Data Architecture Vison

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Data Architecture Vison by Mind Map: Data Architecture Vison

1. Data-Centric

1.1. Technology Angnostic

1.2. Enterprise View on Data

1.3. Major Culture Shift

1.4. Data is "Forever"

1.5. Compliant By Nature

1.6. Integrated by Design

1.7. Data-Centric => Data-Driven

1.8. Share and Absorb

1.9. Low Code \ No Code

2. Application-Centric

2.1. Technology Dependent

2.2. Application View on Data

2.3. Business As Usual

2.4. Technology is Transient

2.5. Eventualy Compliant

2.6. Integration at a (high) Cost

2.7. Data-Drive ≠ Data-Centric

2.8. Duplicate and Integrate

3. A Core Model, not an Overweight Enterprise Model

4. "...Alas, customers usually presume their technology partners will also provide them with good data management, failing to understand that this is exactly what their partners are NOT providing because it's essentially not technology.." Martijn Evers

5. Data-Driven : Usage

6. Data-Centric : Control

7. Data models depict and enable an organization to understand its data assets.

8. "Data is a tremendously important corporate asset." Yawn. How many times have you heard a CXO say something to that effect? I'd bet quite often. Most of the time, those words fall on deaf ears. That is, an organization's actions betray its credo. Put differently, there's a world of difference between talking the talk and walking the walk. Not at Google. If anything, the company might be too good at the data game.

9. Het is onze missie om alle informatie ter wereld te organiseren en universeel toegankelijk en bruikbaar te maken.

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11. the starting point in defining a data strategy begins with understanding how the organisation use the data to satisfy a variety of use cases within your enterprise,

12. Data Integration Fintech's

13. Data Architeture

14. Metadata

15. You’re a tech company – regardless of your industry or sector. Regardless of sector, most companies need to reorganize themselves to take advantage of emerging “human-machine” opportunities. To be competitive in speed, product and business innovation, and to recruit and retain top talent, businesses will need to adopt a modular core data and tech architecture in the back-end combined with highly scalable processes and agile front-end teams. We know of financial services companies that are turning what once were massive sales and “relationship” business into apps. Leading industrial players are working to become “bionic companies” – creating units to develop software, tech platform businesses and ventures, while simultaneously deriving value from legacy assets. Face it: You’re a tech company.

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18. Metadeta

19. Metadata

20. Blackstone

21. Systems of Record Systems of Engagement Systems of Understanding