Ladies and Gentlemen, it is getting difficult. There is so much data to be analyzed. From business to finance, education, population, health, and what have you. That is why we have a discipline known as BIG DATA.
Let me try to describe Big Data using a business website. Let's take the Jumia website, for instance, the owners of the site have a lot of goods and sales on their site they will have to analyze on regular basis. They will have to know the number of goods they have on the site and their categories. They also need to know how many were sold and how much gain was made.
But this actually is not the main problem. The problem starts to pose when other producers began to place their goods on Jumia site. This means that Jumia will have to analyze the data of the producers using their website as a marketplace and also analyse their products. As you can see, the data is growing but that is not the end.
Now, each customer who wants to purchase goods there will have to register on that site. That has not ended as the website also has an affiliate programme that they use to reward those who promote their sales. And the data continues to grow, that is what we call BIG DATA.
So the business analyst will have to analyse all these data differently and together. The image below may be of help to you. Remember I said, "future work will be so different and we should get our kids ready".
A course known as Data Analytics may be helpful to you. Wait for it!
Benefits of Data Analytics
Proactivity & Anticipating Needs:
Organisations are increasingly under competitive pressure to not only acquire customers but also understand their customers’ needs to be able to optimise customer experience and develop longstanding relationships.
Mitigating Risk & Fraud:
Security and fraud analytics aims to protect all physical, financial and intellectual assets from misuse by internal and external threats.
Delivering Relevant Products:
Products are the life-blood of any organisation and often the largest investment companies make. The product management team’s role is to recognise trends that drive strategic roadmap for innovation, new features, and services.
Personalisation & Service:
Companies are still struggling with structured data, and need to be extremely responsive to cope with the volatility created by customers engaging via digital technologies today.
Optimizing & Improving the Customer Experience
Poor management of operations can and will lead to a myriad of costly issues, including a significant risk of damaging the customer experience, and ultimately brand loyalty.
Limitations of Data Analytics
Lack of alignment within teams
There is a lack of alignment between different teams or departments within an organization. Data analytics may be done by a select set of team members and the analysis done may be shared with a limited set of executives.
Lack of commitment and patience
Analytics solutions are not difficult to implement, however, they are costly, and the ROI is not immediate. Especially, if existing data is not available, it may take time to put processes and procedures in place to start collecting the data.
Privacy concerns
Sometimes, data collection might breach the privacy of the customers as their information such as purchases, online transactions, and subscriptions are available to companies whose services they are using. Some companies might exchange those datasets with other companies for mutual benefit.
Complexity & Bias
Some of the analytics tools developed by companies are more like a black box model. What is inside the black box is not clear or the logic the system uses to learn from data and create a model is not readily evident.
If companies are not careful and a poor quality data set is used to train the model, there may be hidden biases in the decisions made by these systems which may not be readily evident and organizations may be breaking the law by discriminating against race, gender, sex, age etc.
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digital