Companies and business have to collect a large quantity of data to see how their products or services are doing in the market and how they can improve and create more impact on the market. They would also collect data on gaps in the market so they can create products. The process of analyzing, sorting through and going through all the data and forming a conclusion on how to progress their business is called Data Analytics.
Benefits of Data Analytics
Companies are often under constant pressure due to the changing needs of people and competition from other businesses, it’s the best way for a company to figure out what is missing from the market and what might be required to boost their business. This is why a lot of companies are constantly asking for feedback and ratings and also take details like email and phone numbers; it’s all to help boost their business.
There are teams such as the project management team which have the sole responsibility of finding out gaps in the market, finding out what is currently preferred and delivering the relevant information to the company so the company knows where to put in their efforts and create a business plan for the future. Data analytics is a key part of creating business plans and seeing trends and how certain companies might perform in the future.
It can also help businesses improve their customer experience. Companies lookout for feedback through user and customer data to help them improve their services. Companies with bad customer experience can ruin their brand image and loyalty from customers. Customers often use star ratings and feedbacks and use the data provided by those to see what they can add or improve in their customer experience.
The Downside of Data Analytics
The biggest concern of Data analytics is the invasion of privacy of the customers. Companies need customer information and data such as purchase history, what the customers might be looking for, their searches, etc. This is a major breach of privacy as companies are buying private information for their own gain.
Another downside of Data Analytics is it is time-consuming and expensive. Data analytics requires going through large quantities of Data to find relevant information and form conclusions using the data provided. This can be highly time-consuming as companies might have lots of data to go through. Sometimes, the tools used such as the applications might be difficult to use and would take time and money to teach their employees on how to use the software and use it correctly.
Data Analytics Course is more than just collecting and going through data, it requires planning on how to collect the data and how to form conclusions using the correct tools and collecting and filtering the information to the right places and determining which data is relevant and which is not. Data scientists will go through and analyze the information and data engineers would help create data sets.
Referring Links-Logistic Regression using R