BIG DATA WITH DINO PEDRESCHI: THE ROAD AHEAD


The road ahead

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 data commons, network effects, Gdpr and our right to explanation.

Gaetano Albertini

In response to Ramesh Sigrún Rocca

Melina,

Big data is applied heavily in improving security and enabling law enforcement. I am sure you are aware of the revelations that the National Security Agency (NSA) in the U.S. uses big data analytics to foil terrorist plots (and maybe spy on us). Others use big data techniques to detect and prevent cyber attacks. Police forces use big data tools to catch criminals and even predict criminal activity and credit card companies use big data use it to detect fraudulent transactions.

Got one more: optimizing machine performance.  Big data analytics help machines and devices become smarter and more autonomous. For example, big data tools are used to operate Google’s self-driving car. The Toyota Prius is fitted with cameras, GPS as well as powerful computers and sensors to safely drive on the road without the intervention of human beings. Big data tools are also used to optimize energy grids using data from smart meters. We can even use big data tools to optimize the performance of computers and data warehouses.

Ramesh Sigrún Rocca

In response to Mélina Aubert Porcher

The topic of this discussion is the Road Ahead for big data.  What are some other fields in which big data is slated to make a difference?

Melina,

Big data is applied heavily in improving security and enabling law enforcement. I am sure you are aware of the revelations that the National Security Agency (NSA) in the U.S. uses big data analytics to foil terrorist plots (and maybe spy on us). Others use big data techniques to detect and prevent cyber attacks. Police forces use big data tools to catch criminals and even predict criminal activity and credit card companies use big data use it to detect fraudulent transactions.

Jessica

In response to Mélina Aubert Porcher

The topic of this discussion is the Road Ahead for big data.  What are some other fields in which big data is slated to make a difference?

I thought of one more--city optimization.  Big data is used to improve many aspects of our cities and countries. For example, it allows cities to optimize traffic flows based on real time traffic information as well as social media and weather data. A number of cities are currently piloting big data analytics with the aim of turning themselves into Smart Cities, where the transport infrastructure and utility processes are all joined up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to minimize jams.

Jessica

In response to Mélina Aubert Porcher

The topic of this discussion is the Road Ahead for big data.  What are some other fields in which big data is slated to make a difference?

I think one such area is Financial Trading.  High-Frequency Trading (HFT) is an area where big data finds a lot of use today. Here, big data algorithms are used to make trading decisions. Today, the majority of equity trading now takes place via data algorithms that increasingly take into account signals from social media networks and news websites to make, buy and sell decisions in split seconds.

Mélina Aubert Porcher

The topic of this discussion is the Road Ahead for big data.  What are some other fields in which big data is slated to make a difference?

Angelo Faustino Carboni

While AI is critical for self-driving cars, the military, commerce, AI-driven SEO and gaming, it’s poised to make the most human impact in medicine and human behavior. Imagine the UN leveraging neural networks and deep learning to discover what helps some communities thrive and others fall behind. Those lessons can then be leveraged into community builders, city planners, grants and projects.

Darius Tavas

In response to Gaetano Albertini

Big data is used to improve many aspects of our cities and countries. For example, it allows cities to optimise traffic flows based on real time traffic information as well as social media and weather data. A number of cities are currently piloting big data analytics with the aim of turning themselves into Smart Cities, where the transport infrastructure and utility processes are all joined up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to minimise jams.

I'd never thought about this but you are right, this is really happening and it's improving our lives. But what happens when technology simplifies our live to a degree when we don't need to go outside, meet with friends and experience nature. Maybe one day we won't even need to walk to get to where we want, not even a simple move and we are there. How is advanced technology going to solve such problems?

Edward Wachter

Technology such as predictive analytics will never be enough on its own to gain meaningful insights from data.  It is essential to apply specialist industry (and sometimes legal) knowledge to the data analytics to identify the factors which have the most impact on potential outcomes.

Prof. Dr.-Ing. Helga Breitner

In response to Анета Владимирова

@Klas, here is an interesting discussion on some of the challenges of Big Data by Dr. Borne.  They all start with the word V: Volume, Variety, Velocity, Veracity, Validity, Value, Variability, Venue, Vocabulary, and Vagueness :)

Aneta, this was a good post about the challenges of big data.  The definition of big data also involves letters that start with V: You have big data if your data stores have the following characteristics:

  • Volume: Big data is any set of data that is so large that the organization that owns it faces challenges related to storing or processing it. In reality, trends like ecommerce, mobility, social media and the Internet of Things (IoT) are generating so much information, that nearly every organization probably meets this criterion.
  • Velocity: If your organizations is generating new data at a rapid pace and needs to respond in real time, you have the velocity associated with big data. Most organizations that are involved in ecommerce, social media or IoT satisfy this criterion for big data.
  • Variety: If your data resides in many different formats, it has the variety associated with big data. For example, big data stores typically include email messages, word processing documents, images, video and presentations, as well as data that resides in structured relational database management systems (RDBMSes).
Gaetano Albertini

Big data is used to improve many aspects of our cities and countries. For example, it allows cities to optimise traffic flows based on real time traffic information as well as social media and weather data. A number of cities are currently piloting big data analytics with the aim of turning themselves into Smart Cities, where the transport infrastructure and utility processes are all joined up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to minimise jams.

Fabricio Ruiz

In response to Professor Dodds

I have heard that Blockchains offer an alternative type of data ownership and data marketplace.  Does anyone know what Blockchains are and how they can be used to build a global data commons?  Thanks.

Hello,

The Convergence Ecosystem will lead to a global data commons. It’s not inevitable, but blockchains and distributed ledgers are disruptive technologies that change the structure of the data value chain. Yes, I know that word is overused, but in this case it is true. The point of value capture in the value chain will change. Instead of web companies capturing value and profit by controlling data, data could be stored on decentralised data file systems and blockchains making it accessible to all, not just a select few platforms that collected it.

Dorothea Petrescu

Aneta,


Excellent post.  I just want to add one clarification.  The V-based characterizations you have listed represent ten different challenges associated with the main tasks involving big data.  They are: capture, cleaning, curation, integration, storage, processing, indexing, search, sharing, transfer, mining, analysis, and visualization.

Professor Dodds

I have heard that Blockchains offer an alternative type of data ownership and data marketplace.  Does anyone know what Blockchains are and how they can be used to build a global data commons?  Thanks.

Анета Владимирова

@Klas, here is an interesting discussion on some of the challenges of Big Data by Dr. Borne.  They all start with the word V: Volume, Variety, Velocity, Veracity, Validity, Value, Variability, Venue, Vocabulary, and Vagueness :)

Klas Eriksen

Diversification of opinion is an important issue to Big Data.  We should understand the advantages and challenges involved if we want to preserve and foster democracy in our society.

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