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Simplify your data management

Data management can be a complex and challenging task, especially when dealing with large volumes and lots of variety of data. There are steps you can take to to simplify the management of your data. These methods include:

  1. Know your data: The first step in simplifying data management is to know which data you have to manage in the first place. You may assume that you already know where your data is. But in modern, distributed environments that include a range of different data storage assets – like on-premises RAID arrays, network file shares, databases, cloud object storage and beyond – it can be easy to overlook data stores. You may also not be sure which types of data you have. That’s why it’s important to step back and catalog or map your data. Document all of the locations where your data lives, as well as which types of information you store. This visibility provides the foundation for simpler data management.

  2. Identify data silos: When you know where your data lives, you can also identify data silos. A data silo is a data set that is difficult to share across the organization. Typically, data becomes siloed because one business unit or department “owns” the data and doesn’t configure it for easy accessibility by others. You should determine where data silos exist, then take steps to increase accessibility. Although you may not want every data set to be accessible by everyone in the business, you also probably don’t want some data to be hidden away by one department, with other business units deprived of access.

  3. Use data governance: Data governance is the process of establishing, aligning, and securing data within an organization. It aims to ensure that data is collected, stored, processed, and disposed of consistently. Data governance covers the strategies and processes needed to manage enterprise data effectively to leverage it for business decision-making. It also provides a framework for managing the risk associated with businesses in an uncertain regulatory environment. In short, data governance is about managing all organizational information assets — not just data but also documents, applications, networks, configurations, and metadata. By implementing data governance, you can ensure that your data is managed consistently and securely across the organization.

  4. Standardise data management: Standardisation can really help simplify data management. Processes can be standardised and communicated to all stakeholders. Data inputs can be standardised and validation applied at the front end, eliminating errors at source. Adopting standards and schema can simplify both the management of data and improve error proofing.

  5. Automate data management: Automation can help simplify data management by reducing the need for manual intervention. For example, you can use automation to perform routine tasks like data backups, data archiving, and data replication. Automation can also help you to identify and resolve data quality issues more quickly and efficiently. But dont view automation as a panacea

  6. Use cloud-based data management tools: Cloud-based data management tools can help simplify data management by providing a centralized platform for managing data. These tools can help you to manage data across multiple locations and devices, and they can also provide advanced features like data analytics and machine learning. By using cloud-based data management tools, you can simplify data management and reduce the need for manual intervention.

  7. Implement data quality controls: Data quality controls are processes that ensure that data is accurate, complete, and consistent. By implementing data quality controls, you can reduce the risk of errors and inconsistencies in your data. Data quality controls can include processes like data validation, data cleansing, and data profiling.

  8. Train your staff: Finally, it’s important to train your staff on best practices for data management. This includes training on data governance, data quality, and data security. By training your staff, you can ensure that everyone in your organization is on the same page when it comes to data management.

In conclusion, data management can be a complex and challenging task, but there are several practical methods that you can use to simplify it. These methods include knowing your data, identifying data silos, using data governance, automating data management, using cloud-based data management tools, implementing data quality controls, and training your staff. By following these methods, you can simplify data management and reduce the risk of errors and inconsistencies in your data.

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