How to Tackle Slack Data Collection Challenges – Arrow Translation Explains

With the continuous evolution of e-discovery (electronic discovery), new data sources are emerging at a rapid pace. Breakthrough platforms like Slack have introduced significant challenges in terms of evidence collection. As a highly flexible instant messaging and group chat platform, Slack has experienced explosive growth in recent years. The platform allows users to chat, send and store files, and integrate data from other sources. This high level of functionality creates significant obstacles for e-discovery experts when attempting to collect and review Slack data.

While Slack is extremely popular as a workplace communication tool, many litigation professionals are unfamiliar with the platform and the potential responsive data within it. As businesses rapidly transition to new communication paradigms, the impact on litigation—especially e-discovery—has been profound. Thus, collecting, reviewing, and producing Slack data has become a frequent need in e-discovery, especially in international litigation or compliance reviews. Translation companies may also be involved in such efforts, assisting in the translation of relevant documents or helping collect and review files.

Here are some options for retrieving data from this emerging platform:

1) Export Directly from Slack

This is referred to as Slack's "Standard Export," which only exports messages and files from public channels. For all users, this is a useful (and free) feature, but its utility in discovery and review is limited. The exported public messages are provided in JSON format, which is not very user-friendly for large-scale reviews. Additionally, exports generate a JSON file for each day that a channel is active, which could result in hundreds of files per channel. Attachments are provided via links in the JSON file, and litigation support teams would need to retrieve potentially relevant attachments, adding extra steps to the workflow.

2) Compliance Plan

If the standard export is not viable, Slack offers a compliance plan for "Plus" customers, which allows the collection of data from private channels, direct messages, and group chats. However, the compliance plan only includes data generated after the feature has been enabled. Public channel data is still exported through the standard export, but historical data from private channels, direct messages, and group messages need to be retrieved via other methods.

3) Discovery API

If there is no compliance plan, data from private channels, direct messages, and group messages can be obtained through the discovery API. This feature allows the collection of data from users' public channels, user identities, and users' direct message contents.

4) Third-Party Archiving

A more recent functionality involves third-party archiving systems. Platforms like Smarsh are excellent for retrieving traditional data types (such as emails) and have now added Slack as a data source. However, the key issue lies in how the archived data is exported for review.

5) Onna

Onna is a data collection and management platform capable of collecting data from Slack and other platforms. It connects to Slack’s user API and enterprise grid, allowing users to select specific channels, direct messages, and group messages. You can specify a date range, and Onna will collect and process the content. The result is a comprehensive, native file that can be reviewed on any platform.

In addition to having a solid data collection strategy, having an efficient and cost-effective review process is equally important. Slack’s standard or compliance export data is typically in JSON format, which is often converted into CSV format for review. Although the discovery API offers a richer data set, it does not enhance review functionality.

From my experience, Onna is the best option for collecting, processing, and reviewing Slack data. When Onna collects data, it processes and prepares the export, combining multiple stages of the traditional EDRM (Electronic Discovery Reference Model). This approach helps save time and costs by running these tasks concurrently. Onna provides significant flexibility, allowing users to filter or search for specific keywords and export either all synchronized data or just targeted data. Once the data is identified for export, it is added to a load file that can be directly imported into review platforms like Relativity. This allows users to convert a set of loose JSON files into a highly organized load file, which can then be uploaded directly to the review platform. All essential features can then be applied to the Slack data set. Onna's advantages in simplifying the collection, processing, and review processes place it ahead of the competition, making it a leader in how to review Slack data in the industry.

The Key Role of the Translation Industry

In international litigation or compliance reviews, translation companies play a crucial role, especially when it comes to cross-border data. Translation companies are not only responsible for providing accurate document translations but may also need to assist with handling and reviewing electronic documents from platforms like Slack. To ensure the accuracy and compliance of document content, the involvement of translation services becomes increasingly important.

Arrow Translation provides professional support in this regard, helping ensure that language barriers do not hinder the e-discovery and data review process. With the growing prevalence of platforms like Slack in business environments, understanding their data collection and review processes has become critical. Whether for international litigation cases or daily data compliance requirements, selecting the right tools and methods will make your data collection, processing, and review efforts more efficient and convenient.

In the e-discovery field, Arrow Translation is here to partner with you, offering precise, efficient translation and data support services to ensure the smooth progress of your work.

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