Organizations across all industries are increasingly relying on data to make critical business decisions – what new products to develop, what new markets to enter, what new investments to make, and which new (or existing) customers to reach. They also use data to identify inefficiencies and other business issues that need to be addressed.
In these organizations, the data analyst’s job is to assign a numerical value to these critical business functions so that performance can be assessed and compared over time. However, the job involves more than just looking at the numbers: an analyst also needs to know how to use the data to make more informed decisions.
These functions are in great demand. IBM has estimated that there will be more than 2.7 million vacancies for experienced data professionals by 2020, with nearly 40% of advanced data analysis positions requiring a master’s degree or higher. Entry-level data analysts earn an average annual starting salary of around $ 60,000. However, success in this role can lead to managerial positions with wages over $ 135,000.
Read more: Why Data Science is essential in business?
What is Analytics?
The analysis combines theory and practice to identify and communicate data-driven information that enables managers, stakeholders, and other executives in an organization to make more informed decisions. Experienced data analysts see their work in a broader context within their organization and consider several external factors. Analysts can also view the competitive environment, internal and external business interests, and the lack of specific records in their data-driven recommendations to stakeholders.
A Master of Professional Studies in Analytics prepares students for a career as a data analyst, covering the concepts of probability theory, statistical modeling, data visualization, predictive analysis, and risk management. In the context of a business environment. Additionally, a master’s degree in accounting teaches students programming languages, database languages, and software essential to a data analyst’s day-to-day work.
Types of data analysis
Four types of data analysis complement each other to provide added value to a business.
- The descriptive analysis examines what has happened in the past: monthly sales, quarterly sales, website traffic, etc. These types of discoveries allow a business to identify trends.
- The diagnostic analysis takes into account why something happened, comparing descriptive records to identify dependencies and patterns. This helps an organization determine the cause of a positive or negative result.
- Predictive analytics attempts to determine likely outcomes by identifying trends from descriptive and diagnostic analyzes. This allows a business to take proactive steps, such as B. Reaching a customer who is unlikely to renew a contract.
- The prescriptive analysis attempts to determine what business action to take. While this type of research adds significant value to the ability to solve potential problems or stay ahead of industry trends, it typically requires complex algorithms and advanced technologies, such as machine learning.
In a 2016 survey of more than 2,000 directors, consulting firm PwC found that companies consider descriptive analysis insufficient for informed, data-driven decision-making. As a result, diagnostic and predictive analytics are becoming increasingly important to businesses.
Overview of the data analytics industry
There are many jobs in the data analytics field, the salaries are high, and career choices abound. Data analysis offers a multitude of possibilities in different industries and business levels. Therefore, salary and growth expectations can be challenging to identify. The Bureau of Labor Statistics provides several rankings for wages and growth.
The category of financial analysts is generally the most comprehensive classification for data analysts. This type of role can include business analysts, management analysts, and various types of investment analysts. BLS data shows a financial analyst’s average hourly salary at $ 48.55 for an average annual salary of $ 100,990. Hourly wages can range from $ 25 to $ 80. Financial analysts in New York make more money with an average hourly wage of $ 66. The BLS expects this category of workers to grow at an above-average rate of 11%. Until 2026.
A second classification of the Bureau of Labor, often explored by the data analyst’s salary expectations, is the category of the market research analyst. This category shows the average hourly wage at $ 34.11, with an annual wage expectation of $ 70,960. Hourly wages for market researchers can range from $ 16.50 to $ 58.21. BLS also expects strong growth in this category, with a growth rate of 23% through 2026.
Big data and machine learning
As the business world evolves, so does the use of data. The demand for big data technology, big data analytics, and machine learning highlights some of the critical areas of growth. These types of big data technologies are increasingly being incorporated into the data analysis programs of major universities in the United States and worldwide, of which there are many.
Most colleges in the United States offer data analysis or data science as an elementary or secondary school. In addition to the bachelor’s degree, there are also many master’s programs in data science. If you want to develop your skills in a more flexible or shorter period, several certification programs and courses are offered by various educational institutions.
Data Analyst Qualifications
Completing a data analysis program, especially if you have a high-grade average and a high grade in your class, should lead to a primary position in data analytics without significant issues. Even less math, statistics, or economics-focused degree from a respected university is enough to get your foot in the door. Although the job is primary, the salary is higher than that of experienced professionals in most fields.
As mentioned earlier, some of the top data analysis jobs in the first year can be as high as $ 100,000 per year. Experienced professionals can earn twice as much as an entry-level data analyst. The experience can come from working as a junior analyst or a related field, such as investment analysis. However, training is often an essential part of your resume when you apply for a data analyst job. Few people are hired without good academic performance in fields of study related to mathematics.
Job Description for Data Analysts
- Find out what questions are being asked and see if the data can answer those questions.
- Identify technical issues in data collection, analysis, and reporting.
- Identify new data sources and methods to improve data collection, research, and reporting.
- Distinguish between trends and models.
- Report data exhaustively and repeatedly.
- Analyze, collect, and report data to meet business needs.
Skills needed to become a data analyst
Like business analysts, data analysts often have strong technical skills that are complemented by in-depth industry knowledge. You have a complete understanding of the relationships between the various databases and data sources of the company. Information is obtained using complex query statements and advanced database tools and techniques.
Analytical skills: Data analysts work with large amounts of data, including facts, figures, and numerical analysis. You need to look at the data and analyze it to conclude.
Communication skills: Data analysts present their results and convert the data into understandable documents or reports. You must write and speak clearly and be able to communicate complex ideas in easy-to-understand terms.
Critical Thinking: Data analysts need to look at numbers, trends, and data to conclude.
Attention to detail: Data is accurate. Data analysts need to make sure they are careful with their analysis to come to the right conclusions.
Mathematical Skills: Data analysts need mathematical skills to process numeric data.
Read more: How to become Data Scientist?
Data analyst salary
According to Payscale.com, “the average salary for a data analyst is $ 57,261 per year.” Some factors affect salary, including education level, years of experience, certifications, and professional associations membership. In the first five to ten years in this position, the salary increases slightly, but any other occasion does not significantly impact the wage. Most people move to other professions, for example. B. Data engineers, data architects, or data scientists as soon as they have more than ten years of experience in this career.
Job prospects for data analysts
According to the Bureau of Labor Statistics (BLS), computer scientists and information researchers, including data analysts, are expected to increase by 11% from 2014 to 2024, which is above the average for all professions. IT people probably have excellent career prospects, as many companies struggle to find this highly skilled workforce. Many companies are still trying to fully maintain the talent shortage and expect more teams to join this year if they rush to keep up with the rest of the market.
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