Business intelligence (BI) is a booming field. BI is the concept of taking all the data a company collects, organizing it and analyzing it and delivering it to help the company make data-driven decisions. BI is all about getting the right data to the right users to help them determine what’s going well, what isn’t, to identify patterns and draw important conclusions. BI developers are critical for this process, so if you’re looking to break into the field, these are the skills you should focus on.
BI developers have to be able to communicate with both highly-technical members of their team as well as non-tech execs and staff members. Don’t forget, listening and understanding what someone needs is just as critical as explaining concepts to them. Without strong listening skills, developers won’t know exactly what data to work with or how to deliver it to the end user effectively.
Structured Query Language (SQL)
Today, data-oriented jobs require SQL skills. SQL is the backbone of business intelligence and no developer can escape SQL queries. It is so important that most jobs will put candidates through and SQL test to verify that they do, in fact, know what they are doing and haven’t fudged their resume because they know hiring managers want to see SQL listed.
Companies rely on one or more specific BI platforms and they want to hire people who have experience in those areas. From Oracle to Microsoft to Tableau and more, it is important to stay up-to-date on features for these platforms – or if you are only interested in working with one or two, it is often worthwhile to pursue certification.
Data modeling defines and maintains the structure of data and is what allows the data to actually be used. Data modeling is a skill that requires practice, so if you’re new to the field, you’ll probably want to find a class or two in order to get some hands-on, supervised experience.
Presenting data is a bit about design, but it’s really about pinpointing the most appropriate way to present data to end users and decision makers so that they can see complex data sets in a way that helps them quickly assess it and identify patterns.
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