1. What is Cloud Gravity in Data?
  2. How to go about Cloud Gravity in data?
  3. Importance of Cloud Gravity in Enterprises
  4. Problems with Cloud Gravity in Data
  5. How to deal with Cloud Gravity In data

1. What is Cloud Gravity in Data?

Imagine a situation where you are working with a data extensive application, and you need to transfer that application to one of your colleagues for further improvement. This movement of data to the one you want might become cumbersome and expensive. This effect is named Data Gravity. Data gravity is basically a metaphor used to denote the tediousness or difficulties faced while dealing with the situation.

The term Data Gravity was coined or given by Dave McCrory. Cloud Gravity in data can also be inferred from the term gravity, where data becomes heavier, and due to gravity, it becomes difficult to move data from source to destination. Usually, in order to solve this issue, cloud storage services such as Dropbox or Google Drive is used.

2. How to go about Cloud Gravity in data?

The primary step is to get an architecture around the scale-out NAS platform, which enables data integration/consolidation. The platform should support a wide variety of traditional and next-gen workloads and applications that were previously used for different types of storage. With the help of this platform in place, one is positioned to manage the data in a single place and bring all the applications and processing power to the data.

3. Importance of Cloud Gravity in Enterprises

In order to make sure the information the organization provides is accurate, latest, and relevant, The data must be managed by the organization in an effective manner.

Not following the policies, rules, and procedures of the engagement, the huge quantity of data sets in the data house or another dataset might become uncontrollable. in a worst-case scenario, it might become good for nothing. Application owners might go back to using the data which they own in order to make decisions, leading to non-useful decisions made for a single and multi-owned application. 

Data integration gets affected to a greater extent because of Cloud gravity in data, especially when we try to unify the systems and reduce the resources wasted because of errors. 

4. Problems with Cloud Gravity in Data

1) Latency- Latency, as the name suggests, the time taken for the data to travel from source to destination. It’s natural that a large set of data would require its application to be close. i.e.in, in its orbit, but if that is not true, there is a higher chance that the user would have to face latency issues.

Speed is essentially critical for successful business operations, and an increase in latency due to data’s gravity increases is simply not a bearable option. The enterprise should need to ensure that both the output and workload balance out with the data’s gravity.  That means moving applications to the same area so that latency can be minimised and to increase the work output.

2) Lacks Portability– It’s quite evident from above that the data gravity increases the size of the data sets. And the larger the data set, the more it is difficult to move the data from source to its destination.

It is quite a tedious job for the organisations to migrate their data sets as there is continual growth in the organization’s data sets and becomes heavier with the passage of time. Hence Data Gravity affects the businesses at large. 

5. How to deal with Cloud Gravity In data

Data gravity is a reality that is quite logical. The best way to deal with Data Gravity is by proper Data Management, Governance and Integration.

Managing the Data- we know the importance of management in an organisation. Thus that is too important while dealing with a whole lot of data. Data management usually includes the decisions on whether to store data on cloud-based data storage services or to use an on-premise application to keep a record of all the organisation’s data.

Governance of Data- Data governance is the core element of Data Management. As the name suggests, data governance plays the role of responsibility and accountability in regard to the data. This is a function that is responsible for overcoming the issues faced due to Data Gravity and other similar issues.

Integration of Data- Data integration, as the name suggests consolidating the whole data in one place and increasing the applications and systems’ productivity.

Conclusion

After going through the above-mentioned information, it is quite evident that how Data Gravity affects businesses’ data storage. As we are getting advanced with the ever-evolving technology, we are facing new challenges too. But as we are humans, we try to find solutions for almost each and every issue we face. Talking about the basic idea about Data Gravity is that the main drawback that a user faces with data gravity includes the need for less proximity of the source and the destination. The greater would be the distance or weight, and the greater would be the time it would take to complete the specified job.

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