Analysts are business users who need a mostly self-directed data analytics experience. They want to bring in their own data, discover new insights and trends, and collaborate with others.
Analysts are inquisitive, technical people. They’re comfortable working with data and likely picked up the nickname “Excel Master” or “Big Data” at some point in their career. They’re measuring campaign effectiveness on a daily basis, and seeing what percentage of sales calls have been followed up on. They’re comparing revenue generated year over year to see what is working versus what isn’t. They’re focused on improving operational efficiency, and the metrics they’re interested in often change.
Specific examples of analysts include:
An accounts payable specialist who needs to generate revenue and collections reports for different teams to measure and collaborate upon for forecasting
A data engineer responsible for collecting and analyzing information across QC, shipping, and R&D departments to better optimize manufacturing processes
A finance analyst at the hospital who performs cost studies and allocations based on settlement claims and payment reconciliations so that they can provide recommendations for improvements in the future