A computer system analyst and a data analyst: Decoding the difference
What are analysts?
Depending on the situation, ‘analyst’ has many meanings. However, in each case, the analyst specializes in analysis. The analyst combines theory and practice to identify and convey data-driven insights that enable managers, stakeholders, and other executives within an organization to make more informed decisions. Analysts can also explain the lack of specific datasets in the competitive environment, internal and external business interests, and stakeholder database recommendations.
What do computer systems analysts do?
The work of different types of computer analysts includes computer system analysts, forensic computer analysts, and computer specialists. There may be other particular positions and descriptions within these computer jobs. Computer analysts may work as employees of a large company’s information technology (IT) department or work as self-employed. Some computer analysts work for software or hardware vendors by providing services to businesses using specific computer tools, equipment, and products.
Computer system analysts use computer technology to help businesses and other organizations run effectively and efficiently. After performing a cost-benefit analysis, they incorporate new technology into their current system to determine if it is financially sound and valuable enough for the enterprise. Computer system analysts investigate the hardware and software part of an organization’s computer system and how the system is used.
It would be best to analyze your organization’s work to determine how your computer system can provide the best service. Through this research, computer system analysts develop new systems and update or improve existing systems. This includes analyzing the time required to train staff on using the latest hardware and software and the costs and benefits of purchasing it.
Types of computer systems analysts:
There are three types of computer system analysts.
- The system designer or architect finds a technical solution that meets the long-term goals of the company or organization. They are decoding long-term business goals into technical solutions by specializing in selecting specific types of hardware and software systems and creating plans. They work with management to ensure that their systems and technology infrastructure are set up to best fulfill their mission.
- Software Quality Assurance (QA) analysts test and diagnose computer system problems. They perform in-depth testing and problem diagnosis to ensure that critical system requirements are met. We also keep in touch with management by creating reports that recommend improving the system.
- Programmer analysts develop and write software code that meets the needs of their employer or client. Programmer analysts do the most debugging and coding as compared to other types of analysts. They create applications customized to the company’s needs and design and update the software on the system. They determine the specific requirements that the applicant intends to address and work closely with management and business analysts for this purpose.
What skills does a computer systems analyst needs?
Computer system analysts need to have specific soft skills to perform their tasks effectively, in addition to the technical knowledge required for their work.
- Problem Solving and Critical Thinking: These abilities are needed to identify problems, evaluate alternative solutions, and determine which is best for you.
- Reading: Computer system analysts need to keep up with progress, read manuals and technical reports, and implement new technologies to meet the needs of employers and clients.
- Writing: Expect to produce a written report of recommendations.
- Communication: Good listening skills allow analysts to understand the needs of their clients and colleagues. To communicate information effectively, strong verbal communication skills are needed.
- Creativity: Computer system analysts must be able to generate new ideas continually.
- Analytical skills: You need to analyze large amounts of data quickly and efficiently.
What do data analysts do?
Data analysis is the cleaning up, transforming, and modeling of data to find information that can help you make business decisions. The job of data analysis is to extract useful information from the data and make decisions based on the data analysis. Data analysts are needed in situations like when your business isn’t growing, and you have to look back and acknowledge your mistakes and plan again without repeating those mistakes. Data Analysts analyze your business data and processes, and even if your business is growing, you must look forward to growing your business further.
Data analysts gather and perform statistical analyses of large datasets. They use the data to answer questions and find ways to solve the problem. Data analysis has evolved as the movement towards computer development, and technological intertwining has increased. With the development of relational databases, data analysts are breathing new life, allowing analysts to retrieve data from databases using SQL (pronounced “sequel” or “s-q-l”). Experienced data analysts are considering working in a larger context within the organization, taking a variety of external factors into account.
Data analysis is the process of cleaning up, transforming, and modeling data to find information that can help you make business decisions.
Data analysis consists of collecting data requirements, collecting data, cleaning data, analyzing data, interpreting data, and visualizing data.
Types of data analysts
There are four types of data analysts which bring value to their individual organizations:
- Descriptive analytics looks at what has happened in the past: monthly revenue, quarterly sales, annual website traffic, and more. These types of findings allow organizations to find trends. They analyze a sample of complete or summarized numerical data for analysis. Shows the mean and deviation of continuous data and delivers the percentage and frequency of categorical data.
- Diagnostic analytics considers why something happened by comparing descriptive datasets to identify dependencies and patterns. This helps organizations identify the cause of positive or negative consequences. Diagnostic analysis shows why things happened the way they did by finding the grounds from the insights found in the statistical analysis. This analysis helps identify behavioral patterns in the data. If you encounter a new problem with your business process, you can examine this analysis to find similar ways of that problem. And it may have the opportunity to use a similar prescription for new issues.
- Predictive analytics determines possible outcomes by detecting descriptive and diagnostic analysis trends. This allows organizations to take proactive action by contacting customers who are unlikely to renew their contracts. Predictive analytics uses previous data to show “what’s likely.” The simplest example of data analysis is buying two dresses based on your savings last year, and if your salary doubles this year, you can buy four dresses. But of course, it’s not as easy as this because you have to think about other situations such as the price of clothes is likely to go up this year, you want to buy a new bike instead of a dress, or you have to buy a house, etc. Therefore, this analysis makes predictions about future results based on current or historical data. Forecasts are just estimates. Its accuracy is based on the amount of detailed information you have and dig into it.
- Prescription analytics seeks to identify the business action to perform. This type of analysis brings excellent value to the ability to address potential problems and stay ahead of industry trends. Still, it often uses advanced technologies such as complex algorithms and machine learning where it is needed. The prescription analysis combines insights from all previous analyzes to determine the action to take on the current problem or decision. Most data-driven companies rely on prescription analysis because predictive and descriptive analytics is not enough to improve the performance of their data. Based on the current situation and problems, they analyze the data and make decisions.
What skills does a data analyst needs?
Effective data analysts have a combination of technical and leadership skills. Technical skills include knowledge of database languages such as SQL, R, and Python. Spreadsheet tools such as Microsoft Excel and Google Sheets. Data analysts also need data visualization software like Tableau and Qlik. Mathematical and statistical skills are also valuable for collecting, measuring, organizing, and analyzing data.
Leadership skills prepare data analysts to complete decision-making and problem-solving tasks. These capabilities enable analysts to think about the information that helps stakeholders make data-driven business decisions and effectively convey the value of this information strategically. For example, project managers can use data analysts to track the most crucial project indicators, diagnose potential problems, and predict how to address issues with different behavioral policies.