One of the most empowering aspects of the agile mindset is that fact that agile teams are generally self-organized verses the traditional command and control protocols of traditional project management. While there are several benefits to self-organizing teams, it can lead to failure if the team misses some key planning aspects during team formation. Agile chartering is key to executing successful agile initiatives. In general, agile charters consist of the project charter and a team charter. The project charter defines the project vision and objectives, while the team charter establishes how the team will work together and how they can incorporate agile values as the team collaborates. A team charter is especially critical when organizations are new to the process of incorporating agile frameworks into the organization as it will facilitate knowledge transfer and identify key learning opportunities. With that said, here are some key reasons agile teams need team charters.

Business knowledge is simply knowing your business—its facets, strengths, weaknesses, competition, challenges, positioning within the market, and readily available solutions to its daily problems. Strong business knowledge should inform everything you do.  So, what you learn and hear in discovery should be filtered through your business knowledge. What you define in your requirements should also be informed by your business knowledge. As one business analysis writer puts it, “I’ve always been of the opinion that I’d like to know as much as I can about whatever I can because you never know when something you learned may come in handy.”^[2] The following four areas are the ones, specifically, according to BABOK, that you’ll want to apply yourself to.

The quality of any data analysis created to inform business decisions will ultimately be constrained by the quality of the underlying data. If the data is faulty, then the analysis will be faulty too. This is why data wrangling–the transformation of raw data into a format that is appropriate for use–has become such a ubiquitous task in most organizations. Unfortunately, the significance of data wrangling is still often overlooked. And this is where data-savvy business analysts can help save the day.

Thanks to infrastructure as a service (IaaS) and software as a service (SaaS) architectures, the utility of and business case for model-driven, no-code and low-code platforms have become more compelling than ever. More and more enterprises are entrusting their digital transformation, regulatory compliance, and business process management objectives to model-driven, no-code or low-code business application platforms.  These model driven platforms also raise the bar for the business process modeling skills of the business analysts, systems analysts and process owners who use them.

Many BAs struggle to produce ‘normalized’, function-independent data models (or don’t produce them at all). Very few business stakeholders can appreciate such models as “… a picture worth a thousand words.” This article describes an easy-to-create, simple-to-understand view data model. The view is of just those records involved in an information system capability supporting a specific business activity.

NOTE: This article uses the business-friendly terms record and field rather than the usual data modeling terms entity (or class) and attribute.