The flow of information that is so fast with technology that continues to develop has a big influence on the distribution of data needed for the management and management of the company. Fortunately, all things related to data are much easier to do because they can input and manage data digitally or online.
Moreover, data input is an important activity in data management. Given the importance of data management, here are some tips that you can apply to design, manage, and utilize a data management plan.
Understanding the Definition of Data Management
Before discussing tips on designing data management, it helps you know in advance, what is data management? Data management is the process of processing, managing, storing, and maintaining data centers owned by the company.
More effective data management will increase the efficiency of the IT team's work. At the same time, the availability of data can also provide the information needed by the company more quickly, to assist the planning and decision-making processes.
In the process, data management involves a combination of data management functions, availability and ease of access, which collectively aim to ensure you can be quickly reached when you need it.
Most of the work related to enterprise data management is done by the IT team. However, complete processing of other data requires a data scientist and data analytic. In addition, data scientists will also intervene directly, to ensure the processed data meets the company's needs.
Tips for Making a Data Management Plan
Designing a data management plan (DMP) is really needed given the importance of data in a company. DMP will make it easier for you to manage data, get the data needed for the process of making important decisions, prepare company development plans, even based on well-managed data the company can expand and expand the market. Here are some tips for making a data management plan that you can do:
Data Sources Must Be Clear and Accountable
The first thing you need to do is define the source of any data you have. For example, where did your data come from, the type of data, and so on. Categorize each data you get, such as data from observation, simulation, experimental, and so on. If the source of the data is clear, then the data can be said to be valid and useful in business development.
Data Type Grouping
After the source of the data you have processed is clear, also explain the types of data available, then group or categorize the data. The goal is that when you need data, you and the entire management of the company can get it faster and more accurately. Techniques for grouping data types can be based on:
- Text.
- Numerical.
- Audio visual.
- Computer code.
- Musical instruments.
- Fixed data sets or ones that never change after they are created.
- Additional datasets, which you can use to add new data, but not change or delete old data.
- Revised data sets, meaning that new data is added, while old data can be deleted or changed.
- Assign Specific Names for Each Dataset
When managing data, make it a specific name. This way it will be easier for you when you need data. In addition, provide a global recognition scheme to be understood by data scientists and data analytics.
Choice of File Formats to Store Easily Accessible Data
For effective data storage and organization that is easily accessible to everyone, especially enterprise management, choose file formats, such as:
- No ownership.
- If you're using a spreadsheet, use the comma separated values (.csv) format.
- If you are using a text file format, use plain text (.txt). In addition, you can also use the PDF/A (.pdf) format.
- For the presentation format, use PDF/A (.pdf).
- If you are using an image format, use TIFF (.tif, .tiff), you can also use PNG (.png) format.
- For the video format, use MPEG-4 (,mp4).
- Uncompressed.
Use Standard Data and Metadata For Each Data Set
When processing data for business management, it's a good idea to use existing disciplinary standards. However, this is optional and not mandatory. In addition, you can also describe the metadata you want to create.
This is a review of the functions and how to create an effective enterprise data management plan. By applying the tips mentioned above, it will certainly make it easier for IT teams, data scientists, and data analytics to manage company data.
