The design and implementation of a data lake
WHAT IS IT ABOUT?
Customer experience and data management have become the cornerstones of retail banking. This questionnaire aims at identifying data inefficiencies and providing design suggestions for a data lake as well as improving business processes, agile development, and regulatory compliancy.
- The C-DOT for the Banking organization that needs to create a new digital banking platform for its customers.
- The project manager of a data lake and data cloud project that needs to understand the client's strategic objectives and constraints.
- The CTO of a retail bank who needs to differentiate her bank from the rest.
- The consultant that wants to underline the advantages of being an innovator in a mature market.
- The enterprise architect that needs to assess the opportunities for governance and technology solutions.
how to get it right
what is the data?
how do you make a banking ecosystem work?
how to plan for success
what are the requirements of your program?
who will be involved in this program and when will they start? (time)
After you have downloaded this questionnaire, you can - in your Toolbox - edit, add/delete, and translate questions & answers to your liking. Clicking the "Help me PRAIORITIZE" buttons in the Toolbox activates our A.I. to help you finish your masterpiece..
Q. Are fraud risks taken into account when making business decisions?
- We have an outline of what is important to us
- We evaluate risks and actively take this into account when making business decisions
Q. Is the risk of fraud weighed against other objectives (e.g. growth, cost reduction)?
- No or not in our case
- This is weighed against other objectives when making a decision
- The risk of fraud is weighed against other objectives when making a decision AND/OR for cases of fraud a plan is made to compensate for it
If you feel you need outside support after conducting your assessment, we recommend the firms that have written the below mentioned whitepapers. Not having a paper selected does NOT mean that a firm does not give good advice.
|mckinsey||McKinsey Reform Center_2016 Exchange Networks_FINAL.pdf|
|bakertilly||c9d1a01d-ec87-4767-9d88-47b499dcff6c_Leadership Matters Superintendents' Response to COVID19.pdf|
- Respondent profiles for a helicopter view of your audience.
- A maturity model with which algorithms calculate a six times smarter improvement target (compared to when you leave that to a human).
- Improvement suggestions (per question) how to move from one answer to another
- Suggested follow-on projects. After all, moving your organization from A to B might require more than just doing an assessment.