Maybe we have heard this job title floating around recently and desired to be a data analyst. The idea of working with data and technology everyday has piqued our curiosity and we often ask ourselves that does it sound like an intriguing career?
In general, we have seen the vast multitudes of ads in the Internet about Data Analyst job that we will take responsibility for managing, developing and troubleshooting data issues. As more and more companies are looking to expand their businesses, or at least improve their business practices, data analysis is an essential and profitable field. Whether it is exactly like what we have heard and seen. Let's start to find out!
What is a Data Analyst?
In particular, a data analyst is the person who collects, processes and performs statistical analyses based on available numbers and data. You will translate numbers and data into plain English in order to help organizations and companies make better business decisions based on the analysis results.
Every business collects data whether it be market research, sales figures, logistics, or transportation costs. Then, a data analyst will take that data, dig into it and figure out a variety of things, including problems and how to deal with them.
What does a Data Analyst do?
One of a data analysts’ duties is to ascertain how data can be used in order to answer questions and solve related problems. They figure out what’s happening right now to identify trends and make predictions about the future. So, they are like detectives with the mission to discover how things work and make sense of it. In other words, this career is somehow creative, challenging and rewarding.
To figure out their numbers, data analysts typically work with computer systems and calculation applications. Data must always be regulated, normalized, and calibrated so that it can be extracted and used independently, or put in with other numbers and still keep its integrity. Qualitative and quantitative data are the starting point, but the most important step is about understanding what they mean and presenting the findings in an interesting way, using graphs, charts, tables, and graphics as not everyone can understand the IT language.
The responsibility of a data analysts is not only deciphering data, but also reporting and explaining what differences in numbers mean when looked at from year to year or across various departments. Because data analysts are often the ones with the best sense of why the numbers are just the way they are. Project managers and department heads always ask for an advice from data analysts about concerning certain data points and how they can be changed or improved over a period of time, so optimized decisions are ready to be made.
The Detailed Responsibilites of Data Analyst
Data Analysts may have these following responsibilities:
Providing data reports for management
Working with technology and management team including data scientists to set goals
Fixing code problems and data-related issues
Cleaning and dissecting data to get rid of irrelevant information
Pinpointing trends and patterns in data sets
Analyzing and decoding results using statistical tools and techniques
Mining data from primary and secondary sources
Identifying new opportunities for process improvement
Creating, designing and maintaining databases and data systems
A data analyst's skills may not be as advanced as a data scientist's skills, but their goals seem to be very similar. Data analysts are sometimes called as “junior data scientists” and may be limited to handling specific business tasks using existing tools, systems and data sets.
What is the difference between Data Analyst vs. Data Scientist?
As mentioned above, you might be wondering about another prominent data role - the data scientist. We can possibly assume that there is some overlap in the type of work they do, there are significant differences between data analysts and data scientists.
As data scientist’s role is relatively new and sometimes vague, let’s break it down based on skills and job duties.
Master moderate math and statistical skills
Have a strong business acumen
Have moderate computer science / coding skills
Develop key performance indicators
Create visualizations of the data
Utilize business intelligence and analytics tools
Grasp strong math and statistical skills
Have a strong business acumen
Strongly master computer science/ coding skills
Identify trends with machine learning
Make predictions based on data trends
Write code to assist in data analysis
Though data analysts and data scientists have different backgrounds and strengths, keep in mind that these roles can be a little equivocal in how they’re defined. This means responsibilities may change depending on the organization.
The Working life of a Data Analyst
How to suitable for being a Data Analyst?
Data Analysts have distinct characters. Infact, they tend to be predominantly investigative individuals, which means they’re quite inquisitive and curious people that often like to spend time alone with their thoughts. They are methodical, rational, analytical, and logical. Some of them are also conventional, meaning they are usually detail-oriented and organized, and like working in a structured environment.
How is the workplace of a Data Analyst?
Data Analysis is a highly exchangeable skill and can open the door to many interesting jobs including both private and public sector. Almost every industry in the market has a need for data analysis, especially the fields of sales, marketing, and healthcare, these industries tend to have the most jobs available for professional data analysts at any given time.
Almost data analysts work on teams, and a lot of the work is done on the computer. Much of the work can be done from home or from a remote office, though this usually depends on the type of data being collected. Data analysts can typically expect to work 9-5 hours a day, however unexpected projects or looming deadlines can require some overtime and weekend work.
How many types of Data Analytics available?
At its nature, data analytics is about answering questions and making optimal decisions based on the actual data collected. And just as there are different types of questions, there are also different types of data analytics depending on what you’re expecting to achieve. Data analysts can customize their work and solution to fit the scenario. While there’s no set-in-stone dictionary of these types of data analytics, the folks at ScienceSoft has done an excellent job breaking this work down into 4 primary parts:
Descriptive analysts answer: “What happened?”
Diagnostic analysts answer: “Why did something happen?”
Predictive analysts answer: “What is likely to happen?”
Prescriptive analysts answer: “What action should be taken?”
How to become a Data Analyst
A university education is essential for this sort of work. For example, a bachelor's degree is needed for entry-level jobs. Most data analysts will have degrees in fields like finance, statistics, economics, mathematics or computer science with several essential skills:
Strong math and analysis skills, including mining, evaluation, analysis, and visualization.
Technical writing experience in relevant areas.
Strong SQL or Excel skills with the ability to learn other analytic tools.
Preceding experience with database, model design and segmentation techniques.
Strong encoding experience with frameworks including XML, Java Script, and ETL.
Practical experience in statistical analysis through the use of statistical packages including Excel, SPSS, and SAS.
Proven success in a collaborative, team-oriented environment.
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