As data travels from your local server to your desktop or to the Cloud server, data quality is always in danger of being compromised; your applications are in danger of displaying information that is erroneous. Have you ever wondered how you can protect your data, as it travels around the ecosystem you have designed with the Cloud as part of the equation?
Remember, what you may term as a minor event in your data backup process can lead to major problems in data outputs. A single data corruption event can create a chain of events. For instance, an incorrect input into the backup and recovery system (eg. duplicate data) can lead to wrong data analysis and poor decision-making, resulting in loss of revenue and failure to comply with governmental regulations.
So, take care, and pay attention as data quality is very important.
Effective solutions for maintaining and managing data quality will have to be taken even before you certify that the data is ready to be transmitted to the Cloud or across the network for use of your organization.
The process of ensuring your data is ready for use will include the following steps:
- Data profiling: Data profiling is the process of examining your data and understanding all the data issues associated with that data. It is the process of checking the integrity and completeness of the data even as it is being generated, tabulated and stored in the system.
- Reference data: Reference data is “descriptive” data about data. This may be called Metadata. It is an effort to standardize sections of the data and provide descriptions for the data in a manner that make sense to the users of the data. There are many data quality tools that may be used to leverage these standards and use them to ensure data quality.
- Data Standardization: Data Standardization is the process of standardizing inputs for specific fields in a data record. For instance, city names, postal codes and street names can be pre-defined so that mistakes are not made during data input. This makes it easier for the organization to find duplicates of data.
- Matching technology: Matching technology includes de-duplication technology. It is a step forward in standardizing data before storing data in Cloud repositories or local databases. Elimination of duplicates speeds up data transfer and saves on disk space in storage.
- Data monitoring: Data monitoring is the process of ensuring that your data is accurate at every stage of its transmission across the network.
Securstore can help you improve the quality of your data by making sure your data is backed up in the Cloud using BLM, and data is monitored and made accessible anytime and anywhere.