In today’s tech-driven environment, data collection and analysis are critical for businesses to extract valuable insights and make informed decisions. With so much reliance on data, the vital need to efficiently manage and handle it also arises. Data management helps align your tasks, processes, and outcomes across departments. It makes your business infrastructure smarter, enhances operational efficiency, and provides accurate and timely information to stakeholders. Well-managed data helps in optimal resource allocation, formulation of actionable strategies, and improved communication and teamwork.
This makes investing in a robust data management strategy essential for 2024! But how do you begin carving out a flexible and reliable plan? Here are a few practices to adopt that will help you manage and maximize the value of your data at its fullest!
1. Get rid of unstructured data
Your data management plan should begin with structuring the data collected through multiple sources. For instance, your company collects custom feedback regarding a new product launch through numerous channels like emails, social media polls, online surveys, forms, and so on. The input might contain results such as text comments, numerical format, or images. As this data lacks a standardized format, it is essential to structure it to make it easy to understand and analyze.
Depending upon the type and purpose of data, you can use various data structures that simplify your data organization, data retrieving, and data processing services. For instance, you can use Linear data structures where each element is sequentially connected to its predecessor and successor. It includes arrays, stacks, linked lists, queues, and vectors for easy data structuring and management.
2. Invest in a centralized data repository
Having a 360-degree perspective on all your business metrics is essential to understanding market trends, competitor tactics, and customer behavior. And for this, you need an inflow of data from multiple sources. One must practice effective data management to store this data, collected from various sources, in a central data repository. The data warehouse will provide a complete picture of your company and help authorized employees access valuable data from one source.
A centralized repository helps in data standardization and reduces instances of data duplication. It helps maintain high-quality information and eliminates discrepancies for more reliable, accurate, and efficient results. Storing data in a central warehouse also lets you implement robust encryption protocols and access control to protect sensitive information from breaches or unauthorized access.
3. Leverage advanced automation and AI tools
As data volumes and complexities grow each day, manual methods of data management have become obsolete. You can use advanced automation and AI tools for:
- Data collection: Automation can help you in the data collection process to get timely, streamlined, and accurate data as and when needed. For instance, you can use Robotic Process Automation (RPA) to automate your firm’s repetitive tasks like data entry, cleansing, and validation. This frees up valuable resources and time that can be used in core value-added tasks.
- Asset or equipment maintenance: AI algorithms and IoT sensors are being utilized across industries to extend the lifespan of equipment or assets and reduce downtime. With the help of AI tools, you can monitor the real-time performance of your assets, schedule timely maintenance, and reduce the chances of potential failures before any mishap.
- Data governance: AI tools are designed to detect, classify, and tag sensitive information, monitor access permissions, and find potential risks that may lead to data loss or breaches. Data governance, driven by AI tools, ensures that your organization maintains compliance with data security standards and safeguards the information efficiently.
4. Create data backup and design a disaster recovery plan
While creating your data management strategy, a critical practice is building a reliable data backup and recovery plan.
The risk of data loss in hardware failure, cyber-attacks, human errors, or any other mishap can only be avoided with regular data backups. You must store the backup copies of your data in at least three locations: cloud st, such as in-office servers, and off-site storage. Implement ‘versioning’ to safeguard different updated versions. For instance, you edit a document containing customer emails and accidentally delete a few entries. You can find and locate the original file and restore the deleted data if multiple versions are saved.
Strategize with the team and create data Recovery Time Objective (RTO) and data Recovery Point Objective (RPO) metrics. RTO defines the maximum time a company requires to restore its normal functioning after data loss. RPO defines the maximum amount of data loss your company can tolerate. These metrics work as a guiding force when you plan your disaster recovery strategies. Based on your business needs and lessons learned from past mistakes, constantly test and update your recovery plans for a prompt response during future mishaps.
5. Monitor and upgrade data management processes
Your data management plan must be constantly monitored and updated to keep it relevant, secure, and reliable. Technological evolutions introduce new tools and methodologies that you must use to manage your data more efficiently. With strict laws like the California Privacy Rights Act (CPRA), businesses must adapt to regulatory changes by continuously upgrading their systems. You should conduct regular audits and assessments to identify discrepancies and find areas of improvement. Update your data governance policy, implement robust encryption solutions, and keep your data management processes current.
Keep a check on your data storage and processing systems, detect areas of inefficiency, find and delete unwanted data, and enrich your data with up-to-date information. If any of these tasks require more space, you must focus on investing in a scalable data infrastructure that can handle exponentially growing data volumes.
Manage your data with the help of service providers
While creating a reliable data management roadmap looks easy, implementing it is hectic and time-consuming! If you also find it challenging to efficiently manage, analyze, enrich, and implement valuable data in your day-to-day function, professional data processing services might help you! Outsourcing such tasks to a skilled team can help you save time and resources while keeping your data management plan aligned with the industry standards.
