The design and implementation of a data lake

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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)

aligning processes

As you can see, you're not asking your respondents for opinions, satisfaction or agreement. Our scientific research has shown that these are very bad fuel for algorithms. Instead, we ask for verifiable facts or -behaviour. For further reading, you can download our AMAIZE magazine dedicated to this topic or discover the scientific papers in the Resources section.

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?
  1. No
  2. We have an outline of what is important to us
  3. 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)?
  1. No or not in our case
  2. This is weighed against other objectives when making a decision
  3. 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
The artificial intelligence creating the questionnaires for the store has been inspired by over 11.000 whitepapers from more than 100 noted consultancy firms. Algorithms selected the 20% best papers and grouped papers from different consultancy firms into specific questionnaires. Why settle for less? Here is a summary how we did 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.
mckinseyMcKinsey Reform Center_2016 Exchange Networks_FINAL.pdf
bakertillyc9d1a01d-ec87-4767-9d88-47b499dcff6c_Leadership Matters Superintendents' Response to COVID19.pdf
You will download so much more than a set of questions and answers. This questionnaire contains everything for the full consultancy experience:
  • 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.
This English questionnaire is also available in Dutch, French, German, and Spanish.


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