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DATA STEWARD - Coggle Diagram

- - - - 3 240
  - - - 15.12.2025
      - motivační dopis
        
        jakou pozici zastáváte a jaká je vase motivace k absolvování kurzu;
        
        jak dlouho se danou problematikou zabyváte;
        
        jaká jsou vase ocekávání od kurzu;
        
        jaké je vase relevantní vzdelání a kurzy, které jste absolvoval/a;
        
        jaké jsou vase jazykové znalosti;
        
        jaká je podpora vaseho zamestnavatele, ideálne prilozte doporucení;
        
        strucné profesní CV.
      - doklad o vzdělání
  - - - full course
- - - - link to openscience.cuni.cz
        
        open access week
      - link to openscience.cuni.cz
        
        FAQ
      - link to openscience.cuni.cz
  - - - • Access and authorization: Providing users with the data required for their roles and informing them of its use and privacy.
      - • Security and privacy: Securing data, informing stakeholders of its use, complying with data privacy regulations, and protecting data from malicious actors.
      - • Quality assurance: Ensuring that the data your organization uses meets quality standards through metrics, error detection, and data profiling strategies.
      - • Master data management: Creating a single source of "truth" from an organization's data to reduce redundancy and promote efficient workflows through data processing technologies like automatic integration, cleansing, and redundancy reduction.
      - • Streamlining data storage, collection, and security
      - • Implementing policies defined by data governance
      - • Ensuring data quality throughout its life cycle
      - • Managing data access
      - Data stewardship refers to the responsibility for implementing and adhering to the procedures and guidelines established by data governance. A data steward is responsible for implementing these practices, maintaining quality assurance, managing metadata, and categorizing sensitive data. Data stewards collaborate with various data professionals, including data architects, business intelligence specialists, and data owners. Their role involves:
      - It's important to note that data stewardship functions align with the policies and procedures established by the organization's data governance committee.
    - - The core principles of data governance help to standardize the definition of data across an entire business. They help ensure that the data used for different goals is trustworthy, consistent, and employed correctly. Data governance frameworks include the following principles:
      - Data quality involves examining collected data to ensure it is complete, relevant, and accurate. Timeliness and uniqueness are also considered. This helps keep data accessible across multiple platforms and ensures that the professionals interacting with it use the best possible data to derive insights or actionable strategies.
      - Data security involves creating a secure network with tools such as firewalls, encryption, and tokenization to protect sensitive information from cyberattacks. Access control mechanisms help to prevent unauthorized users from accessing confidential data or exposing it incorrectly.
      - Data usability helps to support the right access for different teams so that they can each work with the right type of data efficiently and safely. This principle involves creating a consistent view of data that increases reliable and accurate implementation.
      - Assigning data responsibility makes it easier for businesses to stay within regulatory compliance since each person helps to monitor and protect data. This way, there won’t be any gaps in coverage, and each person knows exactly what their role is in managing the data sets.
      - Data compliance is a necessary facet of any data governance framework. It can help you maintain compliance, bolster customer trust, and avoid the risk of hefty fines. Data compliance ensures that your data collection, management, and storage processes exist within regulatory guidelines, keeping everything safe and secure.