‘Unstructured data’ is a generic term used to indicate all data that does not reside in relational databases. It accounts for all information that is not organised or structured. Examples of such information are social media conversations, electronic health records, documents, files, images, videos, audios, sales and marketing collaterals, emails, and even log files generated by computers.
IoT or Internet of things involves embedding sensors in traditionally used devices and enabling internet connectivity in them to collect a range of ambient data. IoT devices can sense their surroundings and communicate this data over the Internet, and they can in turn also be remotely controlled.
The population of our planet is nearly 7.5 billion out of which, more than half, that is approximately 4.1 billion are active online. With the availability of digital media, the menace of fake news has grown tremendously. So much that it can be called an era of fake news. Media houses worldwide have realised the importance of the deployment of technologies such as AI and ML to combat the spread of fake news. Even governments are urging the likes of Facebook and WhatsApp, the primary mediums via which the false news can be made viral, to find out the source of the data in case of fake news.
Recently, we witnessed how some of the biggest financial services companies in Australia such as CommBank and AMP are battling a full-blown crisis for being on the wrong side of the regulatory and compliance norms. Post the 2008 financial crisis, the pendulum in the financial services industry is swinging between heavy regulations and lower risk. Given the dynamic nature of the regulatory landscape, financial services organisations are under constant pressure to improve their regulatory, compliance and risk management capabilities because the cost of non-compliance is far greater than its apparent monetary impact. As the regulatory and business environments become more volatile than ever before, financial services companies are feeling the increased pressure of the constantly changing regulations such as BCBS 239/RDARR, CCAR, Basel III, and Dodd-Frank. However, keeping up with these regulations places a considerable amount of pressure on risk management.
Once upon a time, withdrawing or depositing money meant going to the bank, standing in snaking queues to gather tokens, and then wait some more for your turn. ‘Bank work’ was a valid reason to take half a day off from work. After all, if you didn’t make it to the bank, how could you make your money work?
Dresner Advisory Services’ “2016 The Internet of Things and Business Intelligence Market Study” presented an extremely detailed view of these growing technology areas. Among the insights was the revelation that the ability of organisations to manage big data / analytics and to manage a successful IoT initiative were highly correlated.
In a highly dynamic and competitive industry like manufacturing, embracing technological innovations like AI has become essential to survive, and is the only way forward.
For some businesses, global shocks have historically welcomed moments of truth.
In recent years, governments across the world including the U.S., U.K. France, India, New Zealand, and many others, are supplementing traditional approaches of functioning (paper-driven systems) with data-driven analytics to enhance the quality of services provided to their citizens. They are encouraging citizens’ participation in their decision-making processes by using social media. These governments have engaged data scientists, Chief Data Officers, and Chief Analytics Officers to better utilize the power of technology to make all public services accessible to citizens, and ensure efficient, transparent, and reliable information at minimal costs.
In the world of DVR’s, advanced set-top boxes, and the easy availability of on-demand content on the internet, media and broadcasting company have their work cut out for them to understand how well their content corresponds to customer demand. Information silos, legacy infrastructures, and changing business models act as major hurdles that media and broadcasting companies need to cross to convince their advertisers that the advertising charges are rational. Along with this, the rise of social networks is also adding to the complexity of how content is being curated and shared. According to a report by report in Fortune, “about 85% of Twitter users who are active on Twitter during prime-time say that they tweet about TV content they are watching”. This report also shows that in the U.S alone there were close to a billion T.V related Tweets, 90% of which came from a mobile device. As every social media user becomes a content curator, distribution platforms are looking to deepen their social integration to increase their reach, deliver the next big hit and hold the interest to the audience long enough to generate profits. Media and broadcasting companies today need real-time operational intelligence with deeper insights into their consumer behaviors and sales and profit trends. The good news is that despite the growing business complexity, today there is enough data that can be easily mined to gain information and improve the odds of the programming bets and serve the audience better.
