Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.
Everything in our life right now is full of data; from the food that we eat to our physical routine. Known as the “quantified self” or QS, it’s actually an emerging trend in big data science. Since smart devices are now embedded with advanced motion sensors, data scientists can benefit from the personal data collected from these devices. Is quantifying oneself just a passing fad or gimmick? Can technology and big data really help people live healthier lives?
Marketing in 2014: every day, tracking software peers into consumers’ spending histories. Meanwhile, companies scour our personal information for any crumbs of data that might be used in the pursuit of a sale. This is ‘big data analysis:’ the Big Brother marketing strategy that has permanently altered the face of retail.
Asia: a huge, diverse, and rapidly changing society. One could even say it has high volume, variety, and velocity. Here in Malaysia we value a good technology festival, and we've been discussing Big Data for at least a year (the veracity of this claim is backed up by the list of previous Big Data Malaysia meetups, which is by no means the only local group discussing these issues). Now that I've paid nominal (and perhaps somewhat cheeky) obligatory homage to the 3+2Vs of Big Data, let's get on with what actually happened during Big Data Week 2013 in Kuala Lumpur.
Hundreds of terabytes. That’s the amount of Big Data being generated by multi-national corporations, every day. While terrifying for some, others see it as an opportunity to fundamentally transform how their organisations operate and make decisions. According to Gartner, Big Data is forecast to drive $34 billion of IT spending in 2013. But what most people think of when they hear the term ‘Big Data’ almost certainly isn’t what I'm talking about. What many organisations still regard as Big Data – unstructured information contained in emails, electronic documents, social media interactions etc – is just a thin layer in the vast strata of data available to them.
No matter what the industry, forming the intelligent discovery environment required to generate competitive advantage from big data can be extremely tough. Although traditional analytics and methodologies are fairly robust, in the rush to generate insight from big data projects, the introduction of new analytics technologies and previously unfamiliar open source data storage tools like Hadoop will inevitably create a learning curv