For a year or so I’ve seen so many data around my work and projects I’ve been involved. I noticed that when we try to analyze this data or when we query on that data, we get some fruitful information.
Let’s take a simple example of an eCommerce website, you might have noticed it shows relevant products, just near by product being viewed. Moreover, you may get occasional email about products either you viewed or purchased a while back. E-commerce site have your historical data and based on that data, it sends out offer/promotional email to you. Apart from marketing, we see frequent discounts on some products, which have not seen anytime or has not come to our way anytime. Such type of products either has stocks to clear or not get any tractions from users. Those products are identified and promoted as a heavy discount item. This is a very basic data analysis example, which helps to drive a business sale.
I believe everyone aware about it. Till now, we were generating data from user’s direct/indirect actions, but now we get plenty of data from devices too. This data helps to improve user experience and efficiency of the device. You would be surprised to know that the airline is generating peta bytes of data in a single way journey from Singapore to London.
Data analysis and processing was a time consuming and lengthy procedure. It was needing a large human power for a long time. In a last decade, we have improved computing power and also it’s very cheap. Advancement in artificial intelligence helps a lot in processing large datasets. Now, a person can process and analyze data in a day or week depends upon how large dataset is.
I see that data analysis can help in below fields significantly:
Analyze past historical data of genes and find out the genes of illness.
Analyze performance of machines and improve their efficiency.
We collect lots of weather data and we can identify some pattern of unfavorable weather.
Marketing and Sales
Depends on user’s choice, we only show relevant data to them. That’s already being implemented and have chances of improvement.
Business decision making
From the historical data, we can plot charts for business process and suggest ideas for improvement.
Past data of stock help to create a technical chart and predict price at some level.
There are numerous fields can take advantage of data analysis. The main goal of data analysis is to give certain useful information, so we can take further steps to avoid any damage or add efficiency to results.
I am planning to dig deep into any of the above fields and helps to build a system around data analysis vertical.
Now a day, you will see plenty of tools that offer data analysis, but each business and process is unique. We either need a customized solution or need to tune the tool according to our needs. In the field of data analysis, you will frequently hear about Hadoop that is a platform for data analysis.