2022 information governance homework help

Introduction

Information governance is a strategic approach to managing corporate information by implementing processes, roles, controls and metrics that consider information as an important business asset. The goal of a holistic approach to information governance is to make information assets available to those who need it, while streamlining management, reducing storage costs and ensuring compliance. This, in turn, enables the company to reduce the legal risks associated with unmanaged or inconsistently managed information and be more agile in response to a changing marketplace. Get top notch information governance assignment from assignmentsguru. We are highly motivated to get you quality assignments that will improve your grades. At assignmentsguru we have a pool of experienced information governance experts. Our writers respects students need for privacy and that’s why our customer care service are very discrete. Incase you need any assignments help let no one lie to you just click order now button.

An important goal of information governance is to provide employees with data they can trust and easily access while making business decisions. The release of a new OS or upgrade to a database can lead to decisions and actions that impact the data repository and provisioning. To prevent

Information governance provides a wide range of benefits. It ensures the following:

• whoever requires access to certain information can receive it;

• underlying data is properly managed, stored and secured;

• regulatory requirements are correctly observed, where necessary; and

• risk management is in place to minimize any issues that might arise from incorrect use.

Why is information governance important?

Information governance makes information more accessible to those who need it, which is crucial for any organization. Organizations of all types and sizes often suffer from poor organization and management of information assets, leading to issues with accessibility, ease of use, timeliness and security — all of which governance can positively affect.

Often, the same information may exist in more than one location, leading to issues with updating. When the same information is in several places and does not agree, confusion can ensue. Effective information governance can establish single source of truth (SSOT), rendering information more trustworthy.

Effective information governance is so important that it has become a C-suite role in many organizations, with an executive responsible for its implementation. The chief information governance officer (CIGO) often oversees the initial governance initiative, shepherding its development, management and ongoing evolution throughout the organization. The officer is generally responsible for maintenance of information integrity standards, gathering required quality and usage metrics and ensuring that the company meets compliance and regulatory requirements.

It is also increasingly common that the enterprise establish an information governance council composed of key stakeholders in the organization, including management-level representatives from every area of the business, information technology (IT) personnel involved in infrastructure and security, and subject matter experts who fully understand how specific information is used. This governance council often aids the executive officer in implementing and enforcing governance policy and can be invaluable in helping to guide its ongoing development.

A commitment to information integrity throughout the enterprise requires the active participation of employees at all levels and in all areas. Awareness of and commitment to information governance processes should be organization-wide, actively promoted and frequently updated.

What is the difference between data governance and information governance?

When considering information governance, data fidelity, as a concept, is a nebulous term which historically referred to data quality. From the current perspective, data fidelity refers to the level of completeness and purity of a given dataset. Data that is flagged as “clean” or “upgraded” will require very little human intervention. It doesn’t have to be perfect—the key is ensuring nothing needs improving

Information governance refers to data assets that have carefully defined business meanings; data governance, on the other hand, refers to the oversight of the physical data itself — its storage, security and transport. Someone implementing data governance might perform those tasks with little or no understanding of the data’s meaning, while, in information governance, meaning is everything.

Information governance challenges

Even a clear vision and strong management support don’t guarantee information governance success. Organizations can experience a number of common issues when implementing information governance, including the following:

• Compliance and regulatory issues. An organization often requires information governance during a lawsuit or some other consequence of noncompliance. On such occasions, compliance teams must go through potentially millions of pages of documents — and possibly even more rows of data — in pursuit of information that has been requested for legal purposes. In an electronic discovery economy, recognizing a problem and determining a solution are two activities that require a high level of information search and organization. While this process is less of a concern in the info age where data is at hand, it can cause serious problems when digitized items have physical separation from the source of data.Organizations can mitigate this challenge using several strategies, such as the following:

  • establishing a universal metadata taxonomy for consistent tagging of information;

  • developing a consistent retention management/defensible disposal policy and process; and

  • establishing a data classification program to rate all information assets according to their sensitivity.

• Big data and machine learning. Machine learning is essential for any enterprise to reach its full potential. Without it, the organization would eventually lose its competitive edge. However, machine learning is a powerful tool that can be used to improve the accuracy of predictive models. Careful attention to the integrity of data sources and the merging and transformation of data from multiple sources is essential in this endeavor. Organizations should ensure that the big data underlying the analytics is as accurate and clean as possible, and strong governance policy can help ensure this.

• Lifecycle management. One major challenge of an information governance implementation is the need to manage data that underlies information assets throughout its lifecycle in multiple domains. As silos come down and information becomes more centralized in the enterprise, inconsistencies in its management can creep into existing processes, causing friction between groups. All groups using common information must agree about the process of refreshing, modifying and archiving that information. Achieving policies that encourage such agreement should be a responsibility of the governance officer and council.

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