When it comes to understanding data in the workplace, there are 4 key job functions involved in the conversation, those of Database Administrator, Data Analyst, Data Scientist and Data Architect. Of these the Data Analyst role tends to lead in demand as it stands as the bridge connecting data and business operations. But what exactly is a Data Analyst? This post will dive into what the job role entails and how someone can break into this field.
What Does A Data Analyst Do?
Today data and the need to harness it for greater efficiency dominate the workplace conversation. While many organizations can derive basic insights from standard database manipulations, most companies want to take the next step in the process to connect those insights to specific operations. Their ultimate goal is to achieve greater efficiency in their business processes and build up their team’s skills in the areas that will be most beneficial to their bottom line. This scenario can apply to organizations across every industry.
While the type of data and insight employers expect a data analyst to review depends largely on the organization’s industry, most roles require the employee to pull, organize and analyze data and then use those outputs to identify trends and business opportunities.
Common Tools Data Analysts Use
Based on the 15,000+ job postings for Data Analysts on LinkedIn at the time of this post, data analysts may need experience in specific databases and/or visualization software including:
- Microsoft Excel
- SAS
- Stata
- SPSS
- Power BI
- Salesforce
- Medallia
- Elevate
- SQL
- Tableau
- Access
- JIRA
- Confluence
- SharePoint
- R
- Python
- Hadoop
It is important to note, that not every job requires someone to operate each of these tools and some only require comfort in Microsoft Excel. It all really depends on the experience level of the job.
How To Become A Data Analyst?
Unfortunately, there are no well-defined entry-level roles within the data space and most hiring focuses on mid-level career positions (between 6-10 years of experience). However, with the right foundational knowledge, most people can enhance their marketability in their current position and then transition into a full Data Analyst role.
Every department within every organization holds an abundance of data that, if managed correctly, can lead to greater business intelligence. This is why job roles such as Marketing Analyst, Clinical Analyst, Customer Experience Analyst and Sales Data Analyst have emerged in recent years. People who enter the workforce through the traditional 4-year degree pipeline can seek entry-level work in their field and then upskill their data analytics capabilities through certification and apply for these job roles.
Similarly, more technical roles in software development can also evolve into data analytics careers. Critical thinking is just one of many software development skills that translates well to the data space and both careers leverage some of the same programming languages, such as Python and Javascript.
Best Certifications For Emerging Data Analysts
The best certification for an emerging Data Analyst to start with is the CompTIA Data+. This is an early-career and vendor-neutral certification that will validate the foundational data analysis capabilities employers seek in not only data-specific careers, but other career paths that benefit from analytics processes and data analytics knowledge. Specifically, CompTIA Data+ validates skills in:
- Mining data
- Manipulating data
- Visualizing and reporting data
- Applying basic statistical methods
- Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
After earning the Data+ certification, the next step is to tackle industry-specific certifications such as:
- SAS® Certified Specialist: Visual Business Analytics
- Tableau Certified Data Analyst
- Microsoft Certified: Data Analyst Associate
Ready To Get Started?
Request a meeting with our team to discuss how you can transition into a Data Analyst career with Data+.