As your startup grows, the amount of data you need to store and manage will increase over time. Therefore, your startup needs to know how to manage big data correctly to prevent data loss or damage. Without a data management strategy, your business may become overwhelmed, leading to chaos. This article will run through some ways in which you can manage and maintain your data.
Outline Business Goals in Data Management
Firstly, before you start managing big data and deciding which strategies you want to use, you should set your goals. Knowing what you want to do with the data and what data you need prevents the data management software from becoming overcrowded and disorganised. Thus, you should keep only the information you want to use to keep things manageable.
After outlining your goals, you can choose appropriate methods and a data management system to execute them. Your business can utilise many types of software, such as:
- relational databases;
- cloud services;
- decision support systems; and
- transactions processing systems.
Cloud Computing
To manage increased data flows, your startup can use cloud computing services. With cloud services, your company can store data on an offsite server that a vendor usually owns. This will enable you to have an automated backup strategy, professional support, and easy access to your data. In addition, with a cloud, you can manage your data with ease, and it will be easier for several people to access the data simultaneously. Your cloud can be as big or small as you require to ensure adequate data storage.
To use a cloud service, you need first to have a plan. Your startup needs to plan who has access to the data and how much data you will move into the cloud. Next, you need to know whether you can use a public, private or hybrid cloud.
You will also need to ensure that all data entries are accurate and do not duplicate pre-existing data. It is a good idea to back up the data yourself, even if the cloud provider is already backing it up.
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Use Metadata
Metadata is information about the data you are using or managing. To manage data, you can include information about the data, so it is easily discoverable for future use. In addition, specific information is more searchable in a large amount of data and can save you time and stress.
You can use metadata to include information such as:
- author;
- field description;
- when data was created;
- where data was created;
- why data was created;
- file size or type; and
- last modification date and time;
Reduce Duplications
During increased data collection, it is likely that some data entries are duplicates of pre-existing data. Duplications cause data software to become overcrowded and reduce accuracy if both entries have different information. Your startup should have processes in place to minimise duplications of data. However, your methods should allow data to be updated to ensure data stays accurate and clean.
Maintain High-Quality Data
As data flows increase, you may lose track of how accurate data is. The principle with data flows is if the input is garbage, the output will also be garbage. This is known as garbage in, garbage out, or GIGO. To minimise GIGO, you need to ensure that your business records high-quality and clean data continuously to make better business decisions. When recording data, it should be:
- accurate;
- complete;
- valid;
- unique; and
- consistent.
Key Takeaways
With increased data comes increased issues, and your startup needs to be prepared to manage such data flows. You should first outline business goals in data management, then choose methods to help you execute your goals. You can use cloud computing to efficiently manage high volumes of data and metadata to ensure data is organised. Reducing duplication and ensuring high data quality is vital to keep data manageable and accurate.
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Frequently Asked Questions
Cloud computing is an application-based software that stores your company data on remote servers, which can be accessed through the Internet. Cloud computing services can either be public, private, or hybrid.
To maintain high-quality data, you must ensure that data inputs are accurate, complete, consistent, and valid. This will minimise GIGO, so data is available and ready for use. You can also reduce data duplications through cross-checking and having processes in place, so duplicate data is not recorded.
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