Saturday, March 2, 2024
HomeData scienceWhat is big data analytics

What is big data analytics

What is Big Data Analytics?

What is big data analytics? The basic answer to this question is that it is a complex process to examine “Big Data” to uncover hidden information like different market trends, hidden patterns, correlations, customer preferences, etc. Let’s dive deep into the roots of big data analytics!

Importance of Big Data Analytics:

Big data analytics is a process used to extract or unveil important and meaningful insights. The information can be in the form of unknown correlations, market trends, hidden patterns, customer relations, and much more. Big data analytics use advanced analytics on a large scale on both structured and unstructured data so that it can produce valuable insights for different corporations and businesses.

Who uses Big Data Analytics?

There is a big group of industries that use and rely on big data analytics. Moreover, it is also quite frequently used in medical lines, insurance companies, educational institutes, and many more. They all use big data analytics to understand better what is working and what is not and to improve their profitability, processes, and systems for a bright future.

It provides many advantages like stopping a client from taking a wrong decision or perhaps helping them in decision making. It can prevent fraudulent activities, even assists in taking an appropriate steps and a lot more.

Benefits of Big Data Analytics:

There are a few perks of incorporating big data analytics into organizations and businesses. Some of these are as follows:

1. Cost Cutting:

Big data can help you reduce costs in storing all your business’s data in one safe place. Keeping track of the analytics can also help companies find ways to work more efficiently and effectively to cut costs wherever and whenever possible.

2. Customer experience:

All data-driven algorithms help marketing efforts like targeted advertisements, media control, television adverts, etc. In addition, it increases customer satisfaction by delivering an enhanced and better customer experience.

3. Risk management:

Organizations and businesses can identify the risks and the levels of risks as well by analyzing the data patterns and working on developing the best solutions for managing those levels of risk.

4. Entertainment:

How do you always get the list of shows on what you are interested in or what you prefer to watch on your favorite streaming applications? The reason behind this is big data analytics. It creates and provides personalized music and movie recommendations according to individual customers’ preferences. This has completely transformed the entertainment industry.

  1. Product development:

How will a firm know that there is a need for a new product? They will know that by looking into data collected from customers’ needs and wants. In addition, developing and marketing new services, products, or brands is much easier when based on the existing given data of customers. Big data analytics also can help businesses understand product feasibility and viability and help them in keeping up with the trends.

6. Strategic business decisions:

Big data analytics help firms and companies in many forms. One of which is helping the firms in taking strategic business decisions on time. Data analytics give firms the ability to constantly analyze data, which helps businesses make faster and better decisions, such as cost and supply chain optimization and much more.

7. Banking Sector:

Data analytics can be a great help for financial task forces to track and monitor illegal money laundering cases and or any illegal money involving matters like turning black money into legal money and much more. Big data analytics can really help in that as well.

  1. Medical Line:

Data analytics can also be very helpful in the medical line as well. It helps with the monitoring of the patient’s medical history which can help the doctors detect diseases and prevent them.

9. Government Institutes:

Big data analytics can also be used for data collection from traffic and CCTV cameras, body cameras, satellites and sensors, calls, emails, and many more to help the government manage the public sector smoothly and easily.

Types of Data Analytics:

There is a misconception as big data analytics is of only one type. But, the answer to that is no. There are actually four main types of it, which are as stated below:

  1. Diagnostics analytics:

Diagnostics analytics can really help companies to understand the reason why the problem occurred. The tools and technologies of big data allow users to recover and mine data that helps dissect an issue and prevent it from happening in the coming future.

Example: The sales of a retail store have decreased even though customers continued to add more items to their shopping carts. Diagnostics analytics helped in finding the solution, they came to the conclusion that the payment page was not working properly and effectively for a few weeks.

2. Descriptive analytics:

Descriptive analytics refers to a set of data that can be read and interpreted easily. This data can help visualize information and create reports that can detail company sales and profits.

Example: During COVID19, a pharmaceutical company conducted data analysis on its research labs and offices. Descriptive analytics really helped them identify unutilized departments and spaces that were consolidated, saving them millions of dollars.

3. Predictive analytics:

Predictive analytics looks at the present and past data to make predictions of the future outcomes. With the use of machine learning, artificial intelligence (AI), and data mining, users can easily analyze the data to predict the upcoming market trends.

Example: In the manufacturing sector, companies use algorithms based on historical outcomes and data to predict or verify if a piece of equipment will break down or malfunction.

4. Prescriptive analytics:

Prescriptive analytics gives out a solution to a problem, but it completely relies on AI and machine learning to gather the data and use it for future risk management.

Example: Within the energy sector, gas producers, utility companies, and pipeline owners find and identify the factors that may affect the price of gas and oil in order to hedge risks.

Conclusion:

Hence, big data analytics is important not only for firms and businesses but also in almost every field. It gives the companies and firms insights and valuable information, and by using this information, they can attempt to improve the future of their firms and companies.

RELATED ARTICLES

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Most Popular

Recent Comments