics experts take to leverage data to improve business conversions.

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Big Data and Analytics Skills for a Data-Driven Enterprise

How organizations can effectively hire and leverage Big Data talent, and how the internal structure of an organization can be tailored to fit the needs of a data-driven enterprise.

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