This has led to the search for intelligent solutions that support the structuring of these records. After all, the process of maintaining a standard in the company's internal files is essential for decision-making and strategic actions within startups.
Want to learn more about how maintaining good quality australia whatsapp users data can transform your corporation ? Find out more below:
Better understand the context of data quality
Data quality is directly linked to theBusiness Intelligence(BI). This, in turn, aims to transform registered files into relevant insights for business actions. Thus, it is a process that collects, organizes, analyzes, shares and monitors information.
Incorrect data can cause several problems for the institution , such as difficulties in decision-making and incorrect strategic directions. For this reason, they are so essential for organizational success.
See the next topic for the main dimensions to consider regarding the relevance of information within your business.
The 6 dimensions of data quality
The most common factors for measuring data quality are:
Completeness
The completeness dimension refers to the extent to which records are present and cover all necessary information. This means that records must be collected and stored comprehensively, without significant gaps or omissions.
This factor also ensures that all necessary fields are filled in. Furthermore, there is no missing information that could compromise the analysis or its use.
Consistency
Consistency refers to the uniformity and harmonization of data throughout its structure. This implies that files must be free of contradictions, duplications and discrepancies.
This dimension also involves the standardization of formats, units of measurement and conventions used in records. With this in mind, maintaining this point is essential to enable the effective integration and comparison of information across different systems and sources.
Accordance
The compliance dimension addresses the adherence of data to established rules, regulations, and policies. In other words, they must comply with defined quality and governance standards, as well as federal laws.
Precision
Accuracy refers to the accuracy and reliability of information. This implies that it must be correct and faithfully represent the reality it intends to portray.
This point involves validating and verifying data against reliable sources. Errors and inaccuracies can lead to erroneous decisions and incorrect analyses, which shows the relevance of this factor.
Availability
The availability dimension discusses the accessibility and readiness of files when needed. This ensures that records are available for use when required, without significant delays or interruptions.
It also addresses the ability to recover in the event of system failures or interruptions. This is an important safeguard to support the continuity of operations and timely decision-making.
Integrity
Ultimately, integrity is about the overall state of data in terms of its completeness, consistency, and accuracy over time.
As a consequence, records must be kept safe from unauthorized alteration, corruption or loss. This dimension involves implementing control and security mechanisms to ensure that records remain reliable and are not compromised throughout their lifecycle.
Why invest in data quality management?
Investing in good data quality management is essential to maintain secure and valid information to take care of the health of the business . In addition, it is vital to outline improvements to the functioning of internal activities, such as in relation to the company's operating method and administrative and strategic issues.
The importance of maintaining data quality is linked to how information can be useful and contribute to achieving better business performance. Thus, it is a process that:
Supports predictive and non-predictive analysis
Data underpins the company's analyses, whether predictive or non-predictive.
The first is a way of thinking about forecasting trends considering a specific factor. The second can identify the period that provided the best performance for the company or observe the evolution of sectors, for example.
Assists in marketing strategies
The quality of records results in more assertive marketing actions and strategies, since distorted or erroneous information will be eliminated.
Furthermore, this factor will directly influence more accurate results , since the information collected will be filtered. In other words, it is an important process for targeted and efficient actions.
Help in decision making
With a focus on data quality, making sensitive business decisions becomes a more reliable process . This is because the information collected is vital for decision-making within the company and can directly impact the outcome of an action.