Data Management is a bit of a vague and awkward term. Data management and big data are entangled, you cannot mention the one without considering the other. If you are handling a huge amount of data, it would be risky not to have proper data management policies in place. One way to effectively structure these policies is considering the overall life cycle of data.
The Data Life Cycle
The life cycle of data can be explained briefly by the following:
- Creating data. This is the easy part, and the abstract part. Creating data is like thinking thoughts. Any meaningful form of information is data. It doesn’t even have to be in tangible format yet.
- Processing data. This is a PhD topic on its own, but simply put, do something with the data that was created. Capture it in a database, post it on a social media application, calculate it using relevant software. Work with the information.
- Analyzing data.This refers to the process of taking raw data and, well looking at it and extracting valuable information from it, investigating the data and drawing deductive or inductive conclusions, explanations or interpretations from what is observed. The method to analyze and the deductions made from the analysis depend on the nature of the data, whether it’s qualitative or quantitative.
- Preserving data. This relates to backing up your data and storing it in a safe place. It also involves deciding how long to keep data for and which media is most effective for such retention.
- Giving access to data. Trustworthy data protection and backup companies allow users access to their data, Anytime, anywhere.
- Re-using data. Recycling is good. Two main aspects include the re-analysis of data (like when NASA found a new planet whilst re-analyzing old data) and data serendipity (such as the discovery of knowledge from old data that was not necessarily collected for that purpose).
- Purging data. Purging data refers the method of permanently erasing data. Forever. Scary thought, but sometimes the volume of data just becomes too much to archive. And it is good to just let it go.
Tips for Data Security In Your Data Management Plan
There are multiple practices, applications and policies that are very important for each of the above-mentioned life cycle phases. In order to stay in control of your data, it is important to know your data is managed effectively and that such management is conducive to good data security. Here are a few tips to that effect:
- Make sure your data is organized at the source. Start the data management process off on a good foot.
- Set up data tiers. Make sure your backup and data storage service provider makes use of Hierarchical Storage Management, or HSM, in order to optimize your storage policy.
- The Hybrid cloud is your (and your data’s) friend. It allows for best of both on-site and off-site cloud storage and flexibility to manage aspects of either – depending on the needs of your business.