English 
Vietnamese As a result of the ever-increasing amount of data, reducing the need for manual tasks in data management is a key objective every business should be pursuing. These data management best practices are used by industry-leading businesses to help increase visibility into their data and reduce costly errors.
What is data management?
Data management is the process of consuming, storing, organising, and sustaining data that is created and collected by a business. Data management is extremely important for businesses as it is used in daily functions.
The importance of data management
It is important to keep up-to-date with data management and with changes and improvements of data management software as it becomes increasingly digitalised. Having an up-to-date data management tool allows businesses to increase their competitiveness due to the numerous benefits it provides.
Data management is indispensable in making decisions, improving efficiency, and reducing costs. All these benefits have the overall aim of increasing a business’s financial outcome and competitiveness.
Read more: What can businesses get from data management and democratisation?
Benefits of data management
1. Productivity
It makes it easier to filter through data as it is stored in a place that is easy and accessible to use.
2. Cost efficiency
As data becoming more accessible and reliable, this will make decisions more dependable and, in particular, will reduce the risk of money being injected into decisions that may not be as effective. It also makes the data for research and analysis purposes within a business more effective as the data is easy to filter through.
Read more: Rise of Chief Data Officer (CDO) to Solve the Data Issues
3. Reduced data loss
As data is managed and stored correctly, this will reduce the risk of data becoming lost, especially as data is becoming more reliant on technological ways to store data.
4. Security risks
Data management helps data stay safe and can also protect against data breaches.
5. Accurate decisions
All employees will be analysing the same data which helps makes more accurate decisions.
6. Operational nimbleness
It is easier to adapt to the changing environment around your business and it can make more efficient changes in response to competitors.
Best Practices for effective data management
In order for a company to ensure they have high-quality data, it is important to implement effective data management practices. This reduces the risk of dirty data that could create several negative effects on companies.
1. Define and outline goals
Companies should set goals for data management and understand what their future plans are for using the data that is collected. By setting these goals, it means that the collected data can aid you in only keeping data that is relevant to your set goals and reduces the risk of your data management software from becoming too full and unorganised.
By only storing data that is will be used in the business at a later date and relevant to the business will make it more manageable and may also help with efficiency as there is a reduction in the time taken to store and filter through data.
2. File naming and cataloguing
Storing data with useful names and creating a reporting or file system may increase the time storing the data but it will reduce the chances of confusion when filtering through the data. It allows the data to be recognisable and will overall improve business efficiency as it will be easier to find specific data and reduce the chance of people comparing different data sources.
3. Description of data
Adding a description of the data will make it easier to find in the future. The description can contain information about the data’s content, structure and permissions.
4. Prioritisation of data protection and security
Data protection and security and security needs to be a top priority, especially with the growing concern about data breaches. It is extremely important for consumer data to be protected and for companies to comply with regulations.
Learn more: Make compliance an opportunity not a burden
5. Quality of data
If data is high quality, it should be checked regularly as data can become outdated and inaccurate and this will impact the success of analysis and decision making within the business.
6. Reduce duplicate data
Duplicate data could lead to inaccurate analysis and business decisions. Introducing a system that rules out duplicate data will in turn reduce the risk of dirty data.
7. Accessible data
Although you want to ensure security, data still needs to be accessible for your team. If data is difficult to access this may reduce business efficiency as the time it takes to access the data is increased.
8. Data recovery strategy
Creating a data recovery strategy means any errors can be undone. This is extremely important as accidents may happen and if any data lost cannot be recovered. This can cause an inaccurate store of data which will also affect analysis and decision making in the future.
9. High-quality data management software
Making sure your business has the best data management software may induce a high initial cost but in the long run will be worth the investment.
All data management will vary, and it is vital that you find data management software that is best for your business as investing in the wrong software can cause errors. Finding a data management software that suits the style of your business will increase the efficiency of your business and provide several benefits so extensive research will need to be done.
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