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White Paper
Handling Too Much Data and Finding Too Little Information Strategies for Managing the Unintended Consequences of Data-Driven Organizations
Date: 05/18/2018 Length: 10 pages Cost: $99.00

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Abstract:
Organizations that already adopted data-driven strategies are going to find, establish, and maintain competitive advantage over traditional rivals in competing marketplaces. They will develop new markets and opportunities that traditional enterprises will have difficulty capitalizing. Yet, opportunity costs come with the value of data-driven initiatives.

Few organizations can effectively construct and operate the supporting environments that data-driven strategies demand. Internet-focused organizations have certain advantages in their technology-oriented cultures and presence of digitally-native data sources. Whether it is in terms of modern data center infrastructure for on-premises deployments, or virtual private clouds, or utilizing public cloud resources, the CIOs and IT departments of data-driven organizations are oriented toward supporting, deploying, and staffing complex data landscapes. Many traditional companies, and even some startups in Internet-focused markets, have difficulty handling the data necessary for data-driven strategies.

Even for organizations that can manage data collection and storage, there are issues with the proper utilization of the data. It is one thing to collect a mass of data from IoT devices or mobile apps; it is another to prepare and correlate the data to compare the actions of a customer on a smartphone with their brick-and-mortar purchase history. This management, curation, and operational execution is crucial to making the proper targeted offers to customers and prospects at the correct time.

Finally, as data is collected and correlated, it needs to be curated as an asset. Understanding data quality and the association of data to relevant customer, product, or location domains is part of managing customer relationships and product portfolios. Creating enterprise catalogs of the data and metadata across a landscape can be a significant challenge for organizations whose primary goal is manufacturing or supply chain distribution. Yet, this is a key component in the ability for organizations to evaluate and value their data as an asset, meet requirements for internal risk controls, and meet compliance for governmental regulation.
Author:

John Myers, Former EMA Analyst


 




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