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Summary Advanced Data Management

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Summary of all the lectures of Advanced Data Management. It contains all the relevant material needed for the final exam.

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  • December 11, 2021
  • 29
  • 2021/2022
  • Summary

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By: AnnaStudent • 3 year ago

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By: uvtstudent5 • 3 year ago

Contains all the exam material

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Summary Advanced Data Management
Lecture 1

Data management
 Definition: Data are the facts (measurements or statistics) used as
a basis for reasoning, inference, or analysis.
o Reasoning, inference, or analysis -> Value Creation
 Definition: Data Management is the development, execution, and
supervision of plans, policies, programs and practices that deliver,
control, protect and enhance the value of data and information
throughout their lifecycles.




Understand the Domain (DM Perspective)
 Modelling the domain allows us to understand the role of technology and its data
requirements.
 What is a model?
o A model is a formal representation of the target domain, using constructs and
construction rules.
 We build models to describe a domain in unambiguous ways
o Analysis of existing domain
o Planning or designing a future state
 In order to reason about the phenomena in that domain and communicate between the
stakeholders.
o Also used in building a business case (communication)
 Using models we can explore, observe, analyze, explain and predict phenomena in the
domain and build (or plan/design) artifacts that operate in the domain.

Uses of Models in DM
 Understand the Business in order to Generate Value
 Data Governance
 Integration and Metadata Management
 Improving Data Security and Quality

A More Abstract View of Information Systems
 Information Systems are models or representations of real-world phenomena and applications
(Representation Theory).

, Information Systems are comprised of three structures:
o Deep Structure: meanings and facts about real world phenomena in form of data and
business rules.
 DM and business process management.
o Surface Structure: features such as user interfaces that allow users to engage with the
deep structure.
 DM and IT management / System Design.
o Physical Structure: the infrastructure (e.g., hardware and network) that enable the
implementation of surface and deep structures.
 DM and (physical) architecture.

Application of Models in DM




Business Case
 Before committing resources, businesses need to have a (somewhat) clear picture of what the
expected costs and benefits are
o Businesses need to understand the rationale for undertaking an initiative
 Conducting such analysis is challenging as a large part of Data Management fall under the
category of complex systems where an ultimate solution cannot be analyzed to solve a
problem.
 Conceptual models allow us to simplify and formalize the complexity

Business case – systems thinking
 To tackle the complexity, systems thinking conceptualizes the problem as:
o System made of interacting components;
o Interactions happen within an environment;
o The systems fulfil a goal.
 Two methods to analyze complex systems:
o Soft Systems Methodology including Rich Pictures where the interactions and roles
are modelled.
o System Dynamics where cause and effect relationships among various variables are
studied (using causal loops).

, Example of a rich picture and a casual loop




Another incentive for business case




 Successful: On time, on budget, with all features and functions.
 Challenged: Project completed, but either over time, over budget, or with fewer features than
originally specified.
 Failed Project: cancelled at some point during development

Reasons for Project Failures




Information Systems Research
 Information Systems research domain is the confluence of people, organizations, and
technology (Hevner et al. 2004).

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