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fingers crossed, we need to first create a complete and reliable single source of truth of data for the ecosystem and then push it to the ultimate data lake, so data can rest in peace.
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Get browser notifications for breaking news, live events, and exclusive reporting.Take a data-first approach. Once we realize the importance of these data management products, we should redesign them with a data-first approach. Although they're data products, they shouldn't be built with only a workflow-centric approach in mind, in which effort is purely put into making a better user interface with some element of machine learning. The data that currently goes into and comes out of these systems isn't typically used effectively because the systems are often built on a weak data backbone. We should reinvent these products by ensuring that the data capture, storage, processing and distribution happen in the most effective manner with impeccable data lineage and easy data governance. As an example, data reconciliation is one of the most important processes in any organization. The quality of data that goes into reconciliation platforms is usually top-notch and what comes out is fully reconciled data: the single source of truth. Do we harvest it? Do we use this source for regulatory, client and financial reporting? Often, the answer is "no."fingers crossed, we need to first create a complete and reliable single source of truth of data for the ecosystem and then push it to the ultimate data lake, so data can rest in peace.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
4. Consider distributed ledger technology. Distributed ledger technology (DLT; i.e., blockchain) can process, store and distribute data with effective traceability and immutability. We can use DLT to build an enterprise data backbone to manage all the data life cycle events. DLT can help make data lineage, data ownership and data governance easier and facilitate building a federated and collaborative model of data management. It can also allow multiple data sources to contribute to data management, instead of relying only on a centralized data management platform.
We've spent enough time and energy building new data infrastructure, big data stores for aggregating data and moving the often costly infrastructure to the cloud waiting for the magic to happen. It's time to take a step back and look at the basics of our data management products—to reimagine, rethink and reinvent them so the data in motion can be effectively harvested. Rather than sending data from multiple platforms in the business ecosystem to the data lake and keeping ourfingers crossed, we need to first create a complete and reliable single source of truth of data for the ecosystem and then push it to the ultimate data lake, so data can rest in peace.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
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