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Data in Banking: 3 Newest Advancements Evolving Data Communities

Exploring Advancements for Teams in Data Collection and Data Utilization Approaches for Financial Ecosystems


Data communities are networks of engaged data users within an organization—represent a way for businesses to create conditions where people can immerse themselves in the language of data, encouraging data literacy and fueling excitement around data and analytics.


What’s New with Data Collection-Utilization Approaches Seeping into Financial Ecosystems?

‘Web 3.0’ was originally coined as the Semantic Web by Tim Berners-Lee, the Web’s original inventor. It is an extension of the World Wide Web through standards set by the World Wide Web Consortium, being called semantic because of its all-linking web-like nature.


The most fundamental goal of the Semantic Web is to make internet data machine-readable and easily interpretable by the vast number of computation devices out there.


What’s New? Blockchains have become the foundation for the storage of all validated information that web 3.0 needs to become what it wishes to be. In a blockchain, information is validated by multiple contributors, making it impractical, and almost impossible to hack or manipulate information.


Termed the most secure data storage method to date, Blockchain is versatile and vast ecosystems can be created to suit specifications.


Redefined Digital Connectivity: Evolution of the Internet into a Safe Space


New world internet is based on updated digital safety norms for sensitive data, where the concept of web 3.0 will now let the internet benefit from being –

  • Open as its underlying infrastructures will now be built from open-source software by an open and accessible community of developers and executed in full view of the world.

  • Trustless as the network in itself allows everyone to interact publicly or privately without a trusted third party.

  • Permissionless as both users and suppliers are participating without authorization from a governing body.

Couple this with banking, and we see a revolutionary partnership brewing. For new-age finance, Application Programming Interfaces (APIs) connect different applications built with different programming software. To reimagine banking, APIs promote a connected ecosystem with shared data sources built with blockchain for the trusted processing of customer and transaction data.


A merger of APIs and Web 3.0 is what has come to be known as open banking and is being built on blockchain ecosystems to enhance digital banking with A-grade security.

Naturally, for traditional banks, the competition with internet-based banking services is intensifying.


More Data, Increased Data Diversity Drive Advances in Processing and the Rise of Edge Computing


It may come as a little surprise that the pace of data generation continues to accelerate. In the financial services industry alone, the amount of data generated each second grew by over 700% in 2021.


Upwards of 90% of an organization's unstructured data goes unprocessed, according to analyst firm IDC. Non-database sources will continue to be the dominant generators of data, in turn forcing organizations to re-examine their needs for data processing. Voice assistants and IoT devices, in particular, are driving a rapid ramp-up in big data management need across industries, including finance.


The use of devices for distributed processing is embodied in the concept of edge computing, which shifts the processing load to the devices themselves before the data is sent to the servers. Edge computing optimizes performance and storage by reducing the need for data to flow through networks, reducing computing and processing costs, especially cloud storage, bandwidth, and processing expenses.


Edge computing helps to speed up data analysis and provides faster responses to the user.


The emergence of DataOps and Data Stewardship for fluid data-sharing practices, and challenges in managing data over its lifecycle


One area of advancement is the emergence of DataOps, a methodology, and practice that focuses on agile, iterative approaches for dealing with the full lifecycle of data as it flows through the organization. Rather than thinking about data in a piecemeal fashion with separate people dealing with data generation, storage, transportation, processing, and management, DataOps processes and frameworks address organizational needs across the data lifecycle from generation to archiving.


Due to widespread security breaches, eroding customer trust in enterprise data-sharing practices, and challenges in managing data over its lifecycle, organizations are becoming much more involved in data stewardship and working harder to properly secure and manage data, especially as it crosses international boundaries.


New tools are emerging to make sure that data stays where it needs to stay, is secured at rest and in motion, and is appropriately tracked over its lifecycle.


If you're interested in learning more about the latest data collection and utilization approaches in the financial ecosystem, then connect with D2K's banking fintech experts who can guide you through the complexities of this exciting and rapidly evolving landscape.


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