Codetown ::: a software developer's community
Implementing new data systems is a difficult process sometimes. New systems result in some amazing benefits including improved processes and the ability to access data more easily, but they are also going to need data to be converted to a format that can be used in the new system. This is a challenge that small businesses must face. This post will look at 5 challenges of data conversion to ensure that you are prepared to conquer them!
The first step is to define the scope of the data to determine how much of it needs to be converted. You’ll likely find that some of it is essentially useless so there is no need to convert that. Make a list and double check it. How much data is being converted? How much of this data must be converted manually? Determining the scope of data that needs to be converted is a critical step because it allows you to create a plan of action.
Now you will have to determine exactly where the data is coming from. Are you pulling it from different databases or have you consolidated everything into a single database? You must clearly define the source.
Once you know the source, identify the destination for the data. This will determine exactly what type of conversion is necessary. In some cases, there might be more than one destination so you’ll need to identify what data goes into specific destinations. Write all of this down.
There is so much data that is accumulated by a business that it’s easy to get lost in a sea of raw data. The sheer intimidation of all this data is what leads to many entrepreneurs to procrastinate updating their systems. They simply don’t want to deal with all of this data conversion.
However, there is a way to face this challenge – data mapping. This is seen by many experts as an essential step to successful data conversion. Detail the requirements for each element of data within the conversion. You’ll have a list by this point to help make this easier. Define all of the following details:
Every element of the conversion must be documented and mapped out in detail. This includes the estimated time to implement each change.
This is another challenge that can become a major bottleneck in the overall conversion of data. I’ve seen companies forget to define everyone’s roles during the conversion so they all do their own thing, resulting in an even bigger mess. It’s essential that you detail every team member’s roles before you begin the data conversion process.
Finally, you’ll have to make a list of every resource required throughout the data conversion process. Develop a full plan of action from beginning to end including development, testing, and validating new data. Then make sure that you review this plan in detail with all associates involved.
Keeping your systems up-to-date is important because the business world continues to grow at a record pace. If you can meet all of the challenges in this post, then you will find that it’s not quite as intimidating as you believed.
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.

Dropbox reduced its backend monorepo from 87GB to 20GB by optimizing Git delta compression in collaboration with GitHub. The changes improved clone times, CI performance, and developer velocity, highlighting how repository storage inefficiencies can impact large-scale engineering workflows.
By Leela Kumili
The panelists share insights on evolving company culture. They discuss leveraging feedback loops, lending social capital, and the friction between legacy bureaucracy and agile engineering. The panel explains how to maintain cohesion in remote teams and use interviews to uncover the true "unmanicured" culture of a firm.
By Nicky Wrightson, Suhail Patel, Lesley Cordero, Matthew Card, Natan Žabkar Nordberg
Cloudflare has released Sandboxes and Containers into general availability, providing persistent isolated Linux environments for AI agent workloads. New capabilities include secure credential injection via egress proxy, PTY terminal support, persistent code interpreters, filesystem watching, and snapshot-based session recovery. Active CPU pricing charges only for used cycles.
By Steef-Jan Wiggers
Sovereign fault domains are failure boundaries defined by legal, political, or physical jurisdiction rather than hardware topology. The article maps geopolitical events to known distributed-systems failure modes, argues multi-region should replace multi-AZ as the HA baseline for systems crossing jurisdictions, and outlines design patterns, chaos experiments, and an ALE model to justify the spend.
By Rohan Vardhan
Cloudflare has outlined a reference architecture for scaling Model Context Protocol (MCP) deployments across the enterprise, positioning centralized governance, remote server infrastructure, and cost controls as key requirements for production-ready agent systems.
By Matt Foster
© 2026 Created by Michael Levin.
Powered by
You need to be a member of Codetown to add comments!
Join Codetown