Friday, December 03, 2021


What is Data Analysis?

PUNJAB NEWS EXPRESS | November 26, 2021 10:35 AM

It wouldn't be false to say that data drives the world. We live in an era where data lets us make critical decisions, avoid dangers, foresee the future, and whatnot. 

Earlier, organizations considered data as a mere by-product and dumped it without a second thought. Soon after, they realized the potential of such corporate datasets. These datasets can produce numerous game-changing insights that help a company understand its business and make necessary modifications for its overall betterment. 

Is raw data capable of revealing all things by itself? No. It takes organizing, cleaning, processing, and analyzing volumes of data to extract intriguing patterns and insights for a company. 

As companies become data-driven, they are opening numerous vacancies for data analysts and offering handsome wages. These reasons make data analysis a blooming career opportunity with an average payout of $96, 709 per year. 

Are you willing to pursue a career in data analysis? Getting a data analyst course in Delhi, Mumbai, or any other metropolitan city can benefit you. But, you need to master the fundamentals before stepping forward. So, let's start from the basics and master everything! 

What Do You Mean by Data Analysis?

What could be better than understanding the meaning of data analysis in the first place! Let's see what we mean by saying 'data analysis!' 

So, what on earth is data analysis? Essentially, it takes up datasets and cleans, formats, processes, and analyzes them using various tools to derive meaningful insights. Organizations can use the information gained to make effective decisions around multiple departments. 

Where can data analysis benefit a business? Probably, everywhere! From sales to customer management and supply chain, data analysis can uplift all areas and help the stakeholders achieve a flawless and profitable business. 

Some Real-Life Examples for Data Analysis

The above definition for data analysis comprises only theoretical aspects; however, you can perceive a better picture through some real-life instances. In other words, the meaning of data analysis is better understood with some practical examples. 

So, let's walk through some of the best data analysis examples.

  • Achieving Better Security in a City

The increasing rate of crimes is an alarming situation for the city administration and police. Maintaining law and order and sending troops for immediate arrest can be highly challenging. However, there is a ray of hope! 

Administrative authorities in top cities like Los Angeles use data analysis to identify the areas having a higher crime rate. Through better and more frequent patrolling, they check crimes and keep the city safe.

  • Preventing Cyber Attacks

Cyber-attacks have become a headache for companies. They face a continuous threat of financial and reputational loss through such attacks. Do they have an option to prevent cyber attacks? Yes! 

Leading organizations leverage data analysis to spot suspicious trends in their businesses. These abnormalities often lead to attacks. Through data analysis, they can prepare for such threats well ahead of time and stop them en-route.

  • Intelligent Expenses

Planning your expenses can be tricky, especially when the investments are enormous. However, various data analysis tools can help you understand unnecessary costs and save them for the future. 

Smart cities can use the same concept to chalk out their expense strategy. As frequent remodeling and unplanned costs can be expensive, the stakeholders use data analysis to identify unnecessary expenses and utilize them in essential purchases.

  • Enhanced Customer Experiences

Customers have varying expectations, and you cannot understand what they want without some external assistance. Here's a little secret! Companies rely on data analysis to understand customer needs and craft compelling strategies accordingly.

Hopefully, these realistic examples have inspired you to learn more about data analysis. So, without further ado, let's understand more about data analysis right below. 

What are the Benefits of Data Analysis?

By now, we have been discussing specific applications of data analysis. So, you might not be able to get a 360-degree view of data analysis advantages. Don't worry; we've got your back! Here are some of the groundbreaking benefits of data analysis right below. 

  • Risk and Fraud Management

Data analysis can keep risks and fraud away from a business. Yes, that's true! Companies can leverage data analysis to identify abnormalities in datasets well ahead of time. Such an advanced step provides the enterprises with sufficient time to prepare unbeatable strategies and effectively dodge threats and cyber attacks.

  • Implementing Customizations

Efficient customizations can change a business altogether. With better customer engagement and satisfaction, customizations can bring more profit for a product-based company. However, understanding customer demands can be challenging. Luckily, performing data analysis on customer feedback can surface their exact needs, producing even better customizations.

  • Highlight Invisible Patterns

Many times, some prominent trends remain hidden in datasets. These patterns can reveal numerous insights and provide avenues for better business management. Using data analysis, experts can highlight such schemes effortlessly.

  • Foreseeing Future

Can you look into the future? Yes, you can! Data analysis allows you to look into what is likely to happen in the future. Through present and historical data analysis, you can find the probability of future happenings and prepare accordingly. 

Besides, more benefits remain associated with data analysis. Companies and organizations heavily leverage data analysis to harness these advantages for their betterment. 

What are the Types of Data Analysis?

Stepping ahead, we come to understand the types of data analysis. Below are the different kinds of data analysis. Have a look! 

  • Descriptive Analysis: Such an analysis helps you understand what happened in the past.
  • Exploratory Analysis: This analysis assists in exploring various data relationships.
  • Diagnostic Analysis: Through diagnostic analysis, you can understand why an event occurred in the past.
  • Predictive Analysis: As the name suggests, it helps you predict what can happen in the future.
  • Prescriptive Analysis: Through prescriptive analysis, you can find a way for how an event will occur in the future. 

Data analysis is still under extensive research. Although we have explored many things about data analysis, more aspects remain hidden from us. So, a better future is waiting for the data analysts.

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