Blog Blog Posts Business Management Process Analysis

Introduction to Data Analytics

Today, practically every firm has evolved into a data-driven organization, which implies that they are implementing a strategy to acquire more data about their customers, markets, and business processes. This data is then classified, saved, and analyzed in order to make sense of it and gain useful insights.

Table of contents:

What is Data Analytics?

Most businesses are constantly collecting data, but this data is meaningless in its raw form. This is when data analytics enters the game. Data analytics is the process of analyzing raw data to derive meaningful, actionable insights that can subsequently be utilized to inform and drive smart business decisions.

What is Data Analytics

A data analyst will take raw data, arrange it, and then analyze it, changing it from unintelligible statistics into cohesive, understandable information. After interpreting the data, the data analyst will share their findings in the form of suggestions or recommendations for the company’s next steps.

Data analytics allows you to make sense of the past and predict future patterns and behaviors; rather than relying on guessing, you can make informed decisions based on what the data is showing you.

Armed with data insights, businesses and organizations can gain a much deeper understanding of their audience, industry, and firm as a whole—and, as a result, are much more positioned to make decisions and plan forward.

Check out our blog on Data Science tutorial to learn more about Data Science. 

Why is Data Analytics important?

Data analytics plays an important part in business improvement since it is utilized to collect hidden insights, develop reports, conduct market studies, and improve business requirements.

Data analysis is a type of internal arrangement in which numbers and figures are presented to management. With the help of data analytics, enterprises will be able to decide on customer trends and behavior forecasting, boost business revenues, and promote efficient decision-making.

Role of Data Analytics:

Certification in Bigdata Analytics

Data Analytics tools

With the growing market demand for Data Analytics, different tools with varying functionality have arisen. The top data analytics tools, whether open-source or user-friendly, are as follows.

Prepare yourself for the industry by going through these Data Analyst Interview Questions now!

How to become a Data Analyst

Academic Qualifications

It is recommended to have a strong CGPA and a graduation degree from a data analysis program. Even if a person does not specialize in data analysis, a degree in mathematics, statistics, or economics from a well-known university can lead to an entry-level Data Analyst position.

A bachelor’s degree is required for entry-level data analyst positions. Higher-level data analyst jobs normally pay more and may require a master’s degree. Aside from the degree, a person interested in becoming a Data Analyst may enroll in online courses.


Programming Languages: A Data Analyst should be familiar with at least one programming language. R, Python, C++, Java, MATLAB, PHP, and other programming languages are among those that can be used to edit data.

Data Management and Manipulation: A Data Analyst should be familiar with programming languages such as R, HIVE, SQL, and others. Developing queries to retrieve the relevant data is a critical component of Data Analytics.

A data analyst is in charge of giving management accurate and trustworthy information. Data analysts must therefore have a thorough understanding of the data as well as each user’s specific requirements. Good communication skills are also required when working with others to ensure that the data is effectively aligned with the objectives.

Mathematical Ability: A Data Analyst must understand statistics and be conversant with the formulae required for data analysis in order to deliver real-world value. As a Data Analyst, you must understand mathematics and be able to handle common business problems. You must also understand how to use tables, charts, graphs, and other tools.

Microsoft Excel: Data Analysts’ primary responsibilities include organizing data and gathering numbers. As a result, it is important for a Data Analyst to be familiar with Excel.

Career Scope in Data Analytics

A Data Analyst can expect to make a significant amount of money, do fascinating work, and have a lot of job stability. This is a career that is always changing and diverse and requires a lot of attention to detail and a focus on quality. A profession in Data Analytics also provides excellent prospects for progression.

Data Analyst is a position that is clearly on the rise. The difference between mid-level and senior-level positions is determined by experience and extra education. However, because Data Analysts are in such great demand at all levels, job growth is expected to be positive for each tier over the next decade, ranging from 5% for a Financial Analyst to 25% for an Operations Research Analyst.

The post Introduction to Data Analytics appeared first on Intellipaat Blog.

Blog: Intellipaat - Blog

Leave a Comment

Get the BPI Web Feed

Using the HTML code below, you can display this Business Process Incubator page content with the current filter and sorting inside your web site for FREE.

Copy/Paste this code in your website html code:

<iframe src="" frameborder="0" scrolling="auto" width="100%" height="700">

Customizing your BPI Web Feed

You can click on the Get the BPI Web Feed link on any of our page to create the best possible feed for your site. Here are a few tips to customize your BPI Web Feed.

Customizing the Content Filter
On any page, you can add filter criteria using the MORE FILTERS interface:

Customizing the Content Filter

Customizing the Content Sorting
Clicking on the sorting options will also change the way your BPI Web Feed will be ordered on your site:

Get the BPI Web Feed

Some integration examples