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Design Meta, governing data


Contents & topics Data governance

Metadata

Mindmap opsec ALC type2 Business Apllications - 3GL Security Access Metadata, what is in it? Just having data, there are a lot of questions to answer:
📚 Information data is describing?
⚙ Relationships data elements?
🎭 Who is using data for what proces?
⚖ Inventory information being used ?


🔰 Most logical back reference.

Contents

Reference Topic Squad
Intro ICT at an organization by layers. 01.01
descrpt_data Describing data. 02.01
model_data Describing descriptions of data. 03.01
access_usrkey Who has access. 04.01
descrpt_documnt Describing Information - documents. 05.01
What next Data governance 06.00
Following steps 06.02

Combined links
Combined pages as single topic.
👓 deep dive , Data Proces layers
👓 describe data ,Data Administration
🚧 Data Modelling
👓 Security Access


Progress


Operational processes - data models.

The modelling of data and than building your own on premise solution was hot in the 80´s. These days is hardly seen to build on premise solutions.
🤔 Modelling data for an operational solution is knowledge becoming rare. It is not needed anymore for several reasons. One of those are commercial ERP solutions.
⚠ In the cases when an on premise approach is the only option, as a pitty not getting that attention as necessary requirement. Agile: fail fast.

Example SAP
This core concept of auditing has remain unchanged since BO XI 3.1, though the number of tables have increased significantly in BI 4.x audit database. The increase in number of tables is primarily due to increase in the attributes being captured and more normalization of the data structures. audit data model (SAP blog BI 4.x )
sap_bi4_1_audit_613785.jpg
Example Salesforce
Field Service Lightning Core Data Model (Field Service Lightning Developer Guide).
If your team often performs the same tasks for multiple customers, create work types to standardize your field service work. Work types are templates that can be applied to work orders and work order line items. On a work type, you can define the duration of the work and add skill requirements to indicate the level of expertise needed to complete the work. You can also opt to auto-create a child service appointment on any record that uses the work type. Work orders and service appointments are supported by a variety of objects that control when and where the work occurs, the nature of the work, and who performs it.

salesforce_218.png

BIAnl ALC type2 - data modelling.

The classic business Intelligence reproting still heavily relies on data modelling with the goal of report building.
🤔 The difference in approach is remarkable. Operational requirements sometimes get solve by using the datawarehouse is also remarkable. Something must be wrong.

Example Kimball group.
Enterprise Data Warehouse Bus Architecture (Kimball group).
The associated Enterprise Data Warehouse Bus Matrix, shown below, is a key design tool representing the organization´s core business processes and associated dimensionality. It´s the architectural blueprint providing the top-down strategic perspective to ensure data in the DW/BI environment can be integrated across the enterprise, while agile bottom-up delivery occurs by focusing on a single business process at a time.
Data-Warehouse-Bus-Matrix1.png
Example Nova architecture van der Lans.
Migrating to Virtual Data Marts using Data Virtualization Simplifying Business Intelligence Systems (r20 pdf - sponsored by Cisco)
Unfortunately, data marts are expensive because they require a lot of work to develop, operate, and maintain.  They also complicate the architectures of BI systems. For example, changes made to the data  warehouse can lead to a multitude of changes throughout all the data marts, and changes made to a report can involve complex modifications to the data marts and the corresponding ETL programs. In addition, they can degrade data quality and complicate data governance.
..
Star Schema – The tables in a data mart developed with SQL technology are usually organized as a star schema1. In a star schema the tables are classified as dimension tables (or dimensional tables) and fact tables. Fact tables are the central tables in a star schema. A row in a fact table usually represents a business event. Lans_datavirtualise.jpg

 lost long way

Object Oriënted Life Cycle model (I).


An object - a container with al lot of artifacts.
Object containers are describing the whole of all. A sample model of legal property registration.
imkad20.jpg
imkad21.jpg
As being too complicated only a part is realy uased.

imkad22.jpg
Interested in only a small part, the relationship of property and owner searching what the owner as object or artifact is.

imkad23.jpg
Finding an ER relationship with several type of property objects and several type of owner objects. Easilty missing some types if you do not check all on completeness.

 lost long way

Object Oriënted Life Cycle model (II).


Converting an object container to relational records.
Getting data in containers goes into a challengin conversion.
  1. Receiving (a) and prepraring (b) for further processing.
  2. Bring it into an target technical environment (TE)
  3. Extract within that TE to a logical sementical structure
  4. Convert sementical to users - programmers lay-out.
What users -programmers have as theier data, can be a source to the next data message container api interface decoupling.
oolc_00.jpg

Life cycle of an object in a chain.
Every object can change in SOME content by time. With a pre-post key identification unique to the mutation block object of ALL content, there is a validation chain.
oolc_10.jpg
Every object can change in time on another moment. There will be a lot of chains. Having te identifictions of object an d time any viewpoint is possible.
A new object is a mutation without a pre situation.
A removed - invalidated object is a mutation without a post situation.
oolc_11.jpg
 horse sense

Step by step, Travelling the unexplored.


OOLC object oriënted life cycle - artifact mindset
🤔 designing business processes and the corresponding information represented as data goes by containers of information.
⚠ The historical apporach with SQL normalisation 3nf is based on optimization because of technical limitations on artifacts.
⬇ - ⬆ Time for change... ⬅ - ➡

OOLC object oriënted life cycle - ACID
🤔 Processing containers of information (example XML) requires several conversions.
Those conversions do not follow normal aasumptions of an internal data flow using a DBMS system. It isn't the using DBMS transactional automatic controls. The input data can´t be trusted and must get validated on (ACID): availablity-atomicity, consistency, integrity -isolation, durabiltiy.

OOLC object oriënted life cycle - chain mindset - variable moments
The life cycle of objects are chains for any of those object. When the moments of mutations for each object is undetermined, there is a chaotic system of state.
Selecting an dtermining the moment of state on each object is a required step to do. Following the changes in time is anohter viewpoint that is possible.
This kind of different thinking in designing the way of analyzing information could be a game changer.

No it is not the blockchain ledger. No distributed approach of duplicated chains neiter an prove of unchanged blocks. It is basic following information flow and change in time.

OOLC object oriënted life cycle - chain mindset - fixed moments
When the moments of change - mutations are mandatory moments a lot gets simplified. That situation is by example caused by legal delivery on reporting periods.
Predictable moments of new inforamtion make the pre mutation situation and then undefined varbiel time moment of change obsolete as being a standard series. Using that standard series definition is the most understandable way of approching that. Little for identicational keys on mutations needed.



Unexplored joureney Enterprise
Transforming processes.
Change is a the only constant factor of a journey. Never knowing for sure what is next. Changing fast is exploring where no one has gone before.
The people around ICT are a different kind of species than the ones running the business. Understanding the business during fast transitions is another world.

Combined pages as single topic.
Combined links
👓 deep dive , Data Proces layers
👓 describe data ,Data Administration
Data Modelling
👓 Security Access


🔰 Most logical back reference.



⚒    Intro     descrpt_data     model_data     access_usrkey     descrpt_documnt     What next     ⚒ 👐    top bottom   👐
📚    BPM    SDLC    BIAanl    Data    Meta    Math    📚 👐 🎭 index - references    elucidation    metier 🎭

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