The data ecosystem serving today’s modern enterprises is a multi-platform architecture that attempts to embrace a variety of heterogeneous data sources. This modern data ecosystem (MDE) might include data lakes, traditional data warehouses, SaaS deployments and other cloud-based systems, data hubs, and distributed databases.
Reality of Modern Enterprise
The MDEs can potentially enable a wide variety of business goals as well as support data diversity, optimize costs, and support multiple systems of insight. However, MDEs will never be able to deliver these benefits unless enterprises can surmount a series of formidable challenges:
Data ownership. Who owns the data and with whom can it be shared?
Integration and unification. How will disparate data be integrated and unified to support reporting and analysis across the entire portfolio?
Data quality risks. How will an enterprise ensure adequate data quality given that different data systems will be characterized by different levels of data quality?
Skillset scarcity. How will an enterprise fulfill the need for a diverse set of skills?
Optimization issues. How will an enterprise optimize the interaction among MDE’s, separate, poorly orchestrated components?
Multiple data models. How will an enterprise work with multiple data models that proliferate, reducing efficiency?
Holistic view. How will an enterprise establish a sustainable method for gaining …
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