Research Paper: Data Governance Planning Document

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¶ … Governance Planning Document

Scenario

Major roles of our organization are to collect massive amount of data through automated systems on customer utility, supplier, and customer account information. While some of the data are used in aggregate form, some data are cross-referenced to GIS (geographical information system) data. These data are the organizational strategic critical infrastructure assets that need effective protection to enhance data integrity.

Objective of this report is to develop a data governance-planning document. The planning document provides the information pertaining to customer, operations, supply chain partners and production facilities.

Data governance refers to overall usability, integrity, availability, and security of the data within an organization. A sound data governance program refers to policies and strategies to make data consistent, secure, accurate, and available to accomplish an organizational objective. (Thomas, 2010). Effective data governance allows an organization to save money, reuse data to make analytical decision. Typically, the data governance assists an organization to effectively manage data assets. However, the policy document is very critical to enhance the greater understanding on the layout of our data governance document

Template for Data Governance Policy Document

A data governance policy is a living document that sets a guideline to ensure a proper management of the organizational digital information. Such guideline involves policies for BPM (business process management), data security, privacy and data quality. ( Duvall, 2011). The data governance policy is carried out to ensure accurate, consistent, protection and accessibility of data. (Illinois State Board of Education, 2011). A data governance policy needs to be updated regularly to meet the changing needs of an organization. Table 1 provides the template for our data governance policy document.

Table 1: Template for Data Governance Policy Document

Introduction

This data governance policy establishes the framework for guideline standard to be followed in data storage and access mechanisms. Our organization will exercise control over and access to data to enhance integrity and security of our data. To support all aspect of our operations, all data within our organization will be managed as a strategic asset according to governance procedures.

Regulations, Statutes, and Policies

In accordance with Public and Records Law and Data Protection Act, all personnel must abide to the rules and regulations with reference to the company data assets. It is the responsibility of all personnel to protect the company data from theft, misuse and alteration. All personnel must follow policies and legal statues in relation to company data assets.

Policy Scope

Data stored in the organizational information system are the property of our organization, and access to the data should be in line with the ethical and legal policies.

Data Security Policy

The organizational data must be protected from deliberate, unauthorized or unintentional destruction, alteration, or/and inappropriate use or disclosure or use. All data stored in electronic format must be protected using appropriate electronic safeguards or/and in physical access controls to restrict data access only to authorized agents.

Data Control

Data taken from the corporate assets must be appropriately protected to ensure data integrity and availability. All data retrieved through electronic format must not be altered in any form to enhance continuous integrity. All data taken from the corporate data assets must be encrypted before being transferred offsite to safeguard data security.

Data Governance Corporate Working Group "dream team."

A best practice to successfully implement data governance is to collaborate between business leadership and it management to design a refine future state of data governance commitment. Major benefits of selecting efficient and effective working group are to ensure that solution-minded leaders are used to resolve Data Governance issues. The group will also be able to address the critical issues related to Privacy, Security, and Compliance issues.

Our data governance corporate working group will consist of Executive Sponsor, Data Quality Leader (DQL), Data Governance Board, Executive Steering Committee, and Enterprise Data Architect. (Berson, & Dubov 2007). The Table 2 presents our data governance-working group.

Data Governance Corporate Working Group

Role

Responsibilities

Skill Set

Time Commitment

Executive Sponsor

The Executive Sponsor sets initial goal and direction for the program.

The Executive sponsor also approves track of progress and information policy, and compared quality initiatives to the target plan.

Respected and recognized leadership,

LOB expertise

Proven ability to manage multiple functions such as governance policies, governing, enforcing and arbitrating.

< 5%

Data Quality Leader (DQL)

The DQL provides day-to-day leadership over the DQM (Data Quality Management) program.

Ensures execution of policies and strategies with the Steering Committee and Data Governance Board,

Prioritizes and review projects to determine the funding needs,

Provide scorecard feedback to all parties involved.

The DQL should have a significant data management expertise,

Ability to deeply involved in all aspects of the program as well as participating in the Executive Steering Committee and Data Governance Board.

