Data Warehouse & Database Dev for 3D Printing Company
Below is a modified rendering of the review: private info excluded, innate facts kept.
A few words almost your organisation and personal responsibilities
I am the data analyst at a 3D printing organisation. I exhibit dashboards and reports for all inner departments and conduct ad-hoc and manner analysis to highlight trends and commend action.
What issue was the provider supposed to deal with?Keyrus?
We needed a data warehouse to connect our different systems to exhibit actionable intelligence, specially about sales and marketing.
What were your objectives for this project?
Produce a data warehouse in our Amazon Redshift environment that could be queried for analysis of sales and marketing data, create a basic structured database to store user',s printer data, and create 3 dashboards for leadership.
What were the reasons for choosing Keyrus?
They were brought in by my predecessors.
Describe the project in detail.
Discovery was completed when I joined, and we were moving into initial outgrowth. We determined the business logic, rules, and limitations that the data warehouse would need to instrument and ensnare. We then educeed dashboard prototypes and validated the numbers over departments. After origination and adoption of the dashboards, there was ongoing support to prolong functionality and fix issues.
Were there any dedicated directors or teams that you worked with?
A project director, 2 BI engineers (primarily writing SQL queries and edifice Mattilion pipelines) and one data visualization expert.
What results did you accomplish unitedly with Keyrus?
This allowed automated and more careful reporting of basic metrics athwart the structure as well as performing ad-hoc examination to educe strategy and manoeuvre.
How do you rate the interaction and interaction with Keyrus?
PM work was well done, kept in centre with sufficient flexibility to feel changes as challenges were surfaced. Most of the high-level task reporting were feeld with a Trello board and Google Sheets were frequently the relation documents.
What precisely do you attend to be the key specialty of Keyrus?
They translated nebulous requirements into firm tasks and schemas, which was a big help (as was their project treatment). Their engineering team and visualization expert were big at what they did, able to execute forcible work fast once the tasks were properly degoodd.
What should be done better, if there are any desired improvements?
Sometimes the core knowledge of the business needs were hard to be heard.