As businesses rely heavily on data for decision-making, understanding the importance of effectively managing and leveraging data has become critical. Data management ensures that organizations can access, store, and utilize data efficiently, leading to improved operational efficiency, better-informed decision-making, and enhanced overall performance. Implementing best practices for data management can help businesses maintain data integrity, ensure regulatory compliance, and mitigate the risks associated with data breaches and loss. Thus, businesses can ultimately save time and money.
Best Practices for Data Management in 2024
The key challenges of data management in 2024 include –
- Handling the exponential growth of data
- Ensuring data security and privacy in the face of increasingly sophisticated cyber threats
- Employee awareness
- Complying with evolving data regulations, and
- Harnessing the potential of emerging technologies such as automation and machine learning for functional data management.
The following best practices can aid in resolving the above challenges in data management –
Data Security and Compliance
Data security measures are essential for protecting sensitive information from unauthorized access, theft, and manipulation in the face of evolving cyber threats. These measures help mitigate the risks associated with sophisticated cyber-attacks and uphold data confidentiality, integrity, and availability in the evolving cybersecurity landscape.
A significant data security requirement for 2024 is the encryption of sensitive data to render it unreadable to unauthorized users. Other data security tactics include having robust access controls to limit data access to authorized individuals, and regular security audits and vulnerability assessments to identify and address potential weaknesses.
These tactics can only be beneficial when the following compliance considerations for data management are followed –
- Stay updated with evolving data privacy laws such as GDRP, CCPA, and emerging regional laws
- Ensure compliance with industry-specific data security standards such as ISO 27001, PCI DSS, and HIPPA to protect sensitive information
- Establish and maintain data retention policies to comply with legal and regulatory requirements for retaining and disposing of data
- Understand the regulations governing cross-border data transfers and implement appropriate safeguards for internal data sharing
- Consider the ethical implications of data usage and ensure compliance with ethical guidelines related to data collection, storage, and processing
Need to be confident of your compliance needs? Tenax Solutions, an IP Pathways Company, can help!
Data Governance and Quality
Data governance is a critical aspect of any enterprise, encompassing the management of data’s ability, usability, integrity, and security. It involves coordinating people, processes, and technology to safeguard data assets. Establishing robust policies to ensure data quality and consistency is paramount, as it guarantees the proper handling of data assets.
The following steps create an effective data governance policy that supports data integrity, security, and usability.
- Identify Stakeholders: Determine the key stakeholders who will be involved in the data governance process, including executives, data managers, and IT personnel.
- Assess Current State: Evaluate the existing data management processes, data quality, and security measures to understand the organization’s current state of data governance.
- Define Objectives: Clearly outline the objectives of the data governance policy, such as improving data quality, ensuring compliance with regulations, and enhancing data security.
- Develop Policies and Procedures: Establish specific policies and procedures for data access, usage, storage, and security. This may involve creating data classification standards, retention policies, and access controls.
- Assign Responsibilities: Clearly define the roles and responsibilities of individuals involved in data governance, including data stewards, custodians, and owners.
- Implement Technology Solutions: Utilize data governance tools and technologies, such as data quality management systems, metadata management tools, and data security solutions.
- Communication and Training: Communicate the data governance policy across the organization and provide training to employees to ensure understanding and compliance with the policy.
- Monitor and Review: Establish mechanisms for monitoring and reviewing the effectiveness of the data governance policy, including regular audits, data quality assessments, and compliance checks to foster continuous improvement.
Scalable Data Storage Solutions
Managing a growing volume of data presents challenges such as ensuring data security and privacy, maintaining data quality, scaling infrastructure, and managing diverse data sources and formats. Some best practices in managing an increasing data volume include updating equipment, scaling infrastructure using cloud services, and utilizing modern data integration and management solutions to handle diverse sources and formats.
The most popular way to scale data storage in 2024 is by utilizing cloud storage services. Cloud-based storage offers flexibility and cost-effectiveness, allowing users to easily increase or decrease their storage capacity based on their needs to scale. Many cloud storage providers offer various storage tiers and options to accommodate different types of data and usage patterns. Implementing a hybrid IT storage solution both on-premise storage and cloud storage has proven to be the future of data storage.
International Data Corporation (IDC) reported in January of 2023 that spending on cloud infrastructure will have a compound annual growth rate (CAGR) of 12.9% over the 2021-2026 forecast period. Meanwhile, spending on non-cloud infrastructure, such as on-premises storage, will have a CAGR of 2.3% over the 2021-2026 forecast period. While both storage solutions are expected to grow, they each carry their own weaknesses. However, combining the two to create a hybrid solution will bring their strengths together and minimize weaknesses to develop the most efficient IT storage solutions for your business.
Considerations for selecting the right data storage solutions for business needs.
Data Analytics and Visualization
Leveraging data analytics tools provides meaningful insights and helps make decisions more accessible by allowing businesses to uncover hidden patterns, correlations, and emerging trends within their data. These tools can process large volumes of data quickly and accurately, providing a deeper understanding of customer behavior, market trends, and operational performance. Businesses can use data analytics tools to make informed decisions based on real-time data, leading to improved efficiency, better resource allocation, and a competitive edge in the market. The proof is always in the numbers!
Data Backup and Disaster Recovery
Regular data backups and archiving are essential for preventing data loss because they provide a safety net in case of hardware or software failures, human error, cyber-attacks, or natural disasters. They also help with compliance, legal requirements, and business continuity planning. Not having a data backup or disaster recovery plan leaves data at a high risk of being lost after an unplanned event and can lead to costly downtime.
A data backup creates copies of your files in a secondary physical or virtual location saved at set time intervals. Somebody could store this data on another storage device like a flash drive, a hard drive, or cloud storage. There are many different types of backups, many of which are often used together. A general rule with backups is to follow the 3-2-1 rule. This rule means you should have three copies of your data. Two are stored on-site; the remaining copy will be stored off-site.
Disaster recovery is a process/plan that satisfies the need to access and use your data when the primary location is down. The backup infrastructure will support the operations when your primary data location is down. Once your primary location is up, you can switch back to and use the primary location. DR is essentially duplicating your production environment for redundancy. Without a DR plan, your recovery costs can be high. According to Gartner, the average cost of downtime runs to $5,600 per minute or more than $300,000 per hour.
Employee Training and Awareness
Training employees on data handling best practices helps to ensure that sensitive information is handled and stored securely, reducing the risk of data breaches or leaks. The training can help employees understand the importance of data privacy and compliance with regulations, which is essential for maintaining trust with customers and partners. Proper training can also improve overall organizational efficiency and productivity by ensuring that data is effectively managed and utilized.
Examples of data handling best practices for employees –
- Encryption: Ensuring that sensitive data is encrypted when stored or transmitted to prevent unauthorized access.
- Access controls: Implementing strict access controls to limit data access to authorized personnel only.
- Regular training: Providing regular training to employees on data handling policies, procedures, and best practices to keep them informed and up-to-date
- Secure password practices: Encouraging strong, unique passwords and multi-factor authentication to protect access to systems and data.
- Data minimization: Only collecting and retaining data necessary for business purposes and securely disposing of no longer needed data.
- Incident reporting: Establishing clear procedures for employees to report any potential data breaches or security incidents to the appropriate personnel.
- Compliance with regulations: Ensuring that employees are aware of and comply with data protection regulations such as GDPR, HIPAA, or other industry-specific regulations if necessary.
In summary, constructive data management is vital for businesses in 2024. By addressing key challenges such as data security, compliance, governance, and scalable storage, organizations can improve operational efficiency, decision-making, and regulatory compliance in the evolving data landscape.
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