Full Time

Enterprise Data Architect

Deliver a single point of architectural coordination for all data related approved initiatives,

Focusing on planning of infrastructural efficiencies, usage of data, linkage, and implementation of data.

Ensure compliance and execution of data governance;

Maintenance, reconciliation and re-creation of data design and maintenance.

Technically strong in it,

Skill in solid data analysis,

Mining and migration experience

Good Technical writing skills,

Presentation skills

Full Time

IT Resources and Business Leads

Liaison between the business leaders and it to achieve a data quality,

Data management and process and data element.

Play various data management support, which include metadata lead, data quality lead, data architect and enterprise architect.

Having leadership and communication skills.

Having data governance skills as well having ability to work and make decisions within a team.

Technically strong in it and understand basic data modeling and conceptual physical data.

Skill in solid data analysis,

Mining and migration experience,

Good Technical writing skills,

Presentation skills

Full Time

Data Governance Board

Data Governance Board monitors and develops an overall strategic plan for our wide data quality improvement.

Approve sponsors, prioritize and champion data quality initiatives.

Ensures resources and scheduling allocation and provide data quality progress feedback,

Communicates with business segments to ensure data quality expectations and initiatives.

Having leadership skills on effective Data Governance lead,

Having an industry practices content knowledge, and a strong data governance.

Excellent communication skills and expert knowledge of collaboration tools such as WebEx SharePoint, and wikis.

Quarterly

Adhoc meetings

Executive Steering Committee

Responsible for developing Data policies and Quality strategy;

Leadership/supervision roles for the overall program.

Delivering a periodic data quality update to the senior management,

Estimating high level funding needs, requests budget from the executive sponsor,

Approves data quality initiatives.

Having a respected and recognized leadership ability,

LOB expertise,

Proven ability to manage multiple functions such as enforcing governance policies, governing, and arbitrating.

Monthly

3. Data Flow Diagram

The fig 1 reveals our data flow diagram that demonstrates how our organization store, transfers, collects, delete and updates data in our database.

Fig 1: Data Flow Diagram

4. Matrix of Data Sources, Classification, Categories, and Formats.

The Table 2 presents the matrix of our data sources, classification, categories and format.

Table 2: Matrix of Data Sources, Classification, Categories, and Formats.

Secure Infrastructure

Identity and Access Management

Information Protection

Auditing and Monitoring

Manual Controls

Collect / Update

Data are collected directly from the customer, and suppliers who provides personal data.

Incoming data is tagged and classified by the application server to allow customer to update their account

User creates account and password. Users also have access to as being by our governance policy.

Data Transaction log data is encrypted. Communications between the customer and the CSP are encrypted using SSL.

Data privacy and classification policies are updated.

Communications channel through our server are monitored to prevent abuse

Verification of privacy policy is aligned with our governance policy

Secure Infrastructure

Identity and Access Management

Information Protection

Auditing and Monitoring

Manual Controls

Process

No third party is allowed to access data. Processing is limited to extraction of the minimum data needed for organization

Regular operating system are up-to-date and anti-malware signatures is installed

Access to the data is limited to our employees and customer and suppliers

Data directly accessed by the application are encrypted .

All employees could log in based out governance policy.

Delete

Customers who requests for account deletion are deleted from the cloud database.

Log data is deleted as per data retention policy.

Accepted data deletion methods will be followed based on our policy.

Store

All customer information and transactional details are stored in our database .

Server is on regular operating system are up-to-date and anti-malware signatures is installed

Access to transaction logs is granted on a per-role basis and on per the organization's policy.

Transaction log data is encrypted and communications channel is also encrypted.

Data are encrypted before transmitted.

Data backup process is implemented to restore an accidental loss of data.

The log backup process and schedule will be in place.

Compliance requirements will follow the designed policy.

5. Data collection, retention, sharing, disposal, and protection policy

Data protection policy is to ensure that all personal data as well as traffic data are protected… [END OF PREVIEW]

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