Data Availability

Owned by Mike Deskis
May 19, 2023
2 min read

Successful pricing implementations require high-quality data available from the beginning of the configuration effort.  We work with you to establish a timeline for when data is available and align this with the overall project timeline. 

Data availability refers to the accessibility and reliability of data when it is needed. In the context of data readiness methodology, data availability is one of the key components of data quality. A high level of data availability ensures that the data required for business operations is accessible in a timely manner, and is accurate, complete, and consistent. Poor data availability can lead to delays in decision-making, and missed opportunities, and can negatively impact business performance.

Therefore, it is important to assess data availability as part of the data readiness process to ensure that the organization has the necessary infrastructure and processes in place to provide reliable and timely data.

Characteristics of Data Availability

The characteristics of the data availability concept in data readiness methodology are as follows:

  1. Accessibility: Data availability means that the data is easily accessible and can be retrieved when needed. It involves having the right systems, tools, and processes in place to ensure that data can be accessed by authorized users.

  2. Timeliness: Data availability emphasizes the importance of having up-to-date and timely data. It ensures that the data is available in a timely manner to support real-time decision-making and operational processes.

  3. Reliability: Data availability requires that the data is reliable and trustworthy. It should be free from errors, inconsistencies, and inaccuracies to ensure that it can be relied upon for decision-making and analysis.

  4. Scalability: Data availability considers the ability to handle large volumes of data. It involves having scalable infrastructure and systems that can handle increasing data loads without compromising data availability.

  5. Redundancy and Backup: Data availability also involves having backup mechanisms in place to ensure data is available even in the event of system failures, data loss, or disasters. Redundancy measures, such as data replication and backup systems, help ensure uninterrupted data availability.

  6. Security: Data availability takes into account the security of data. It involves implementing appropriate security measures, access controls, and encryption to protect data from unauthorized access or breaches, ensuring data remains available only to authorized users.

  7. Data Integration: Data availability also considers the integration of data from various sources. It involves ensuring that data from different systems and sources can be integrated seamlessly to provide a comprehensive view of the data.

By prioritizing these characteristics, organizations can ensure that data is readily available, reliable, and accessible for decision-making, analysis, and operational processes within the data readiness methodology.