Did you know that your data has a temperature?
It’s true.
However, that temperature has nothing to do with Fahrenheit or Celsius, or even how healthy your data is. The “temperature” of your data refers to two things:
- How soon after the data is created it is used, transformed, or processed
- How it’s stored
The temperature references for data were initially developed when data location and the type of physical storage space being used were often the limiting factors to being able to quickly access and use data.
Data that needed to be accessed immediately was typically stored in a data center located near where the processing took place so that data access times were reduced. Data that was not needed as frequently was typically stored off site, which would take longer to access but reduced the cost of storage. However, in the digital era, traditional file storage systems have been replaced with newer, more efficient file systems and virtual storage, so data access times based on location have been significantly reduced.
Today, data is separated into temperature categories based on the level of criticality for a business. The more critical the data is to the business operation, the more frequently the data is accessed and the hotter the data temperature. As such, there are three categories used to classify data – hot, warm, and cold.
Let’s take a brief look at each of these.
Data categories
Since hot data often needs to be instantly accessible, another critical issue is the speed at which the data can be accessed. That’s why today, hot data is often stored in the cloud, where availability and accessibility is typically well above 99.9%. Data latency is another critical issue for hot data, so the closer to the source the data processing takes place the better.
An example of hot data is data used for real-time decision-making for online transactions in a retail environment. Another example is telemetry data captured from a satellite that is then used for computations.
Warm data refers to data accessed within a relatively short period of time after being created, or data accessed on a fairly regular basis. Unlike hot data, warm data is not typically transferred to another location, so it may even be archived when it is not in use. Note that the period of time defined as short will be different for each company and will depend on the usage; there is not an industry standard.
Cold data refers to data that has been created, but is accessed rarely or infrequently, so it doesn’t need to be immediately available. Cold data is generally older data that is not active or up to date, so latency is another issue that is not as critical when accessing this data.
An example of cold data are compliance records that may only need to be accessed annually for end of year reporting. Another example are records about projects that have been completed but may need to be referred to at some point in the future.
Data categories may be further refined by implementing policy-driven procedures that determine how long data will stay in one category before being moved to the next. This data categorization process helps ensure that only the data required in each category is available.
Data storage
In addition to the data categories, the other component for determining the temperature of your data is how it is stored. This determination is important because the type of storage used directly impacts the data accessibility and its ability to be transformed.
The type of data storage used is strictly up to the business based on their unique data access requirements, but some general recommendations are discussed below.
Hot data storage – Because this type of data needs to be immediately available and accessible, whether for processing or transfer, it requires short access times with no latency issues. Data storage typically used for this category includes cloud storage with solid-state drives optimized for accessibility and low latency. Another option may be a storage area network (SAN) located near where the data processing will take place.
Warm data storge – This data type is accessed within a relatively short period of time after being created or is data that is accessed on a fairly regular basis. Data storage for this type of data may include NAS drives or cloud storage.
Cold data storage – data of this type is not accessed on a regular basis, so it does not need to be immediately accessible. This data can be located offsite in a data warehouse. Because access and latency are not critical, this type of data storage often uses a storage medium such as a tape drive or hard drives.
Why categorize data?
As you have seen, each of the three categories of data indicates the timeframe in which the data will be accessed (immediate, short-term, long-term) and processed. Knowing how data will be used in your business will make the assignment of the correct category easy.
Why is it important to assign data to the proper category?
Because if your data is not correctly categorized, access to the data may be compromised, which could impact your business. In today’s digital economy, data is the new lifeblood of business and is what drives insight and innovation. It’s what provides product teams with direction for new product development. It’s what informs the business. Ensuring access to that data is a mission-critical step.
If your data isn’t categorized correctly, it may be stored incorrectly or routed incorrectly, leading to delays in access, delays in processing, and not being able to derive the insights and information from the data when your business needs them. Incorrectly categorized data also can impact your business financially.
Access your data with HPE Ezmeral Data Fabric
One last point is that data is often located in numerous silos throughout a business. Being able to consolidate and access that data through a single data management platform that spans edge to cloud and unifies different data types into a single logical data store is critical to your business. HPE Ezmeral Data Fabric provides that capability. To learn more, visit the HPE Ezmeral Data Fabric webpage or contact your local sales rep.
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RichardHatheway
Richard Hatheway is a technology industry veteran with more than 20 years of experience in multiple industries, including computers, oil and gas, energy, smart grid, cyber security, networking and telecommunications. At Hewlett Packard Enterprise, Richard focuses on GTM activities for HPE Ezmeral Software.