In years past, Business intelligence (BI) was something only big blue chip companies could enjoy. Mainly because employing analytics software was expensive, and it required building data centres and hiring IT specialists, who are also expensive. BI systems have, over time, become less expensive and have become a useful way of gathering corporate data and correlating that data in a way that will produce useful observations to the business.
However, times have changed. Data is getting bigger every day, in terms of volume and variety, and businesses need Data Science if they are to capitalise on market opportunities faster than their competitors. BI and Data Science are distinctively different beasts. BI systems deliver answers to the questions you know you need to ask. They are usually single systems that don’t help you to predict anything: they may help you to view the relationships of various variables, but they don’t help you to easily obtain any new meaning from those relationships, nor do these systems help you to apply insights to new data. Data science driven Big Data programmes, on the other hand, may consist of several technologies and should work to provide customer insight that companies can use to predict present and future patterns, thus enabling them to react customer behaviour accordingly.
Using data science allows organisations to stop being retrospective and reactive in their analysis of data, and start being predictive, proactive and empirical. Moving from traditional business intelligence (BI) to adopting data science is a huge shift and a fundamental part of becoming a data-driven organisation. By taking an empirical view of its data and implementing tools like Hadoop and NoSQL databases, a public sector organisation can transform its operations entirely. Whether that means taking the pressure off the data warehouse, and so reducing cost; or driving efficiency improvements through recommendations for process changes, the opportunity is enormous.
To survive and prosper in the increasingly competitive market as well as to be able to resolve complex business problems, drive innovation and growth, companies must shift their focus from traditional BI to data science. Data Science changes the game for virtually all industries. When used in conjunction with predictive analytics, it allows organisations to achieve real-time insights and make future predictions that increase understanding of customer behaviour, improve response to customers and deliver a tangible competitive advantage.
