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A data analyst is a person who is responsible for collecting, processing, and performing statistical analyses of data. He translates statistics and data into simple English language to be understood by different companies or organizations so they can make better work decisions.
WHAT DO DATA ANALYSTS DO?
Every business association collects data to let it be the research about the market, logistics, sales information, or transportation costs. A data analyst will take all of that data and process it to perform tasks that revolve around the financial decisions of the company. He helps companies to make better work decisions, mainly related to cost. He also helps the organizations how to reduce the budget, how many employees do they required and how they can entitle a new price to the product.
According to a very famous writer Ms. McKenzie, successful data analysts possess all of these skills, which are:
When theory and practice are brought together for identifying and communicating data-driven perceptions, it is called Analytics. It allows data analysts to inform executives, stakeholders, and managers in the organization, so they take more structured decisions. Data analysts with a certain amount of experience always consider external factors for the safe side and take a broader picture of their work within their organization. They are also accountable for making recommendations to the stakeholders in situations like; competitive environment, external and internal business interests, and the shortage of any data in the database.
Data analyst is considered to be an expert in professional studies in analytics. He has knowledge about the concepts of statistical modeling, probability theory, data visualization, risk management and predictive analytics of any business environment. He is well equipped with other talents, such as comprehensive information about the programming languages, coding, software programs and database languages that are significantly used in everyday work.
TYPES OF DATA ANALYTICS
Following are the four types of data analytics that built are on one another to bring collective worth to an organization:
It is used to inspect the past, such as monthly, quarterly and yearly information regarding sales, revenue, and website traffic, and much more. This type of analytics helps in spotting trends.
Using diagnostic analytics, the data analysts identify dependencies and patterns by comparing descriptive data sets. These analytics compute the causes of good and bad outcomes in an organization.
Predictive analytics is used to determine the probable consequences after the determination of different tendencies in descriptive and diagnostic analyses. It allows the organization to make practical decisions.
While identifying the type of business resolutions, prescriptive analytics comes into use. This analytics allows staying ahead of industry trends, addressing the potential problems before they happen, and takes the help of machine learning or any other type of advanced technology and sophisticated algorithms.
A survey was conducted by Consultancy PwC on more than 2000 business executives in 2016, where they established that descriptive analytics is considered to be insufficient for informed, data-driven decision making by many organizations. While diagnostic and predictive analytics can be used for critical decision making sometimes.
TOOLS USED BY DATA ANALYSTS
Data analysts use a combination of different tools to give adequate sense to their data. These tools are used to gather information and data from news sites, social sites, and even magazines. The collected data is then categorized, sorted out, and then visualized for making reports and presentations. Some standard tools used by data analysts are:
DATA ANALYST ‘S PLACE OF WORK
Data analysis is a highly valuable skill, and it can open new doors for a data analyst to get fantastic jobs both in the private and public sectors. Nowadays, almost every industry presumable is looking for a skilled data analyst such as in the fields of sales, finance, marketing, and healthcare, and even in the cyber world.
Data analysts always need his computer to work, and they mostly work in teams. They can even work from home, remote office or even in some kind of practical office. They place of their work mostly depends on the type of data being gathered. Data analysts usually work as 9-5 employees; however, the duration of their work can be changed depending on the project deadlines and emergency. We have made a shortlist of typical organizations, companies, and employers who need data analysts:
Along with the personal skills, a data analyst must have these technical job skills as it will help him to get the best job possible. Following are some of those technical job skills required:
SALARY OF DATA ANALYST
The salary of a data analyst depends upon his experience in the field and the type of data analyst he is. In the United States, the average annual salary for a professional data analyst was found to be $67,377. Other related fields, such as analytics data scientists, made an average salary of $72k and $117k, respectively. While an entry-level data analyst made $63k and data analyst intern made a total of $68k.
EDUCATIONAL REQUIREMENTS FOR DATA ANALYST
As we know that, a bachelor's degree is necessary for any entry-level job as a data analyst, while a master's degree will be extremely beneficial for upper-level jobs. Most of the data analysts will have a bachelor’s degree in fields like economics, mathematics, statistics or computer science, or any other field that is closely related to data analysis. Excellent analysis and math skills are very much appreciated.
PERSONAL SKILLS AND REQUIREMENTS
For the role of a data analyst, the person must have some built-in personal skills to flourish in this field, such as:
The job of data analyst may seem simple as it requires only collecting and analyzing the data to meet the customer's needs, identifying new sources of data, and finding methods to improve the analysis, but the competition is very tough as many people are trying to become a data analyst. Therefore, if you are going to pursue this field, we suggest you read thoroughly all the information we have provided. We also think that you should join a data science boot camp to gain more information and skills before stepping into the field.