After a long day, I settled down for some binge-watching on Netflix (you may be a Prime fan). I had been watching this series Ozark and wanted to watch something different that evening. Netflix had some recommendations for me – similar dramas, suspense thrillers that Netflix thought I would like based on what I had been watching. I stopped to wonder how Netflix generates content recommendations that appeal to my taste and do so for millions of other users globally.
How do algorithms work to find me my recommendations?
I am equally fascinated by how fashion brands like Burberry provide ‘personalised’ experience and buying suggestions. Not to mention how the retail and tech giants like Walmart, Amazon and Google seem to know more about you than your own mother.
All these companies have one thing in common: Big Data and Analytics.
What is Big Data?
The concept of big data has been around for several years. The term big data refers to data that ar
e so large, complex, and comes in so fast that they are difficult to process using traditional methods. It gained momentum in the 2000s when industry analyst Doug Laney articulated a new definition for big data as three V’s: Volume, Velocity and Variety. Companies are evolving from being “knowing” organizations to “learning” organizations.
What is Data Analytics?
Big Data Analytics in simple terms can be defined as the application of advanced analytical techniques to big data. These techniques might typically include variety of tools like statistics, data mining, AI, predictive analytics and natural language processisng (NLP). The hottest trend in business intelligence today is amalgamation of these two technical entities: Big Data and Big Data Analytics.
Why is Big Data Important and why are companies using Analytics?
Gathering big data is not enough, you also need to know what you do with it. If data are the crude oil then analytics is knowing how to refine them. into actionable business insights unleashing their potential. Most of the top-performing organizations identify data analytics as to the ‘differentiating factor’ from the competition in the industry. Here’s it is how:
Boost customer acquisition and retention
Many companies are now using data analytics to understand and predict consumer behaviour. The information is in turn being used in advertising algorithms. Amazon found another use of such data – maintaining customer relations by providing faster and more efficient customer service.
Marketing Insights – focus on targeted adverts.
In the modern age, personalization is highly valuable and a differential factor for consumers. Real-time analytics have made it possible for companies to deliver more targeted and precise service and product options to their users.
Product Innovation and Development
Data Analytics provides valuable information and reveals the future trends. Companies can take advantage of big data to branch out to different avenues and open up new revenue streams. Amazon’s Whole Foods and Amazon’s Fresh are perfect examples of how Amazon utilised the analysis of consumer grocery buying behaviour from its huge supply chain database. It applied this acquired knowledge to diversify and establish new innovative businesses.
One of the basic premise for any business to be profitable in the long run is its ability to identify and mitigate business risks. The wide variety of innsights provided by data analytics come in handy for institutions to develop better risk management solutions. The future is to be able to carry out real-time risk analysis.
How can you build your career in Data Analytics?
Have you got a knack for numbers and an analytical mindset? Data analytics may be the right fit for you. As an analyst, you will be responsible for analysing and understanding the trends in big data and help improve business processes. You can launch your data analyst career with these simple steps:
Earn an Information technology, CS or statistics bachelor’s degree
If you are just starting off your career, earning a bachelor’s degree is a great place to launch your career in the right direction.
Gain analytics work experience
No education degrees are useful unless they are gainfully applied. Gain valuable experience while in school or after. Entry-level positions will provide you with much needed on-the-job training which is otherwise difficult to obtain.
Advance your Analytics career with a Masters
Work experience and a bachelor’s degree may get you to a certain level of success. For further career development and growth in the field and into the management, you should consider pursuing a master’s degree programme in data science, data analytics or big data management. These programs will provide exposure to the latest trends and knowledge.
How can we help?
Robert Kennedy College offers 100% Online MSc Data Analytics in exclusive partnership with the University of Cumbria. With an in-depth curriculum, you will study data analytics, advanced databases and learn new trends in digital marketing and artificial intelligence. The University of Cumbria is ranked 8th in the world and is recognised by the British government. Trust me, with such credentials until its belt, you do not need much (big data) analytics for choosing the University of Cumbria as your online graduate school. Join us today!