Initially this year, the media was awash with stories of a data compromise which involved Facebook and Cambridge Analytics. This raises major concerns over the long burning issue of data security and privacy. As technology has evolved we have started leaving a data trail for almost everything we do. Whether we use the GPS, online shopping, apply for jobs or send emails. All this data becomes fodder for companies to carry out analysis to understand us better. The question is where to draw the line, and where this obsession with data becomes a case of intrusion into our privacy. Recently, several governments are launching laws to ensure data privacy and security of its citizens. The answer, according to many visionaries, lies in changing the way we view data. Who owns the data? Is it the large corporations who collect & store it, or, the people who generate it? The answer lies somewhere midway. The clouds clear up when we realize that the answer lies in the way we view data. It’s an extension of ourselves, and we should have the ownership of how much to reveal and how much to keep private. With this in mind, the mantra that is catching up is leveraging Data Analytics and data management to design for data security.
As technology advances, organisations are driving all their energies into leveraging the most modern capabilities in order to boost their revenues. As data becomes an indispensable part of businesses, very often organisations struggle with gaining insights into the massive pool of unstructured data. However, with text mining, you don’t have to search too hard to discover relevant and important insights that would otherwise remain buried. Forward-thinking companies today are making the most of text mining and analytics that is enabling them to uncover trends and patterns and use them to improve products, enhance customer experiences and business revenue.
Data is the new oil of the 21st century. As an increasing number of organisations realise the benefits of taking a data-driven business approach, data is fast becoming one of the most coveted assets of an organisation. As technologies like the Internet of Things take off, the data deluge that we are experiencing today will grow 10 fold by circa 2020. We are looking at data volumes that will amount to 44 zettabytes! This data, called Big Data, can deliver transformational insights to organisations by providing massive quantities of information that can deliver tremendous business value. However, data by itself can hardly deliver the potential benefits it promises. For data to deliver value organisations have to make significant IT infrastructure and IT investments to store and analyze this data. This is not something that every organisation can afford. So, does this mean that those organisations who cannot make these Big Data investments cannot reap the rewards that data promises? Given the technologically advanced world that we are living in, it would be ludicrous to think so.
I say Blockchain. You think Bitcoin.
Anyone who has ever hired (or attempted to hire) a data scientist is well aware of the challenges: not only are they extremely difficult to find, cut-throat competition, and sky-high salaries further make them inaccessible.
An end-to-end capability with data analytics prompts companies to organise teams in a certain way. After all, everybody wants an optimised team that can come together, collaborate, and create results.
In the modern age of technology and data, the evolution of the banking sector has been noteworthy and commendable. It has been emerging with modern processes like providing Automated Teller Machines, online shopping, mobile banking, to name a few. However, with the ever-growing market volatility, unpredictability, market dynamics, and competitive environment, the banking institutions now need to rely on business analytics which gives them detailed insights into the need of the tech-savvy and ever-demanding customers.