Data gravity refers to the fact the fact that information has the potential to be an appealing force with the potential to draw more kinds of information, data developers companies, and even applications.
In this post, I’ll take a look at the underlying principles of data gravity, and how they are applicable to enterprise data strategies.
Principles of gravity of data
Data has a magical nature to it. Doesn’t it? It can be described in a variety of ways. Every person has something to comment on it. Every person can utilize it in different ways. (You can use blue paint and create a myriad of things using it.) Each individual has something they want to speak about it–what it’s intended to do, what it’s best to use it for, what its function is, and how important it may be, the fact remains that it is. Data lies in the middle of the notion.
Data gravity is a study of data. It examines data and reveals two fundamental concepts:
The larger data sets have more mass and greater impact. There is more talk about it.
The information contained in the NSA documents Edward Snowden released was significant in its own right however, because it was a large amount of data–ranging from 9,000 to 10,000 documents–it was more prominently scrutinized. It is likely that had it been a single file or even 100 of them, the information would appear less important, and there could be a way for the NSA as well as the Federal Government to dodge it and the public could be able to forget about the information. The fact that it was extensive and comprehensive piece of work made it more appealing.
If more information is available about a topic, that subject will remain in the public eye.
If an artist such as Ryan McGinley is able to show only few photos to showcase his work, the public are able to dismiss it quickly. If Ryan owns thousands of professionally developed Polaroid images of same New York City subject matter His collection of data points can draw more interest. He is elevated from being a photographer to an individual who is obsessed and a person who has something to say.
Information in workplaces: Use cases
Businesses have always been known to gather as much information as is possible, without consciously responding to the data gravity. It doesn’t matter if they had a specific reason to collect this or not. The general sentiment was, “The more, the more enjoyable.” The companies in question were not aware of their response to the gravity of data.
Although the greater the better argument is open to discussion (one we don’t have) however, it’s an actual fact that companies are able to utilize data to:
More efficient service
Naturally, the more data Netflix has about its customers more it is able to recommend and produce videos for the user. In the world of service it’s standard to greet people by name, inquire whether they’re doing well and to remember their favourite meals. The server is more appealing. The service becomes more individual.
This type of information retrieval, also known as collection could be effective for personal communication as well as the personal touch the service industry demands. However, for services that are tech-enabled it is important to scrutinize the information these services gather regarding their users of tiers.
Increase your offerings
With more information Google is able to provide new services. If Google is focused on capturing street-view images and satellite images It can broaden the scope of its products beyond Search Engine to Search Engine and GPS service.
Rethink your product offering completely
If your company is stuck and you need to solve it, you could utilize the data as a basis for the creation of an entirely new business.
Let’s imagine that Netflix decides to take Hulu out of its video streaming services and no one wants to shell out money for Hulu to stream any more. If that happens, Hulu does not sit on the sidelines of nothing important. It holds a wealth of information regarding viewers’ viewing habits, and their views which must be useful to some one. Hulu could come up with an innovative service with the information it has amassed or…
If that fails then sell the the data to be an asset
Data is available for sale to other companies. Data is a resource and people who have it may be able to utilize it better than a business. Your neighbor or Picasso can buy paint at the same price but the way they choose in using it will result in totally different outcomes.
Data attracts more data
1. Larger collections of data are more massive and have a greater impact. People are more likely to talk about it.
As the data bodies expand new services are attracted to them. Data bodies grow through:
- The pooling of other data sources
- Connections with other bodies of data
The data bodies that exist have already completed the hard work and are now ready for users to access or contribute to. The concept is that once there is a database and is being used, more data flow towards it. If there is libraries of the work of Henry Miller, it is likely to receive more donations of Miller’s work.
Data bodies that are pooled
One company that is autonomous has been collecting for four years data from its sensors in order to find speed limit signs so that they be aware of the speed limit. Another company has been collecting photos of pedestrians in crosswalks so that they be aware of pedestrians crossing the road. The two data sets could collide to create a larger collection of data, which creates one algorithm which can be able to know how fast it is and prevent hitting people who are crossing streets.
Connectivity is growing
By using an API and an API, the data is made available to be used by the general public. Developers are able to use the data, and advance it to develop apps. They can integrate it with other data sources to develop services.
For instance an example, an example is that a Wells Fargo API tied to the weather API can provide a user with their expense for rainy days.
With the power of greatness comes the responsibility of a great leader.
Principle 2. If more information is available regarding a subject, the subject may be kept alive in the public eye.
Museums are there for two reasons they serve as a means to preserve physical data (the arts) and because the people believed it was crucial to provide access to the data. It is the norm in our society that with a huge amount of data, it’s seen as an obligation for this data to be accessible to the public for free or with restricted access.
Another principle that is a part of data gravity has an important connotation: the more information you own, the greater the responsibility you are entrusted to the data. Big data sets include:
- More difficult to move
- It is more difficult to protect
- More difficult to supply
What are these challenges for your storage of your data, data security and API service?
As we begin to recognize the forces around data and the potential value data has, they have to take on the responsibility for both good and evil which are entailed by the saying, “The more data, the better.”