Data Science
While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.

6 Ways Business Intelligence is Going to Change in 2017
Data-driven businesses are five times more likely to make faster decisions than their market peers, and twice as likely to land in the top quartile of financial performance within their industries. Business Intelligence, previously known as data mining combined with analytical processing and reporting, is changing how organizations move forward.

Stream Processing Myths Debunked
This post appeared originally in the dataArtisans blog Six Common Streaming Misconceptions Needless to say, we here at data Artisans spend a lot of time thinking about stream processing. Even cooler: we spend a lot of time helping others think about stream processing and how to apply streaming to data

How to transform your business with Artificial Intelligence
Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit’s work involves applying machine learning techniques to

Journey Science: Combining 18 Data Sources + 1 Billion Interactions to take UX to The Next Level
Journey Science, being derived from connected data from different customer activities, has become pivotal for the telecommunications industry, providing the means to drastically improve the customer experience and retention. It has the ability to link together scattered pieces of data, and enhance a telco business’ objectives. Siloed approaches are becoming

Get the facts straight: The 10 Most Common Statistical Blunders
Competent analysis is not only about understanding statistics, but about implementing the correct statistical approach or method. In this brief article I will showcase some common statistical blunders that we generally make and how to avoid them. To make this information simple and consumable I have divided these errors into

Why building an IoT product isn’t like anything else
Dataconomy has joined forces with Alexandra Deschamps-Sonsino, one of the world’s leading IoT entrepreneurs and influencers, to run an exclusive, 3-day IoT workshop in Berlin, February 24-26, 2017. Alexandra will host an intensive course where she will provide guidance and share everything she knows about how to build a business that offers

Analytics Strategies for the Internet of Things – Getting the most out of IoT Data
IoT data offers answers to a simple question: “Are things changing or staying the same?” There are new data streams generated each day, that make it possible to quantify the formerly unquantifiable. The Internet of Things (IoT) enables us to measure processes and react more quickly to ever-evolving conditions, not

Data Mining for Predictive Social Network Analysis
Social networks, in one form or another, have existed since people first began to interact. Indeed, put two or more people together and you have the foundation of a social network. It is therefore no surprise that, in today’s Internet-everywhere world, online social networks have become entirely ubiquitous. Within this

How to avoid the 7 most common mistakes of Big Data analysis
One of the coolest things about being a data scientist is being industry-agnostic. You could dive into gigabytes or even petabytes of data from any industry and derive meaningful interpretations that may catch even the industry insiders by surprise. When the global financial crisis hit the American market in 2008, few

Cognitive Computing: How to Transform Digital Systems to The Next Level of Intelligence
Cognitive Computing: What’s in a Name? Cognitive computing might be one of the many buzzwords that you today hear and see alongside such terms as Artificial Intelligence, Machine Learning, Deep Learning and Big Data. However, quite opposite to these terms, Cognitive computing, as it seems, does not have a clear