Why Data Quality and Data Access Are Crucial at Present

Why Data Quality and Data Access Are Crucial at Present

Introduction

Data quality is the measure of the data condition depending on factors such as completeness, accuracy, reliability, consistency, and whether it is up to date. Measuring the data quality levels can enable organizations to recognize data errors that need resolving and evaluate if the data in the IT systems is good enough to serve the purpose. The importance on data quality in enterprise systems is increasing each day since data processing as data intricately linked with business operations. Also, organizations increasingly use data analytics to help gain business insights. Data quality management is the key component of the overall process of data management process.

Data Quality and Data Access

Without the correct level of data quality, using data may lead to incorrect business insights by business leaders, their teams, and even algorithms. Ensuring that the right data is easily accessible to the right users is crucial. Ensuring that users are able to access the data quickly and in a user-friendly way allows them to fully analyze and interact with the data. Thus, data quality and easy and full data access is an essential part of upcoming digitization and data projects.

Challenges with Data

Based on current reports, a significant “data decision gap” is impacting organizations’ business intelligence efforts. Organizations worldwide are investing in data at a much higher rate, however, the decision-making process has “not changed at all” in such organizations. The main attitudinal or cultural challenge for using data effectively is that too few people in most organizations understand how to access useful data or use it to drive meaningful business insights. Decisions are still largely being made from a gut feeling, rather than data. Even as organizations have adopted the power of data, most organizations continue to struggle with the implementation due to their data tools.

Data Democracy

Businesses that adopt suitable tools for democratizing the data are aware of the advantages of data-driven decision-making. It is excellent to have all this data, but if you cannot help the employees to use the data easily to drive better business insights, then the investment of the organization in the efforts does not matter at all. Ease of access to data via integrations and apps can allow organizations to capitalize quickly on their investments in digital transformation over the recent years.

Integration of Database

A good working database is the key to linking all data processes together. This, in turn, supports various users and applications in the business, with efficient data access and quality stored data. When selecting a database, it is essential that it is flexible with respect to the data capacity. A database should be able to respond quickly to the needs of a business. Making the correct choice helps avoid unnecessary expenses and potential integration and technical problems when there are modifications to the operational data needs in the future. There also needs to be a straightforward way to put across information into the database via its integration with other business applications, and an easy quick way to extract applicable information using various formats.

Conclusion

Ideally, organizations should utilize a single database to store different data types. This will help organizations efficiently extract the full value from the data and simplify their data handling and data stack. One must be able to generate accurate and faster business data insights, whether a single user or thousands of users are demanding information simultaneously.