ARMY AL&T
LOGISTICS FOR DATA
Get ting bat tlefield data to the right place at the right time: The mess versus the mesh.
by Thom Hawkins and Andrew Orechovesky Part Two of a three-part series. T
he Great Library of Alexandria, which flourished in Egypt during the Ptolemaic dynasty of the third and second centuries B.C.E., took any manuscripts found on ships that docked in its port, copied them, and then returned the copies to the ship while retaining the originals. Viewing an original and a copy as interchangeable relies on the notion that the parchment’s information provides the value, not its medium—a giant step forward toward our modern, digital world.
While the first entry in this series (“Logistics for Data,” Army AL&T Fall 2023) discusses the demand signal for data, this entry will focus on inventory and warehousing of data. Making use of a physical resource, like an ancient parchment or a shiny new case of ammunition, requires geographic co-loca- tion and a limit on the number of simultaneous users. In contrast, an unlimited number of people can use a digital resource remotely at the same time. Even still, as we discuss in this article, the library is an apt metaphor, and ties data to the same physical logistics as something like ammunition.
DATA STORAGE Army logisticians seeking to replenish a unit’s ammunition must know where the ammunition is stored and have access to view the current inventory, specifically the desired items. Te same applies to data (e.g., tactical or strategic data products) stored in a data repository, or “data platform.”
Te location of where data is used has evolved in recent years. A structured database, often referred to as a “data warehouse,” is co-located with the application that uses that data. Tis is inefficient because the same data may be needed by different systems, but each system may have its own source or frequency of update, resulting in the potential for discrepancies. Databases can use a process called federation to create links that synchronize those data points. However, this can lead to chaotic and disorganized connections that databases cannot maintain, especially as applications change.
From data warehouses, industry’s response to the limitations of data warehouses was data lakes, which are a common pool of raw data, only structured or federated as needed to serve set purposes. Data lakes have their own set of limitations, including the potential for disparate or conflicting sources of data. More recently, data fabric, which acts as a common data warehouse, has gained popularity. Instead of assigning each application a database with its own data, all applications rely on data in the common
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