From Silos To Synergy: Real-time Data Sharing Across Eco-systems In Real Time

By Author: Frame Outlook
Total Articles: 17
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Despite advancements in data management technologies in recent years, the ability to get true potential of business data continues to evolve. From cumbersome batch processing to complex data formatting and transformations, sharing data across diverse systems and tech stacks is anything but easy or in real time.

This is one (of many!) reasons why we’re starting to see event-driven data automation tools revolutionize how businesses leverage data, especially when it comes to collaborating with strategic business partners and other external parties.

This article investigates common hurdles associated with traditional data sharing, highlighting the benefits of event-driven data automation for multi-party data exchange.

Data-sharing bottlenecks: Time to clear the path

Today’s data-driven economy demands agile data sharing, and relying solely on internal data is no longer sufficient. But while third-party data is essential for personalized experiences, fraud prevention, and lots more, current data-sharing mechanisms often fall short when it comes to exchanging information across diverse systems.

Historically, ...
... data exchange is primarily conducted through two methods:

Network data loads: Meticulously formatted data (e.g., CSV files) is transferred in batches between different systems. However, this static approach limits data updates to daily cycles at most, leading to information delays and stale business insights.
Online data platforms: While online platforms like CDPs, data lakes, and warehouses offer some potential for data sharing, the reality is that incompatible data stacks frequently create obstacles, requiring significant data formatting and transformation efforts.

Both methods present additional challenges as well. Batch processing is inflexible, making it difficult to accommodate real-time operational or market fluctuations. Transferring large datasets also carries significant security risks, potentially exposing sensitive information. Plus, incompatibility between data stacks can create silos across systems and companies, blocking business leaders from gaining a clear, comprehensive view of information for decision making.

These limitations translate to a host of real-world business challenges, such as:

Downstream disruption: Batch processing in industries such as financial services often leads to delays and lost opportunities. For example, payroll deposits arriving outside designated processing windows can disrupt downstream systems, causing customer frustration and potential financial hardship.

Increased operational costs: The complexities of data transformation and heightened security measures associated with traditional methods drive up costs. In manufacturing and retail, a lack of real-time data visibility exacerbates issues like inventory mismatches, inaccurate demand forecasts, and reactive replenishment strategies, all of which inflate operational expenses.

Poor customer experiences: Customers also face friction when businesses lack real-time data. For example, if a global airline doesn’t have access to up-to-date information, its customers may face limited flight or seating options or missed opportunities on using their miles for upgrades.

Heightened fraud risk: Across industries, delayed detection of fraudulent activities due to batch processing can also increase an organization’s exposure to financial losses.

A new paradigm: Secure, event-driven data sharing

Event-driven data automation is revolutionizing how businesses harness the power of data. End-to-end data automation platforms like Vendia act as a secure intermediary between mixed tech stacks (often with different database solutions), unlocking real-time data sharing.

This means that organizations can instantly analyze data, uncovering previously hidden opportunities and driving proactive strategies faster.

Here's how it breaks the mold:

Event-driven architecture: Data is immediately shared any time a predefined event occurs, eliminating the need for batch processing and ensuring information across business systems is always up-to-date.

Secure direct data transfer: Data moves directly between parties through secure connections, minimizing the attack surface and reducing the risk of exposure during transit.

Read More: https://www.thecioera.com/from-silos-to-synergy--real-time-data-sharing-across-eco-systems-in-real-time/

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