Data Analyst Job Description

What is a Data Analyst job?

Over the last decade, data has changed the face of our world. The numerous emails, text messages, and YouTube videos we consume are part of the trillions of bytes of data generated daily worldwide. Large and small businesses handle vast amounts of data and rely heavily on their ability to extract meaningful insights from it. That’s exactly what a person in a data analyst job does. They interpret statistical data and translate it into useful information that businesses and organizations can use to make important decisions. 

Organisations in all sectors are increasingly dependent on data to make important business decisions, such as using the data to identify business weaknesses that need to be addressed. 

Data analysis has become a profitable job. The world’s largest companies seek data analyst jobs. Data analyst jobs’ salaries and benefits only reflect the demand for their job, which can continue to grow exponentially. 

What does a Data Analyst do?

The data analyst job has various tangents and angles in the data collection and analysis. Depending on the type of profile a data analyst wants to build, there are different sections to explore.

The four types of data analyst jobs complement each other and add value to any organization. 

1.Technical Analysis – Examines what has happened in the past, and these types of results can help organizations identify trends. 

2. Diagnostic Analysis – Looks at why a problem is occurring by comparing a set of descriptive data to identify relationships and patterns. This helps the organization determine the causes of positive or negative outcomes. 

3. Predictive analytics – Seeks to identify possible outcomes by identifying trends in technical and diagnostic analytics. This allows organizations to take proactive measures, such as contacting customers who are unlikely to renew. 

4. Prescriptive analysis – Tries to determine the business activities to take. While this type of analysis offers significant value in its ability to solve potential problems or stay ahead of industry trends, it often requires the use of sophisticated algorithms and advanced techniques such as machine learning.

A person can choose what kind of data analyst job profile they want to pursue.

Data Analyst job duties include:

• Interpret the data and analyze the results using statistical techniques. 
• To optimize the efficiency and quality of statistics, development, and implementation of data acquisition systems, data analysis, and other strategies. 
• Collects data from primary or secondary data sources and maintains the database.

Job brief for a Data Analyst:

• The consultant role may include travel, but the role is usually office-based. The dress code and office culture will vary depending on the company one works for, with thousands of data analysts working for all types of employers.
• Work in complex systems that require a high degree of concentration and attention to detail. 
• Good communication skills are required to interpret customer requirements and present data clearly and compellingly.

Responsibilities of a Data Analyst:

• Using automated tools and software, data analysts should be able to extract data from various sources. 
• Delete corrupted data, fix coding errors and related issues. 
• Database, Data System Development, and Maintenance-Reorganize data into a readable format. 
• Performing analysis to assess the quality and importance of the data. 
• Review reports and performance counters to filter data to identify and fix code issues. 
• Use statistical tools to identify, analyze, and interpret patterns and trends in complex datasets that can be useful for diagnosis and prediction. 
• Assigning numbers to key business functions to assess performance and enable long-term comparisons. 
• Analysis of regional, national, and global trends affecting both companies and industries. 
• Use relevant data to generate administrative reports showing trends, patterns, and forecasts. 
• Work with programmers, engineers, and management leaders to identify process improvement opportunities, propose system changes, and develop data management strategies. 
• Create a final analysis report to help stakeholders understand the process of data analysis so that they can make important decisions based on various facts and trends.

Requirements for a Data Analyst job:

• Excellent math skills for collecting, measuring, organising, and analysing data. 
• Knowledge of programming languages ​​such as SQL, MATLAB, Python, Oracle, R. 
• Technical knowledge of developing database design, data models, data mining, and segmentation techniques. 
• Experience working with report packages such as business objects, programming, and databases. 
• Knowledge of statistics for use in dataset analysis and statistical packages. 
• Familiar with processing data processing platforms. 
• Knowledge of data visualization software. 
• Knowledge of creating the most accurate algorithm and applying it to a dataset to find a solution. 
• Problem-solving skills. 
• Attention to accuracy and detail. 
• Questions, report writing, presentation experience. 
• Ability to work in teams. 
• Oral and written communication skills. 
• Solid work experience in data analysis.

Average Salary for Data Analyst job:

The average salary for a Data Analyst in Malaysia varies based on city, industry, experience level, and company. 

Average Salary Overview

General Salary Range

• Entry-Level (0-2 years of experience): Approximately RM 36,000 - RM 48,000 per annum.
• Mid-Level (3-5 years of experience): Approximately RM 48,000 - RM 72,000 per annum.
• Senior-Level (5+ years of experience): Approximately RM 72,000 - RM 120,000 per annum.

Salary by City

Salary by Industry

Salary by Experience Level

1. Entry-Level (0-2 years): Average salary around RM 36,000 - RM 48,000.
2. Mid-Level (3-5 years): Average salary around RM 48,000 - RM 72,000.
3. Senior-Level (5+ years): Average salary around RM 72,000 - RM 120,000.

Salary by Top Companies

This overview indicates that data analysts in Malaysia can expect varying salaries based on their location and industry. Kuala Lumpur generally offers higher salaries due to its status as the economic hub of the country.

Data Analyst jobs Key Skills:

Effective data analyst jobs have a combination of technical and leadership skills. 

Technical skills require the data analyst to have sound knowledge of database languages, spreadsheet tools, and data visualisation software. Mathematics and statistics skills are also useful in measuring, collecting, organising, and analysing data. 

Leadership skills prepare data analysts to perform decision-making and problem-solving tasks. These skills allow analysts to strategically think about the information that helps stakeholders make data-driven business decisions and effectively convey the value of that information. For example, a project manager relies on a data analyst to track key metrics for a project, diagnose potential problems, and predict how different approaches will address the problem.

Why pursue a career as a Data Analyst?

Data analyst job seekers also want to learn about their social benefits and working hours. The perfect job description informs future DATA analysts about the availability of flexible working hours, home office options, or other telework options. It also emphasises unique office benefits and benefits such as conference sponsorship, continuing education credits, and paid leave.

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How to Become a Data Analyst?

Mastering this data analysis career requires more than just technical expertise. A bachelor’s degree in a field that focuses on statistics and analytical skills is desirable. Students in mathematics, statistics, computer science, or economics usually have an advantage in their career as data analysts. However, graduate courses in data analysis, such as Data Analytics Bootcamp, can help one become an industry-appropriate expert. 

One will also need the following soft data analyst skills: 

• Excellent communication and presentation skills. 
• Critical thinking ability. 
• Creativity. 
• Logical and systematic approach. 
• Team skills.

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