Data management: Accelerating change in agile solutions

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Data management: Accelerating change in agile solutions and analytics

Data management agility has become one of the topmost priorities for organizations in an increasingly complex, and diverse environment. Maintaining a solid grip on rapidly growing amounts of data scattered across private and public clouds requires an innovative and secure system approach. The emerging design concept called “Plug and Play” can be a robust solution to ever-evolving data management challenges such as low-value, high-cost data integration cycles and event-driven data sharing.
Data management: Accelerating change in agile solutions and analytics
What is Data management?

What is Data management?

Data is considered the enterprises’ most enduring and valuable asset, employed as the foundation for digital transformation and strategy. A data management solution uses a systematic approach to deliver throughput to handle up to several million messages per hour using simple parameter settings. The insight supports re-engineered decision-making, providing more valuable information through rapid access than traditional data integration practices.

Think of data management as a self-driving individual

Let’s take two scenarios. In the first case, the driver is quite sluggish, quickly gets distracted, and pays less attention to traffic regulations. However, the vehicle has a semi-autonomous mode that holds the potential to make the course corrections whenever needed to curtail any chaotic situation.

In the second case, the driver is quite proactive and pays full attention to every granular detail, route, and traffic signal. Therefore, the car’s autonomous element has minimum or no intervention in the driving cycle.
Think of data management as a self-driving individual
Both types of cases define how data management solution works. It properly monitors the data pipelines as a passive guardian and then starts addressing all the needs of internal departments, compliance groups, counterparties, and customers.

When both kinds of data ”drivers” are comfortable with repeated scenarios, it exchanges data (message, file, document) while allowing secure access for visibility and control. It also factors accountability, governance, integration, and reporting protocols and procedures while leaving the leadership free to focus on innovation.

How can leaders ensure a data governance solution that delivers business value?

Leaders should quest for a solid technology base, evaluate the existing data management tools, and identify the requisite core capabilities of the solution to deliver business value through data management.

Below shared are vital pillars of a data management solution:
What is Data management?

No 1. Gathers and analyses all forms of data

Data comes in across different platforms, and legacy systems are not compatible. While you need to combine some of it to run your analysis, this is not a simple task to be done. There should be a mechanism like a systematic approach that enables data management solutions to connect, identify, and analyse data. Eventually, automate end-to-end processing of messages from connectivity to delivery.

No 2. Convert passive details to active data

Enterprises need to activate a robust data management hub for frictionless data sharing. For this to happen, the data hub should:
 
  • Stay in command of your data at all times with complete visibility and control using a series of dashboards.
  • Establish connectivity with any number of source systems and external entities instantly.
  • Eliminate the need to generate millions of processing code lines that result in low-performance service.
  • No 3. A robust data integration spine

    Data management should be compatible with diverse data delivery styles, including but not limited to SWIFT, Core-banking, OMS, and CRMs. It should also provide context for messages and related data elements, including approvals, notes, stages, user interactions, documents attached, acknowledgments, and reference data.

    Why should you consider IMS in this new data Governance generation?

    IMS Data Governance is a custodian of enterprise transaction data that helps organizations and society deal with radical uncertainty, disruptive change, and opportunities. It stores all incoming and outgoing data (messages, files and documents) with the objective that data arriving via each connection channel qualifies against filters and compliance data relevant to each channel.


    While sharing the data across different platforms, anything can go wrong at any stage. That doesn’t mean you have to look everywhere to know what went wrong. 

    Enable rapid reporting and analytics of Data Management with IMS Data Governance:

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