Today data has become a strategic asset and essential for your business’s future. Together with evolution we witness a ever growing rate of change : changes in data sources, changes in requirements. Agile transformation is hard because cultural change is hard. It’s not one problem that needs to be solved, but a series of hundreds of decisions affecting lots of people over a long period of time that affects relationships, processes, and even the state of mind of those working within the change. The Agile Information Factory offers a best practice to coop with this changes, also when it comes to governance.
Are approach is based on Disciplined Agile (DA) – by author Scott Ambler – and is a process decision framework for delivering sophisticated agile solutions in the enterprise. It builds on the existing proven practices from agile methods such as Scrum, Extreme Programming (XP), Lean software development, Unified Process, Kanban, Agile Modeling and many others to include other aspects necessary for success in the enterprise.
Disciplined Agile (DA) DA fills in the gaps left by mainstream methods by providing guidance on how to effectively plan and kickstart complex projects as well as how to apply a full lifecycle approach, with lightweight milestones, effective metrics, and agile governance.
- Project scope
- Source system Data Analysis & Governance
- SDLC & Methodology Analysis
- Non Functional Requirements Analysis
- Team Structure
- Architecture Blueprint
- Data Modelling
- Source analyses
- Inflow & Outflow analysis
- Develop solution (raw datavault, Business Vault, Facts, Dimensions)
- Validate & refine architecture
- Write documentation
- Improve quality
- End to end testing
- Last minute fixes
- Deploy solution
- Finalize deliverable documentation
- Operate and support the solution in production
Besides an Agile Approach to govern our Data integration projects we specialize in the implementation of Data Governance tools and processes. Data governance is a is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency, data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization.