Six Concepts for Effective Data Conversion

Now That the Secret is Out, Remember These Six Concepts for Effective Data Conversion

By: Doug Kaminski
Chief Revenue Officer, Cobra Legal Solutions

Last time, I discussed the eDiscovery service that nobody talks about – Data Conversion – and three common scenarios where it may be needed to support discovery.  But that’s only half the story.  The other half is understanding how to manage it effectively, as failure to do so can derail your entire eDiscovery project. So, here are six concepts and best practices for effective data conversion, gleaned from our experience performing hundreds of data conversions for clients:

  1. Define and Communicate the Scope: Do you drive somewhere you’ve never been before without a roadmap (or, these days, a navigation app) to tell you how to get there? Of course not.  You can’t get to your destination until you know where you’re going.  It’s important to define what “done” is and what a successfully converted data set looks like (including how it should be able to be used by the destination platform, if applicable).  This includes defining any business rules to support the ability to convert the data consistently and reliably.  Then, communicate that definition of “done” among the team so that everyone is using the same roadmap, er, navigation app to get to the correct destination.
  2. Protect the Data: Protecting the data includes making sure a copy of the data is secure before conversion, so you should always backup the data you’re converting before you begin, as you may need to recover back to the primary state of the data several times as you QC the data conversion process. It also includes protecting the data during transmission between platforms using industry-established protocols.
  3. Understand the Data: You can’t effectively convert data to support the use cases we discussed last time without understanding the data and how it’s stored. Do you understand what a DAT file is?  How about a CSV, LFP, OPT or DII?  Each of these are a type of load file format that defines how data is categorized within the load file and, even in the age of automation, load files remain a key component of transferring data from point A to point B and understanding the data you have on the other end.  Do you know what delimiters are?  They are a way of understanding when each data element begins and ends within a load file.  These are the example of the concepts you need to understand when it comes to data conversion and migration.
  4. Understand the Technology: Not only that, but you also need to understand the technology as well. Even when the source and destination data will both be within the same database management system (e.g., SQL Server), converting and/or migrating that data often isn’t as straightforward as it seems.  Different versions of SQL Server have different attributes, so a later version of SQL Server may not be compatible with an earlier version unless it’s set to a compatibility level that supports that earlier version.  Understanding the nuances of the technology is key to being able to move the data, even when it seems like a “no brainer”.
  5. Make it Repeatable: Many data conversion initiatives are created to support migrating similar data again and again, so it’s important to make the process consumable. Data process mapping is key to making the data conversion process repeatable.  Trust the process, while evolving the process as needed to make sure it’s as efficient as possible.  Even data sources that seem difficult such as Teams and Slack have repeatable playbooks we can follow to help ensure success.
  6. Quality is Job 1: Being from Detroit, I always go back to the old marketing tagline from the Ford Motor Company and it’s worth keeping in mind as you ensure an accurate and successful data conversion. Quality assurance (QA) and quality control (QC) mechanisms must be defined and utilized to ensure the accuracy of the converted data.  You can’t define what “done” is without defining what will be done to ensure the quality of the converted data.

Conclusion

Successful data conversion projects don’t just happen – they require best practices and the skills and knowledge – including project management skills, experience working with data and an understanding of technology – to know how to implement those best practices to prepare data for use within various phases of the eDiscovery life cycle.  Data conversion may seem to be the big eDiscovery secret that nobody talks about, but eDiscovery experts understand that data conversion is essential to the success of an eDiscovery project overall.  We talk about it all the time!

For more information about Cobra’s Technology services (including database and data conversion services), click here.

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