Finest practices to enhance data quality


Information quality improvement is typically a hard, costly, and time-consuming proposal. Read about these critical practices to keep your information clean and your reporting accurate.

Creative big data charts. Image: Who is Danny/Adobe Stock The right information can be utilized for several functions, consisting of decision-making, company preparation and operations. With data as the structure for many enterprise IT systems, the quality of information ends up being crucial to the general success of the IT ecosystem.

Data that is of bad quality can lead to inaccurate analytics, functional ineffectiveness and other kinds of issues that won’t let your service reach its optimal potential. In this guide, we provide best practices for improving data quality throughout your company’s various information sets and systems.

SEE: Data quality vs information governance: How they affect your organization (TechRepublic)

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What is information quality?

Information quality describes the condition of an organization’s data in regards to consistency, precision, dependability and efficiency. Data that is high quality fits the function it was intended for and offers an accurate representation of the real-world construct that it describes.

Information quality itself is an easy sufficient concept to comprehend, however maintaining high data quality standards can be tough without the right methods and best practices in location.

Tips to enhance information quality in your service

The emphasis on information quality has increased as companies understand the worth of information in driving company choices and improving the efficiency of operations. Improving information quality is a continuous process, and that is exactly how it must be dealt with. Here are a few tips to enhance data quality at all phases of the information management lifecycle.

Choose how to determine information quality

There are numerous ways information quality can be measured, and there are no set standards for the metrics that must be used to measure data quality. Preferably, a company should determine data utilizing metrics that are meaningful to their organization. The metrics ought to be quantifiable and specific so you can objectively examine and enhance the quality of data. Some examples of metrics you can utilize for data quality include the number of information test failures or the portion of information test protection.

Develop a procedure to examine problems related to information

When you come across concerns or errors related to data, you need to have an established process to investigate the issue. This will assist you understand the concern and take actions to enhance data quality. Recognizing the issue would be among the primary steps in the process. Every time a problem is dealt with, actions should be taken to lessen the likelihood of this issue taking place again.

SEE: Data governance list for your organization (TechRepublic Premium)

The process can consist of a data quality list to figure out if there are any information incoherencies, gaps in the timeline, formatting mistakes or missing out on characteristic values. Duplicating this process with time will assist enhance the quality of data in your organization.

Enlist information stewards

Information stewards are responsible for the application of data policies, rules and procedures as set by your organization’s information governance structure. You can employ information stewards to work carefully with information under their control and make it a top priority to improve the quality of information. Data stewards can be people from your IT or any other organization unit.

Prioritize an information culture in your service

Must-read huge data coverage

Not just do you require to buy hiring and training both data stewards and data quality professionals, but you also need to promote a data-driven culture throughout your business. This culture must begin with the top. Senior supervisors and leaders of the company should lead by example, prioritizing data-driven organization choices and purchasing information quality tools and functions.

A service ought to empower the information group by selecting to have a consensus culture over a hierarchical setup. Any borders between data professionals and magnate ought to be porous, permitting an easy circulation of information and insights.

Use data quality solutions

Utilizing data quality services to support your information quality management strategy is a fantastic way to recognize the complete capacity of your data. Information quality services provide benefits in terms of quality, costs, performance and scale. You can also use other kinds of technology, such as predictive analytics to proactively handle and improve data quality and role-based gain access to controls to keep data healthy and safe.

Data quality solutions

The information quality solutions market is huge, even using specialized options for particular industries and business use cases. However for the majority of companies, a more general information quality option will meet their needs so long as it integrates with their existing tech stack. For groups that want something uncomplicated and detailed, these two data quality options are strong choices with a variety of user features:

Ataccama ONE Data Quality Suite

Ataccama logo. Image: Ataccama uses tools that can turn raw information into actionable data products to support operations, analytics, AI and different other functions of a business. Ataccama ONE includes premium features such as data anomaly detection and automation tools to support a company’s information quality management objectives. It also uses gain access to policy documents and other features that can increase data quality.

Precisely Trillium

Precisely logo. Image: Specifically Although Precisely has been around considering that the 1960s, it has only just recently acquired and fine-tuned its metadata and data governance capabilities. The company offers a number of types of data quality options, consisting of Precisely Trillium, which offers information standardization and cleansing functions to improve and preserve data quality. Application can be done on-premises or over the cloud. The open APIs used by Exactly Trillium permit it to more effortlessly link to the existing IT environment of your service.


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