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Data Science often points to the need for change - and change can be difficult. Get tips from TDWI for making your foray into data science a success.
Luca Naso's insight:
Most organizations have realized both the potentials and the difficulties of Big Data.
Here is a TDWI checklist report that can help to get organized before beginning a new project: 1. Identify key business drivers 2. Create an effective team 3. Emphasize communication skills 4. Embrace visualization and storytelling 5. Access all the data 6. Operationalize Analytics 7. Improve governance
The 3 elements that I particularly consider crucial are: A. Set clear goals B. Invest on the team, not on individuals C. Communicate and operationalize your project findings 
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Over the last few years, state-sponsored data collection has come to the fore thanks to whistle-blowers and ex-spies. Since then, the clamor for calling the line between private and public data for...
Luca Naso's insight:
Data collection is not a news (cookies exist since the beginning of the internet). Now it has expanded into our life in the "real world", and it is bringing incredible benefits to:
Nevertheless Big Data is a double-edged sword, and cuts both ways. Although the potential of Big Data to do good is great; it is just as easy to manipulate and abuse.
Big Data: hero or villain?
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we talk a lot about how gadgets are changing how we communicate and so on - but could the devices we all carry around with us now also be about to make us a whole lot healthier?
Luca Naso's insight:
Collecting lots of data isn't just about making more accurate Netflix recommendations.
Rather than just judge us on what we say in an eight minute consultation with our GPs, maybe they'll be able to pull up our health data and analyse it properly? Scientists would be able to more easily identify the effects and side-effects of different treatments, and more quickly develop and bring new treatments to patients. Of course - there is one awkwardly massive downside to this. Privacy concerns.
Fàtima Galan's curator insight,
November 26, 2013 11:50 AM
" Luca Naso's insight:Collecting lots of data isn't just about making more accurate Netflix recommendations.
Rather than just judge us on what we say in an eight minute consultation with our GPs, maybe they'll be able to pull up our health data and analyse it properly?
Scientists would be able to more easily identify the effects and side-effects of different treatments, and more quickly develop and bring new treatments to patients.
Of course - there is one awkwardly massive downside to this. Privacy concerns. "
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Ever wonder how Las Vegas casinos catch card-counting teams at Blackjack tables, like the MIT team immortalized in the film “21” with Kevin Spacey? They use many techniques, some of which are confidential, but one we know about is their use of Entity Analytics on many intersecting streams of information about their patrons or potential employees.
Luca Naso's insight:
1. Integrate your analytics stovepipes (put all data in the same pool) 2. Integrate real-time and batch analytics for deeper insight (real-time is King, but also Kings need suggestions)
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Foreign Affairs — The leading magazine for analysis and debate of foreign policy, economics and global affairs.
Luca Naso's insight:
This is one of the best article I have ever read on Big Data.
Big Data is not just about having more data, or at a higher rate, or in different shapes. It is a profound shift in the way we deal with data analysis. Actually 3 shifts:
1. from "sample" to "population" 2. from "clean" to "messy" 3. from "causation" to "correlation"
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It's time to learn up about the data revolution, and begin to understand your data rights.
Luca Naso's insight:
Here are 5 wonderful TED/TEDx talks about Big Data. My favourite is the 3rd one.
1. Jennifer Golbeck Big Data can predict your intelligence from social media behaviour. "My goal is to improve the way people interact online"
2. Alessandro Acquisti Analytics can make our life better, but we must pay a price for that. We trade autonomy & freedom for comfort. 3. Jer Thorp We have the chance to build the Big Data Business in the good way, just bring the human element into the story. 4. Kelvin Slavin Data, particularly algorithms, are changing the very landscape of our world.
5. Philip Evans Value cannot rely just on having the data, but on leveraging them. Technology is what is driving the business strategy, and today it is time for data-driven business.
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The data to measure the happiness of a city is already all around us, in the tweets we send on an hourly basis to the profiles we share on Facebook.
Luca Naso's insight:
The Internet of Things can dramatically improve the quality of our city life. - In Birmingham, lamp-posts are being fitted with sensors that can transmit information about cloud cover to offer hyper-local weather forecasting. - In Seattle 5,000 pieces of rubbish were geo-tagged and tracked around the country for three months to find out whether recycling was really efficient. - A project in Singapore offers advanced weather forecasts to taxi drivers to get them to places in the city ten minutes before it starts to rain. - In Germany a3D dynamical city-model was used to show people what the impact of a new railway line would be.
All this is fantastic but scary at the same time and shifts the way the world works. The danger is that when smart cities become a reality, individuals will not be able to control the ways they are monitored or what happens to the information. The issue has huge implications for society and is going to need serious debate.
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Two esteemed professors at an Ivy League school say that while those in the marketing world continue to struggle with how to handle all the data they are accumulating, they may in fact be wasting their time and more than likely need to go on what they refer to as a “data diet.”
Luca Naso's insight:
I believe that the focus should move from the amount of data to the insights one can gain from them.
Company should go after Big Data not because it is cool and trendy, but only because it can improve their business in so many different ways.
State your goals, and then you decide to keep only the data you need, be it huge, big, or 'slim'.
And when it comes to privacy (about which data to collect), my suggestion is: always put the interest of the customer first, and you will be largely rewarded.
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good new