Final project term about information governance

Assignment Week 1 Name: Manchoopaporn Boonchoo ITS 833: Information Governance Date: 1/7/21 All organizations need to plan how to use data to manage their business to consistently support business results. This means that successful organizations must consider the who - what - how - when - where and why of data to ensure security and compliance and to extract value from all the information collected and stored across the business, hence improving the business performance. Basically, any organization's ideal effort is making sure that their data is meaningful, correct, and timely. Therefore, many analysts are increasingly focused on quality on a per-attribute basis instead of a per-report basis. This helps the organization to avoid excess control of access and instead focus on meaning. A data-driven organization that includes a comprehensive data cleanup can make informed choices that maximize value on strategic investments. To clearly understand the necessity of these efforts, we begin by comprehending what data governance is, techniques like data cleansing and de-duplication, their importance, and their overall benefits to the organization. Data governance is defined as a set of principles and practices that ensure quality through an organization's complete data's lifecycle. Data governance efforts to ensure that control systems, processes, and formal management policies are used to control critical data assets to improve quality and to avoid the negative effects of poor information (Smallwood, 2014). Therefore, it is a practical and actionable framework to help various data stakeholders across any organization to identify and meet their information needs. Organizations don't just need systems for managing data. They need a whole system of rules, with processes and procedures to ensure those rules are followed fully and consistently. Of the several data governance techniques available, I will discuss two:

a) Data cleansing. b) Data de-duplication.

a) Data cleansing. Data cleansing or data scrubbing is the process of fixing, detecting, editing, or deleting to remove invalid data items from a dataset. Focus is on fixing, updating, and gathering information to ensure your system is as efficient as possible. If the information is inaccurate, the results and algorithms will be unreliable, even if they may look correct (Tableau, 2019). Many benefits of data cleansing, such as the use of data cleansing tools can help run businesses more efficiently and make decisions faster. Less error makes happier customers and less frustrated employees (Gimenez, 2020). So, cleaning up the data does not only consist of managing good data and protecting against invalid data, it also consists of updating the database to fix outdated information including fixing various errors that might affect data storage.

b) De-duplication. Data de-duplication is a technique for eliminating duplicate copies of repeating data. De- duplication can be run as an inline process. Data is written to the storage system and/or a background process to remove duplicate data after the data is written to disk (NetApp, 2017). Such a technique can make significant changes in your backup capabilities by managing storage resources more efficiently. The benefits are in the following. First, efficient storage allocation assures data redundancy will not happen because only unique data can be written into a disk. This technique will free great storage capacity and allow you to have more space to allocate data. Second, reducing storage capacity will surely help an organization save money. Cost-saving is a benefit that anyone would be pleased with. Third, Network optimization. De-duplication optimizes storage by preventing data from being sent over the network, which frees up more bandwidth needed to maintain network performance and reliability. Fourth, besides using less storage capacity and spending less money on backup devices. Physical space and the use of power energy will also be reduced, leading to better data center efficiency. Lastly, faster recovery and continuity is possible when duplication is reduced, resulting in speeding up data processing. That also means that de-duplication lets us recover backup data much faster. It will reduce downtime and help keep business plans running on track. (Bradford, 2019) The main benefit of data governance, as Smallwood so aptly states is: “Good data governance ensures that downstream negative effects of poor data are avoided and that subsequent report, analyses, and conclusion are based on reliable trusted data.” (Smallwood, 2014).Therefore, data governance and organization play a key role in any business organization's success. In this era, data is now considered an asset that results in a competitive advantage against their competitors if well-managed. Reference:

Bradford, C. (2019, March 15). [web log]. https://blog.storagecraft.com/understanding- importance-deduplication-backup-strategy/.

Gimenez, L. (2020, November 20). 6 Steps for data cleaning and why it matters. Geotab. https://www.geotab.com/blog/data-cleaning/.

NetApp. (2017, January 1). What Is Data Deduplication: Benefits & Use Cases. Data Management. https://www.netapp.com/data-management/what-is-data-deduplication/.

Smallwood, R. F. (2014). chapter 2. In Information governance: concepts, strategies, and best practices (p. 20). John Wiley & Sons.

Tableau. (2020). Data cleaning: The benefits and steps to creating and using clean data. Tableau. https://www.tableau.com/learn/articles/what-is-data-cleaning.