With newer advancements arriving in the marketplace, data sciences are currently burgeoning with innovation and opportunities. Modern tech companies have made use of these newer methods of data management to make better decisions in order to maximize the growth of their business.
But, the intrinsic fallacies associated with conventional data management systems like a data lake and a data warehouse keep firms from fully realizing the potential of data analysis and its implications. The introduction of a data hub aims to change that around for the better. So, what exactly is a data hub and how does it fare against its less advanced counterparts?
What is a data hub?
According to formal sources, “A data hub isn’t a technology, but rather an approach to more effectively determine where, when and for whom data needs to be mediated, shared and then linked and/or persisted”. At its heart, a data hub is an amalgamation of three different ideas- Data Warehousing, Data Engineering, and Data Sciences. In simple terms, a data hub is a data storage system that aims to connect the creators of the data with the vendors of the same. It allows for a seamless transition between the multiple stakeholders who are vested in the process of decision-making.
How does a data hub function?
A data hub aims to create an environment that enables the hassle-free transfer of data between the different factions working in a company. After the successful integration of the data hub, each user agrees to execute a user agreement providing the operator full reign over the data collected.
The data collected is frequently stored in a central repository where it’s subjected to in-depth analysis. These analytical measures help in transforming meaningless data into insightful takeaways for businesses. After this modification, data is pushed to the operators for them to make the right data-backed decisions.
How does a data hub differ from a data lake and a data warehouse?
A data lake and a data warehouse are some of the relatively newer methods of data procurement and management but are riddled with faults. The data hub manages to surpass its predecessors with an array of advantages like minimal data latency, the ability to handle varied data sources, and more importantly, its relative ease for newer tools like machine learning and artificial intelligence to be integrated.
What are the advantages of a data hub?
While real-time data integration is at the core of a data hub, there are a couple more advantages that merit a mention. Some of them include:
Safer platform
A lot of companies prefer their ground-level employees to have access to only a limited amount of information regarding their firm and the services they provide. Data hub architecture allows this structure to function, despite having a shared central data repository. This hierarchical sharing of information reduces the chances of a potential data breach and leakage of extremely sensitive information. A malicious event might tarnish the reputation of the firm, once and for all.
This principle can be better understood by citing an example. So, here a tech start-up that focuses on data security is taken into consideration. For the sake of safeguarding the interests of their customers, the company in question may withhold access to sensitive information to freshers who’re just starting work or to those individuals that work below a certain rung of the established hierarchy.
Better decision-making
Since decisions are rooted heavily in data sciences, they tend to be geared towards maximizing the growth of the business. A data hub, thanks to its seamless transfer of data to all of its concerned stakeholders, cut down on the instances where a decision-maker has to go fishing for important facts or key statistics. All of the important data sets are made available to the operators who are tasked with identifying the most practical solution to a problem at hand and then implementing it.
Rapid scalability
The biggest advantage of integrating a data hub into one’s business is that it allows for rapid scalability. Unlike conventional systems of data management, the entire layout need not be reworked when a company needs to scale rapidly in case of a data hub. A firm can focus on acquiring the necessary human resources since the existing technological infrastructure should suffice.
Conclusion
A data hub is a newer system of data procurement and analysis that looks to improve on its predecessors like a data lake or a data warehouse. It aims to build a central data repository that can be accessed by all, hence contributing to faster and more impactful data-driven decision-making. This lays the foundation for companies to scale up rapidly to comprehensively consolidate market share. In addition, a data hub also affords more security, minimizing the chances of sensitive data getting compromised with the reputation of the firm taking a bad hit.
