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Is Big Data Dangerous? 3 Common-Sense Data Management Guidelines

Data is a crucial driver of value for most businesses today. But when managed improperly, data can become more of a liability than a benefit. Keep reading for tips on creating a data management strategy that helps, rather than hurts, your company.

No matter which industry your business is in, it almost certainly relies on data to a significant extent. These days, you don’t have to be a big bank or an insurance company to live and breathe data.

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You could also be, for example, a fast-food restaurant that relies on data-driven systems for ordering supplies and paying employees. You could be a construction contractor who uses data to help price bids. You could be an ice cream parlor that collects and analyzes data to determine which flavors to offer.

In all of these examples, data plays a key role in keeping the business operating normally and profitably — assuming that the data is well managed. Poorly managed data can not only undercut your ability to drive meaningful insights, it can also create extra costs and legal risks that lead to threats to your business’s overall stability.

When that happens, your data ceases to be a boon for your business, and it becomes a danger instead.

Building a Healthy Data Management Strategy


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That is why crafting a data management strategy that controls for the risks associated with data at your business is essential for using data wisely.

A data management strategy is your overall plan for storing, transforming, integrating, analyzing and archiving the data that your business collects. It applies to all types of data: Machine data from IT infrastructure, manually collected data like customer records, sales transaction data and much more.

When designing a data management strategy, you’ll want to take the following factors into account in order to ensure that your strategy is efficient and appropriate for your business needs:

  1. Compliance. Increasingly, compliance frameworks like the GDPR are imposing government regulations on the way data must be stored, managed and secured. It’s crucial to identify which regulatory requirements apply to your company based on its location and industry and make sure that your data management strategy can meet those requirements.
  2. SLAs. Service Level Agreements, or SLAs, are contractual guarantees that mandate that you provide a certain level of availability for your applications or services. SLAs typically involve more than just data availability, but because data availability is an important part of overall availability, you want to ensure that your data management strategy allows you to meet any SLA guarantees that you provide. SLAs are especially important if your business is the type that has a lot of external contracts and customers; they may be less important if your applications and infrastructure are used only internally.
  3. Cost. The portion of your budget that you devote to data management will vary widely depending on factors such as the size of your infrastructure and whether you use commercial or open source data tools. In any case, however, keeping data management costs in check is important for protecting the overall financial health of your business. To control data management costs, consider questions such as how much it costs you to back up data, and how many backups you can afford without breaking the budget, for example. For another example, think about the time spent transforming data before it is usable, and whether decreasing that time using automated data transformation tools can help reduce your overall data management costs.

A data management strategy that is designed to address these needs will help to ensure that data continues to drive business value, rather than creating unnecessary business risks. This goal will only become more important as the amount of data your business collects and analyzes continues to grow.

Make sure to download our eBook, “The New Rules for Your Data Landscape“, and take a look at the rules that are transforming the relationship between business and IT.

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