Also called the information lifecycle, this refers to the entire period of time that data exists in your system.
There are nine stages to the data lifecycle, from start to finish:
- Creation or generation. This stage describes the first time you acquire data from sources. You can generate data internally or externally, either from your staff, customers, clients, sales, hiring, and communication. Everything you do generates data.
- Data collection. You have several ways to collect data, including communication, observation, interviews, surveys, forms, and devices.
- Data processing. This occurs when software takes raw data and transforms it into something usable. Programs clean, remediate, compress, encrypt, and translate data.
- Data storage or archiving. You need to store the data once you have it. To this end, you must protect it from intrusion and loss by backing up your data, whether you store it on-site or in cloud storage.
- Data management. Also known as database management, this is how you organize, store, and retrieve data.
- Data analysis. For most companies, data analysis is the most important part of the data lifecycle. Once you have raw data, you have to process it for later analysis. Your computer system generally utilizes software to integrate, validate, apply, and transform raw data into useful information. Software may reformat, summarize, organize, standardize, and enrich data so you and your staff can make use of it. Software will interpret data on preset parameters that let you examine statistics in charts, visual representations, and other digestible formats. You can use apps, software, algorithms, and artificial intelligence (AI) to analyze data.
- Data visualization. This is where software turns usable data into visually appealing formats for staff to see.
- Interpretation, sharing, and publication. Now you make sense of the data. At this point, if you still need the data, it can repeat any parts of the first eight steps over and over again until you are done with it.
- Data destruction. This is the final step of the data lifecycle. When your data has outlived its usefulness, it must be destroyed properly. You might need to perform data destruction due to regulatory and compliance issues or the cost of storage becomes too cumbersome.
Before you begin the data lifecycle, you need a plan in place. The plan must outline specific details, such as:
- Create a data backup policy.
- Choose your data storage system (on-site, cloud).
- Define data outcome parameters.
- Define roles and responsibilities of managers, supervisors, and employees.
- Identify sensitive data.
- Provide security to protect data.
- Calculate costs of data management.
- Decide what happens to the data at the end of its life.