Data gravity: Understanding and managing the force of data congestion
Data gravity is a term that has been gaining attention in recent years as more and more businesses are becoming data-driven. The concept of data gravity is simple yet powerful; it refers to the tendency for data and related applications to congregate in one location, similar to how physical objects with more mass tend to attract objects with less mass.
But how does this concept applies to the world of data and technology? Understanding data gravity can be the key to unlocking the full potential of your data and making strategic decisions that can give your business a competitive edge.
Data gravity is a concept that was first introduced in a blog post by Dave McCrory in 2010, which uses the metaphor of gravity to explain the phenomenon of data and applications congregating in one location. The idea is that as data sets become larger and larger, they become harder to move, similar to how objects with more mass are harder to move due to the force of gravity.
Therefore, the data tends to stay in one place, and other elements, such as processing power and applications, are attracted to the location of the data, similar to how objects are attracted to objects with more mass in gravity. This concept is particularly relevant in the context of big data and data analytics, as the need for powerful processing and analytical tools increases as the data sets grow in size and complexity.
The Data Gravity Index, created by Digital Realty, a data center operator, is a global forecast that measures enterprise data creation’s growing intensity and force. The index is designed to help enterprises identify the best locations to store their data, which becomes increasingly important as the amount of data and activity increases. Digital Realty uses this index to assist companies in finding optimal locations, such as data centers, for their data storage needs.
Dave McCrory, an IT expert, came up with the term data gravity as a way to describe the phenomenon of large amounts of data and related applications congregating in one location, similar to how objects with more mass attract objects with less mass in physics.
According to McCrory, data gravity is becoming more prevalent in the cloud as more businesses move their data and analytics tools to the cloud. He also differentiates between natural data gravity and changes caused by external factors such as legislation, throttling, and pricing, which he refers to as artificial data gravity.
McCrory has also released the Data Gravity Index, a report that measures, quantifies, and predicts the intensity of data gravity for the Forbes Global 2000 Enterprises across different metros and industries. The report includes a formula for data gravity, a methodology based on thousands of attributes of Global 2000 enterprise companies’ presences in each location, and variables for each location.
Data gravity can influence an organization’s cloud strategy in several ways. For example, if an organization has a large amount of data already stored in a specific location, it may be difficult to move that data to a different cloud provider due to the “gravity” of the data in one place. This may make it more difficult for the organization to take advantage of the cost savings and other benefits that can be achieved by using multiple cloud providers.
Additionally, data gravity can also influence where an organization chooses to place its processing power and applications. For example, suppose an organization’s data is stored in a specific location. In that case, it may be more efficient to place the processing power and applications used to analyze the data in that location rather than trying to move the data to a different location.
Enterprise cloud storage is the foundation for a successful remote workforce
Another factor that data gravity can influence on cloud strategy is the decision of choosing where to store the data.
