Data Management Strategies: 3 Battle-Tested Pointers
What does effective data management look like in practice? Keep reading for a discuss of three best practices that are essential for building an effective data management strategy.
Data management refers to the way you collect, store, migrate, transform, analyze and archive data. It involves all types of data, from machine-generated data like logs to manually input user data.
Effective data management is crucial for transforming your data into value. Data on its own is not very useful, but data that is effectively managed can drive critical business insights. Data management also helps in areas such as optimizing user experience.
While the specific processes and tools that your organization uses for data management will depend on your individual needs, be sure to consider the following three best practices when designing your management strategy.
Assess Data Management Needs Realistically
The gap between what you would do with data in a perfect world, and what you can achieve with your limited resources, is often immense. At the same time, it can be easy to underestimate data management requirements, in which case you run the risk of building a solution that is not adequate for your organization.
That’s why it is important to step back and make a realistic assessment of your data management needs. A realistic assessment means determining which level of data management is sufficient for addressing your needs.
For example, you’ll want to assess your data backup needs realistically. You may not have the resources to do hourly backups. But neither should you assume that weekly backups are enough. Instead, determine how much data you could afford to lose during a failure, and plan a backup strategy accordingly.
Similarly, you should assess how many errors you can tolerate in your datasets. Do you need data that is nearly perfect, or can you accept some inconsistencies without undercutting the accuracy of your insights? Decide the answers to these questions and set up data quality tools accordingly.
Integrate Data Management Best Practices into IT Governance
Your data management strategy should not be an island. It should fall cleanly within the framework of your organization’s broader data governance strategy, which should, in turn, be part of your overall IT governance plan.
Making data management best practices part and parcel of your broader IT governance strategy is important because ultimately, the purpose of data management is to drive other IT processes. Data can help your developers determine how to design and implement the next generation of your business’s software applications, for example. It can also help your IT operations department ensure that it has the storage and bandwidth capacity necessary to meet data management needs.
Integrate People, Tools and Processes Effectively
The best data collection or transformation tools are of little use if you lack a consistent process for using them, for example. And no data management process will proceed smoothly if it is not built upon the right tools.
It’s not just tools and processes that matter. People are an important part of the equation, too. Who will identify, implement and manage the tools that factor into your data management strategy? Who will be responsible for monitoring the processes, addressing issues as they arise and periodically evaluating overall progress in order to determine how to improve your tools and processes?
The bottom line: You need a data management plan that combines people, tools, and processes effectively. Each of these things needs the other two in order to work effectively.
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