BIG DATA WITH DINO PEDRESCHI: THE AGE OF DATA


The age of data

Dino Pedreschi, Professor of Computer Science at the University of Pisa and co-lead of KDD Lab - Knowledge Discovery and Data Mining Laboratory, talks about big data, machine learning and intelligent systems.

Magda Ivone Nussbaum

BIG data is suddenly everywhere. Everyone seems to be collecting it, analyzing it, making money from it and celebrating (or fearing) its powers. Whether we’re talking about analyzing zillions of Google search queries to predict flu outbreaks, or zillions of phone records to detect signs of terrorist activity, or zillions of airline stats to find the best time to buy plane tickets, big data is on the case.

János Pataky

Today, the Croatian government is already using an IBM IT infrastructure to provide e-government services to Croats in minutes and hours, rather than the days it traditionally required. The latest government project saw the Croatian national population registry being integrated into the system along with the information systems of the ministry of finance and ministry of public administration, to name just a few.

Jamyang Khachaturyan

In response to Ruben Gansen

We live in the age of data, where everything that surrounds us is linked to a data source and everything in our lives is captured digitally. The physical world around us has turned into raw information: internet, video, call data records, customer transactions, healthcare records, news, literature, scientific publications, economic data, weather data, geo-spatial data, stock market data, city and government records.

We call it big data—and it is indeed getting bigger, growing exponentially with each passing day. Luckily, the opportunities to take this data and marry it with analytics to improve all aspects of our lives are also growing exponentially.

Ruben Gansen

We live in the age of data, where everything that surrounds us is linked to a data source and everything in our lives is captured digitally. The physical world around us has turned into raw information: internet, video, call data records, customer transactions, healthcare records, news, literature, scientific publications, economic data, weather data, geo-spatial data, stock market data, city and government records.

Tonje Rodberg

Thanks to Big Data, every Web ad you will soon see on Facebook and across the Web will have been bid upon in real time by advertisers who will pay based upon your perceived value as a potential customer.

Marie Bourgeois

The new world of mass personalization requires relationships built upon mutual trust. And more than at any time in history, companies – and soon, big government, big education, big everything – are going to have to work hard to earn that trust from each and every one of us.

Gaetano Albertini

Data mining delivers vast quantities of data, often unstructured. Marketers are more familiar with interacting with data via dashboards that structure data to deliver analysis of commonalities, such as averages, ratios and percentages. The goal is to aggregate data in order to report a result, search for a pattern and find relationships between variables. Assumptions are made by humans, and data is queried to attest to that relationship. If valid, testing may continue on additional data.

Sárika Zsuzsi Görög

In response to Volodya Kuznetsov

The artificial intelligence (AI) industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology.

Advances in AI now mean product developers can create innovative and leading-edge products and services that, until recently, would not have been within reach of the average marketing budget.  These new products and services entering the market make AI adoption lower risk with a focus on delivering practical and immediately impactful results. Many past attempts resulted in expensive and custom-developed marketing technology projects that left their scars.

Volodya Kuznetsov

The artificial intelligence (AI) industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology.

Sigmund Gerhard

Machine Learning is defined as a practice of using the suitable algorithms to utilize the data for learning and predict the future trend for a particular area. Machine learning software contains the statistical and predictive analysis that used to recognize the patterns and find the hidden insights based on perceived data. The best examples of machine learning application is Virtual assistant devices like Amazon’s Aleza, Google Assistance, Apple’s Siri, Microsoft’s Cortana and social platforms like Facebook works on Machine learning principles and predict or respond as per the past behavior of the users to suggest them the most suitable things.

Please login or register to leave a response.