Small Businesses Can Meet the Challenges of Data Conversion

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!

Scope of Data

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.

Data Sources and Destinations Need to Be Defined

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.

It’s Easy to Get Lost in the Complexity

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:

  • What will business processes be affected by the change?
  • What will the overall transformation look like?
  • What new data inputs can you incorporate to meet the needs of the new system?

Every element of the conversion must be documented and mapped out in detail. This includes the estimated time to implement each change.

Determining Everyone’s Roles

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.

  • Who will be validating the new data?
  • Who will input data into the new system in order to keep the business running?
  • Who needs to be locked out of the system until the conversion is finished?

What Resources Are Required?

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.

Views: 293

Comment

You need to be a member of Codetown to add comments!

Join Codetown

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

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.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Presentation: Challenging Google Analytics: Building a Scalable, Cost-Effective User Tracking Service

Alina Krasavina explains how Delivery Hero successfully deprecated Google Analytics and migrated to an internal user tracking platform. She discusses how a simplistic, highly scalable architecture allowed them to handle 10 times more load while capturing 97% of tracking data.

By Alina Krasavina

Java News Roundup: Spring Tools, Helidon, Open Liberty, TomEE, JobRunr, Hibernate, Commonhaus

This week's Java roundup for June 15th, 2026, features news highlighting: point releases of Spring Tools, Helidon, JobRunr and Gradle; the June 2026 edition of Open Liberty; the first milestone release of Apache TomEE 11.0; the first beta release of Hibernate ORM 8.0; Quarkus emergency maintenance releases to address CVE-2026-50559; and four open-source projects join the Commonhaus Foundation.

By Michael Redlich

Podcast: How eBPF Empowers Developers to Observe Inside the Linux Kernel in a Safe and Unintrusive Way

Dan Fineran explores how eBPF has evolved far beyond its roots in packet filtering into a robust, safe way to extend the Linux kernel. He explains how the eBPF "verifier", the security guardrail, enables implementation of deep observability and networking without the risks of traditional kernel modules or the slow upstreaming process.

By Dan Fineran

Article: Understanding ML Model Poisoning: How It Happens and How to Detect It

In this article, the author explores data poisoning as a threat to machine learning systems, covering techniques such as label flipping, backdoors, clean-label poisoning, and gradient manipulation. The article reviews real-world incidents, discusses the challenges of detecting poisoned data, and presents practical defenses, tools, and operational practices for securing ML training pipelines.

By Igor Maljkovic

AWS Graviton5 Reaches General Availability with 192 Cores and Formally Verified VM Isolation

AWS made Graviton5-powered EC2 M9g and M9gd instances generally available with 192 ARM cores, formally verified VM isolation via the Nitro Isolation Engine, and DDR5-8800 memory. ClickHouse reported 36% better performance with zero code changes. Meta committed tens of millions of cores. On-demand pricing is 9% above Graviton4, translating to roughly 15% better price-performance.

By Steef-Jan Wiggers

© 2026   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service