统计代写|数据分析：从数据中学习代写Data Analytics: Learning from Data代考|SEC595

统计代写|数据分析：从数据中学习代写Data Analytics: Learning from Data代考|User Management

There are four user groups defined for this framework (Figure 2.8):

1. Super Admin: Head of our research unit or center (e.g., CBD-HS Director). Have all of the admin privileges $+$ can add/remove admin accounts. This is usually a legal entity.
2. Admin: Have all of the project managers privileges $+$ can create project_manger_group and add user to these groups + can add/ remove new groups (e.g., Cerner, UK biobank). Main responsibility is Run/Update/Maintenance of DMF and associated files and user management.
3. Project managers: Can create project-specific folders and files. The main responsibility (other than general project manager duties) is keeping the file’s name and structure consistent and report the changes to admin if necessary.
Each project has a separate project manager user group. For example, Cerner_SAH_Project_Manager is the user group for the SAH project in the Cerner group. The members of this group are managing files and folders in the CBD_HS/Cerner/SAH folder.
4. Regular users: Are responsible for different aspects of projects.
5. The access management to each folder has been discussed in the previous section (Section 2.6.1).

统计代写|数据分析：从数据中学习代写Data Analytics: Learning from Data代考|Data Management Framework

Now we have a reliable and secure server with a detailed convention for naming and organizing our files and folders, but still, a very important issue remains – the reproducibility. It is crucial to be able to reproduce the data files, reports, and results from the EHR research projects. It is not uncommon that other parts of your organization or other outside organizations want to see how you produced the specific results. Having messy data makes this task challenging or even impossible. The steps we described in the previous section lay the cornerstone in creating a data management framework. First, we should note that EHR data analysis is a multistep project and each step is usually dependent on the data from previous steps (see Figure $2.1$ and Chapter 1). This means that each data file or report is dependent on some other data or report. We can use Directed Acyclic Graphs to visualize these dependencies and create a semiautomatic framework to reproduce the data and analysis results. To describe this framework, we begin with an example project (Figure 2.9).
To keep things simple, we describe an imaginary sub-project (Mortality Prediction) from the SAH Project, that belongs to the Cerner EHR working group. The actual network is bigger and more complicated, but the framework functions will be the same for all of them. As you can see, we can arrange the data hierarchy in layers. Each shape in this figure is considered a node. The research Center (CBD_HS), Groups (Cerner), Projects (SAH), and Sub-projects (Mortality Prediction) layers are not data nodes, but they are helping us to keep track of the changes and organize the downstream nodes (the nodes lower than a specific node). The Extracted Data (e.g., extracted lab table), Cleaned Data (cleaned lab table), Prepared Data (prepared lab table), Reports (reports 1 and 2), and Papers (paper 1) are considered as real data nodes in DMF. Each directional edge (arrow) shows the dependency relationship between the current node and upstream nodes (nodes at the same level or higher level). Using the proposed file and folder convention, a computer code can be written to scan all of the files and folders inside the main folder (CBD_HS) and create this network. There are multiple visualization modules to visualize your network as a 2-dimensional (with concentric circles as layers) or a 3-dimensional (with concentric spheres as layers) graphs. As you can see this graph can be considered as a Directed Acyclic Graph. At the next step, we will describe the properties of nodes and edges in DMF (Figure 2.10).

统计代写|数据分析：从数据中学习代写Data Analytics: Learning from Data代考|User Management

1. 超级管理员：我们研究单位或中心的负责人（例如，CBD-HS 主任）。拥有所有管理员权限+可以添加/删除管理员帐户。这通常是一个法律实体。
2. 管理员：拥有所有项目经理权限+可以创建 project_manger_group 并将用户添加到这些组 + 可以添加/删除新组（例如，Cerner，UK biobank）。主要职责是 DMF 和相关文件的运行/更新/维护以及用户管理。
3. 项目经理：可以创建项目特定的文件夹和文件。主要职责（一般项目经理职责除外）是保持文件的名称和结构一致，并在必要时向管理员报告更改。
每个项目都有一个单独的项目经理用户组。例如，Cerner_SAH_Project_Manager 是 Cerner 组中 SAH 项目的用户组。该组的成员正在管理 CBD_HS/Cerner/SAH 文件夹中的文件和文件夹。
4. 普通用户：负责项目的不同方面。
5. 每个文件夹的访问管理已在上一节（第 2.6.1 节）中讨论过。

统计代写|数据分析：从数据中学习代写Data Analytics: Learning from Data代考|Data Management Framework

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