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Traceable Reporting 

For the C-Suite in a Instant

Platform Overview

Data have grown and will continue to grow exponentially. Back in years managing application was a concern rather than data. Data governance was always known to us but what’s the driver for it being so heavily spoken about. The fundamentals of data governance is tractability from the producer to what you report. The impact of micro services with data silo have given us ability to be agile, fast tracking revenue, but have built the complexity around data governance. These days with silos and micro service the mechanism to know what you report can be achieved by creating organization data ecosystem.    

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Spoken across the globe in general but it’s easier said than done. To have solid governance you would need to

  • enable consistency and traceability

  • Reduce regulatory fines

  • Enable Data security

  • Maximize the income generation potential of data

  • Designate accountability for information quality

  • Minimize or eliminating re-work

  • Optimize staff effectiveness

  • Establish process performance baselines to enable improvement efforts

  • Acknowledge and hold all gain

These cannot be achieved by just having a metadata or data process flow in place. Our ecosystem has the right blend to achieve data governance not just by MDM but by enabling process automation, workflow, reporting and custom UX within the ecosystem so every moves is traced, recorded and archive for audit and access rights at time of the event.

Connect Data Virtually

Connecting data virtually enables faster access to data without having to spend time in creating extraction process and making data duplication across the organisation. This reduces one step on data governance by removing tractability requirement between source, middle layer and target. This diversion from traditional approach is beneficial in this era of data driven ecosystem where applications are built using micro service approach.       

Analysis & Process

Virtually connect to data means your analysis is always real time and target in not a middle ware or data warehouse eliminating security concerns of your data in the ecosystem. The access to data remain at the micro service level (silo) but will have relevant functional access for analysis and processes. For example your requirement is to have access to customer model, you can build multiple mode without transferring your data and assign own set of security and control based on the final service you want to provide to end user. This way the data is not ported over outside the source, it is only used for final outcome and archived for audit and compliance. 

Work Flow

You can define workflow based on your internal control. Enabling online authorization not only create audit trail for workflow, it will help you achieve a paperless environment.

Reporting

Our way of looking at data is a system either captures data (source) or data is used to generate some form of report. Everything between is process automation. The best way to keep tractability and govern your data is do not move it anywhere else for reporting, make it readable rather than portable. The platform allows you to produce an outcome based on your business process keeping all relevant information used for the report including business rules and each manipulation steps.

User Defined UX

With application these days narrowing down product positioning, any process will have some form of user interaction to bind them together for a greater business outcome. This is where the platform allows to give you the biggest mileage to custom fit your full cycle without compromising data governance.  

Risk & Compliance 

By using our ecosystem that virtually connect data with capabilities of middle layer, process, workflow and reporting, your risk to data distortion and requirement to clean your data is significantly reduced. The fundamentals of our platform are as follows

  • Don’t port data

  • End to End process automation taking snapshot of data and manipulation steps for future references and audit.

  • In case of data requirement for AI and analytics, the data must have single point of processing keeping tractability confined – Training based silo. AI/ML models work when you train them with correct data.      

Security & Privacy

All process will virtually connect to the applications for a final business out comes. This makes sure that security and privacy is controlled at source and with the end to end business process outcome (mutually inclusive) taking all you other concerns regarding data breach out of the way