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The pace of the creation of data has climbed at such an exceptional pace that it is expected to exceed 180 zettabytes by 2025. So, it’s all the more important that firms operating online possess a robust data aggregation and management system. One of the recent advancements in the world of data sciences is a data mesh. So, what exactly is a data mesh and why are more and more companies opting for it instead of traditional options?
What is a Data Mesh?
Data Mesh, in the simplest of terms, is a radical approach towards data aggregation that aims to create a unified data architecture for easier management of large amounts of data. It essentially provides its users to access data without having to go through the hassle of navigating through a data lake or a data warehouse. A data lake and a data warehouse are the two main pillars of the analytical data plane. A data lake is associated with data science proper, while the latter is concerned with analytical datasets and business intelligence.
The objective of a data mesh architecture is to obviate the logistical challenges involved with ensuring data availability. It accomplishes this by ensuring uninhibited access to data scientists and business professionals alike. Ultimately, data mesh provides tech firms with an opportunity to make their data more available, within reach of all sections of workers.
What are the issues inherent to the existing data management system?
Before one can understand the benefits of a data mesh architecture, it’s important to be aware of the challenges posed by the existing data management services. So, what are some of the issues that are attributed to an ineffective and outdated data management portal?
- A lot of the firms still continue to make use of a centralized system to manage large amounts of data. While this system makes it easier to procure data from different sources, they will need to be transported across from their locations to a central repository like a data lake. The requested data will need to be exported from here to the site where the query was raised. This extra step makes the process more laborious and time-consuming.
- Data being created at such an alarming pace necessitates the existing data pipelines to handle more data than they possibly can handle. After a point, they fail to respond to a said query as the number of source points starts to multiply. As a result, the response time takes a hit, adversely affecting business agility.
- Since the existing models require a fair bit of data transportation, they run into the risk of being subjected to stringent data migration guidelines while transferring data from across geographical borders. Data transport regulations might be a real headache to deal with, eating into valuable time and resources. This step again slows down firms and puts them at the risk of falling behind their rivals.
How does a data mesh tackle these issues?
Data mesh aims to confront these problems, head-on by the creation of a decentralized data management system. It aims to divide responsibilities to the different domains who would each be responsible for ensuring the safety and quality of their respective data sets. With unprecedented access to data, companies are hence in a better position to make critical decisions regarding their business.
What are the advantages of adopting a data mesh system?
Now that one has a basic understanding of what a data mesh is and what it aims to do, grasping its advantages should be much easier. Some of the benefits of signing up for a data mesh system include:
1) Increased business agility
Since a data mesh architecture is designed to decentralize the process of data processing, firms need not wait for data to be transferred to a central repository like a data lake. This accounts for improved business agility and allows owners to scale their business rather effectively. Moreover, a data mesh architecture reduces data latency, thus contributing to better performance, whether it be live streaming or intensive online gaming.
2) Better transparency
Yet another issue with a centralized form of data ownership is the lack of transparency among the various teams of individuals involved. There also isn’t a safety net in place in case data was to be breached in certain unfortunate circumstances. A data mesh architecture is built on the principles of a decentralized form of data ownership. This system delegates ownership across multiple domain teams, thus accounting for better transparency. A newer method of managing data, like this, also ensures accountability as well, with individual domains responsible for their own operations.
3) Faster access to data
With data mesh, companies need not have to deal with international data migration guidelines that differ from one part of the globe to another. It thus ensures a hassle-free experience for technological firms that have massive amounts of data spread across the world. Moreover, data mesh offers an airtight infrastructure that prides itself on accurate data delivery.
4) More flexibility
Companies adopting a data mesh architecture are starting to realize that they can make use of multiple data platforms to store and process data. This affords such firms some much-needed flexibility and independence.
5) Secure platform
Data security is one of the biggest concerns for a lot of up-and-coming companies. A data mesh system minimizes the risk of a data breach. It accomplishes this thanks to a secure decentralized framework that clocks in queries where the data is housed, as opposed to a public network where the threats of hackers loom large.
Conclusion
Data mesh is a recent advancement in the field of data sciences that aims to create a decentralized form of data ownership. This new and improved system of data aggregation and management cuts down on time wasted on the transfer of data to a central data lake before they can be accessed. A crucial step like this getting circumvented leads to reduced data latency and improved business agility for the business. Firms are also on the receiving end of a sophisticated framework that eliminates the possibility of a data breach while improving transparency among those involved. Therefore, it should as come as no surprise that more and more companies are shifting to a data mesh from a traditional centralized system.
