Data Debunked: The Myths and Truths About File Analysis

Kon Leong is President, CEO and Co-founder of ZL Technologies.

Ideal data management strategies are different for every organization; everyone has his or her own take on the exact definition of what “information governance” is even supposed to be. Full data management has become a very multifaceted business challenge, and analysis tools seem to promise to offer some assistance. However, analytics can’t fix the absence of strategy.

Myths arise because everyone loves a simple explanation. We’re drawn to them because they offer to (seemingly) to streamline the vast and unwieldy. The more complex a topic, the more likely it is that myths will spread. File analysis and file governance are excellent examples of this. With file share environments being the epicenter for human-generated activity within the business, organizations question how file analysis best fits into the data management strategy. However, with such a broad topic, it’s easy to fall into the occasional trap made by an attractive myth. Here are some of the more common ones.

Myth #1: File analysis = information governance. Analysis of a file share environment – in isolation – is not information governance; it is simply a snapshot assessment of content at a given point in time. However, file analysis certainly can be used as part of an overarching information governance program. Increasingly, this is exactly the case with file shares, which have often been neglected in governance efforts. Analysis offers a first step for businesses that simply don’t know where to start with sprawling file environments.

Truth: File analysis is part of information governance. The process of information governance, however, is a journey. The first step will only get you moving. The process that follows the initial analysis – deciding what to do and then doing it – is what pushes the data down the path of information governance. This process, called data remediation, is not an inherent function of most file analysis tools available.

Myth #2: File Analysis will classify, sort and manage data. File analysis alone cannot make business decisions— only the business can. So before initiating a file analysis effort, the organization needs to be clear in determining what the objectives and desired outcomes are. File analysis for file cleanup is like walking into a messy room and creating a detailed list of what’s there; the cleanup process itself isn’t provided by the initial assessment.

Truth: File analysis can be the first step in data management. Most file analysis tools will generate an initial report, but the decisions and heavy-lifting remain. If there is a need to move, discard, re-arrange, classify, or otherwise manage the analyzed files, the organization needs to ensure plans for the next steps have been made. Some file analysis tools offer integration with information governance or records management products, and some existing governance platforms can natively analyze file environments. Make sure the business understands what options exist long before a purchase is made.

Myth #3: File analysis is a one-time task. For many organizations, file analysis IS treated as a one-time project. However, unless something is done with the analyzed content, it becomes necessary to eventually repeat the effort. Just as in our messy room example, file shares are a living ecosystem. There are constantly new items, changes and revisions. If file analysis is used as the first step in a one-time cleanup approach, it’s akin to doing spring-cleaning… and no more cleaning for the rest of the year.

Truth: File analysis (ideally) is an ongoing process. Singular file analysis followed by singular cleanup must become a recurring project in order to maintain control over data. With the right architecture, it’s possible to conduct full-scale analysis of files once, actively categorize data or get rid of it, and then perpetually analyze the changes and activity in order to manage any subsequently modified or created content. In the end, a file analysis project can be conducted once… but it’s likely not what you’re looking for.

Myth #4: File analysis can only analyze metadata. Part of the selection process for a file analysis method or tool is deciding how deep the analysis needs to be in order to achieve desired business objectives. Many file analysis products rely on metadata rather than content. While metadata alone can provide a wealth of critical information commonly used to classify and manage content within a records or governance program, it doesn’t give the full picture.

Truth: File analysis can examine data within documents. Often, the most important data is hidden within document content. Take, for example, sensitive information such as Social Security numbers or financial information. In order to reliably tell if these have been stored within a public file share or other unsafe location, the content of the files need to be assessed. If an organization desires to use file analysis as part of an effort to increase data security, content analysis is critical. It does exist, but the business needs to conduct due diligence to ensure that the tool being purchased offers content capabilities.

Myth #5: File analysis is an IT problem. File analysis, used properly within a comprehensive information governance strategy, is an “everyone problem.” The failure to reign in control of files affects nearly every business unit.

Truth: File analysis is a business strategy issue. While IT teams may be key facilitators in the initial file analysis process, the downstream stakeholders are spread across the organization. End users benefit from increased efficiency of file access and productivity. Legal teams benefit from the defensible removal of junk. Compliance and risk managers benefit from better access controls and protection of sensitive content. And IT, of course, benefits from a more streamlined and secure file environment. File analysis should never be conducted simply because of an IT driver.

The file analysis market offers more options than one might expect, but care is required to ensure that complexity doesn’t muddle decision-making. The trick is fitting file analysis into a comprehensive governance road map. To do so requires not only a deep assessment of business objectives, but also cohesion between business stakeholders.

Recognize the myths of file analysis, and overcome the challenge of information governance.

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