We know how important it is for customers to get the help they need, when they need it. To support customers around the world, we aim to build a network of data magicians that are second to none.

We know we have a lot of work ahead to build out the internal content and training we need to support these customers and we are looking for early adopter and data savy people, who want to work with us to ensure we create the right things in a magical way.

We are not great fans of making things complex, but we also know that having a shared language makes many things easier.  So here is what we believe a Data Magician does:

Data Magicians work with organisations to help them improve their processes and systems, using data, to increase organisational value.

Strong problem solving and communication skills are must-have traits.  A reasonable level of data literacy is also required.

Things they do typically include:

• • Eliciting core business questions (How many Customers did we have last month and where were they based?)
  • Eliciting the actions people will take if these questions are answered
  • Identifying an organisations core business concepts (Customer, Product etc)
  • Identifying an organisations core business events (Customer Orders Product etc)
  • Identifying where data can be collected from to answer the core business questions
  • Configuring data rules to change the data to make answering the core business questions easier and repeatable
  • Creating Information Product outputs so people can get answers to the questions in the way they prefer
  • Providing suggestions on changes to an organisations processes and systems to increase organisational value.

Now you might think this sounds very close to the description of what a business analyst or data analyst does.  And you would be right, we just help them do it in a new magical way where they are not required to create masses of documents or write screeds of code.

If you prefer a more traditional job description, this is the one we would pick:

• • Identifying data sources
  • Collecting data
  • Sourcing missing data
  • Organising data in to usable formats
  • Analysing data to find answers to specific questions
  • Developing, implementing and maintaining databases
  • Assessing quality of data and removing or cleaning data
  • Generating information and insights from data sets and identifying trends and patterns
  • Preparing reports for executive and project teams
  • Creating visualisations of data