The world is literally spinning on data. Massive volumes of data are generated every second that industries are relying on to run their operations profitably. Through data analytics, businesses can spot hidden trends, patterns, and customer behavior with the help of SAS Data Analyst which then informs decision-making in terms of how to approach their markets, customize unique offerings, and run their operations to stay ahead of the competition. With the rapid adoption of data analytics across industries, there exist vast opportunities for professionals with Data Analyst certification, skills, and competencies.
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Data Analysis with SAS
Among the top data analysis and visualization tools that are widely adopted by businesses, SAS is the third most popular among data scientists. SAS is built with an array of statistical algorithms and techniques as well as a syntax that is easy to use. SAS mostly uses Python and R languages which happen to be data scientists’ most preferred programming languages. In addition, SAS supports a range of data formats and features an effective data management system.
SAS is designed to retrieve, manage, and mine data from various sources to run statistical analysis operations on it. It also features a point-and-click graphical user interface for visualization. SAS top applications include, among others, business intelligence, predictive analytics, and advanced analytics purposes. It is compatible with both Windows and Linux operating systems.
Who is a SAS Data Analyst?
In general, data analysts are individuals who are responsible for collecting, processing, analyzing, interpreting data, and presenting its findings to stakeholders in a way that can be understood easily. This information is important for organizations to make more informed business decisions, solve business problems, and leverage opportunities. Data analysts typically apply a range of skills, including programming, mathematics, and statistics skills to perform data analysis.
SAS data analysts have the same responsibility as general data analysts, only that they use the SAS software to perform data analysis.
Duties and Responsibilities of a SAS Data Analyst
Overall, SAS data analysts are responsible for managing databases and ensuring their security, updating SAS programs, performing data analysis on large datasets, and drawing reports to present to business owners and stakeholders. While the specific roles of a SAS data analyst will differ from one organization to another, some of their common roles include:
- Building and maintaining data process flows and system maps, data profiling, as well as defining data quality rules using the SAS software.
- Data collection, cleaning, processing, and storage in databases
- Carry out data profiling which involves examining data from its sources to summarize its metadata information and assessing its accuracy.
- Ensuring data integrity as they are in charge of monitoring, process controls, and updating SAS software.
- Statistical analysis of data and presentation through reports, summaries, spreadsheets, or charts to facilitate data-driven decision-making in business.
- Performing regular system checks and troubleshooting to identify and resolve issues within the SAS system to improve software performance.
- Identify, prioritize, recommend, and document systems requirements for the automation of the manual processes.
Important SAS Data Analyst Skills
Ideally, a SAS data analyst, like all others, should be well versed in mathematics and statistics, as well as SAS programming. In addition, he/she should possess the following valuable skills:
- SAS programming language as well as R and Python. These are important through data collection, cleaning, statistical analysis, to data visualization processes.
- Data warehousing skills are essential, especially for SAS data analysts who work at the back end. They should be able to manage databases like SQL, create a data warehouse by connecting databases from various sources, and apply query language to manage data.
- Database query language skills are important because among the core roles of SAS data analysts is database management. Knowing how to use SQL-associated languages like PostgreSQL, PL/SQL, and T-SQL come in handy.
- Proficiency in working with SAS software. A SAS data analyst should be able to apply various statistical analysis procedures and methods that are available in the SAS suite. In addition, analysts should have a working knowledge of Linux and Microsoft operating systems as well as Microsoft Excel. Microsoft Excel skills like advanced data modeling and analytics will give professionals some familiarity with statistical analysis techniques.
- Data visualization. Creating graphical data representation using bar charts, pie charts, histograms, box plots, and scatter plots, all of which are available in the SAS suite.
- Critical thinking is important for spotting and interpreting patterns, trends, and useful insights from datasets to facilitate data-driven decision-making.
- Communication skills. In addition to visualizing and presenting findings from data analysis, a SAS data analyst requires good communication skills to convey these findings.
Qualifications
Although it is not an essential requirement, SAS data analysts will typically have a bachelor’s degree in computer science, information technology, software engineering, applied mathematics, or a qualification in any other related discipline. Also important is SAS training in Statistical analysis and qualification in one’s specific domain.
Conclusion
Apart from the fact that SAS is easy to learn, it enjoys stability and is thus a reliable software that has attracted the attention of large corporate companies. For this reason, there is a rising demand for SAS data analyst skills. These professionals also command a decent package, with the annual median salary of a SAS data analyst estimated at $63,393.
