Data continues to grow exponentially and shows no signs of slowing down, with IDC forecasting that the global datasphere will reach 175 zettabytes by 2025 (that’s 175 trillion gigabytes)! In addition, IDC found that 80% of corporate data is unstructured. According to one study, 95% of businesses stated that they need to manage unstructured data. Although data can be your company’s most valuable asset, it can also be a major headache if you don’t know how to manage it.
Data Management Control in 4 Steps
If you find that your company’s unstructured data is getting out of hand, then it’s time to reevaluate how you manage it. It all starts with an analysis of how your data is being created and stored. From there, you can start to clean up ROT (redundant, obsolete or trivial) data and map all your information to one central location.
1. Take Stock of Your Data Situation
How do you know if you have a data management problem? Do your workers spend more time searching for files and organizing them than actually using them? Do you frequently find useless or outdated data alongside the information you actually need? Is there a lack of clear protocol for how to handle data in the first place?
If you’ve answered yes to any of those questions, then you need to stop and evaluate your data situation. Where is your data stored? Who is using it? How much is being produced on a daily basis? These questions will guide your new data management procedures.
This process, however, can be quite labor-intensive. How can your IT department go through terabytes of files in a cost effective manner? Not only is it a waste of time; it is a waste of valuable corporate resources. This is where an automated data governance system like Aparavi can save you both time and money. The Aparavi Platform can analyze your unstructured data and help you understand the breadth of your data dilemma.
2. Identify Data Sources
Every program you use likely has its own data set. Different departments in your company use programs that best suit their work. In the end, this creates data silos, wherein one department of your company cannot see or access the data from another.
These silos stifle productivity and slow down communication between areas of your enterprise. In order to manage your data better, you need a clear understanding of where the data is coming from. You can’t break down silos if you don’t know where they are.
Employees that gather or produce data are also a common source of data confusion. Two departments may sort their data differently. Even different branches of the same company may fail to follow the same protocols. Training mitigates this to an extent, but it cannot rule out the possibility of employee error.
The best solution is to take the human element out of the equation as much as possible. Intelligent, automated data management through a powerful platform like Aparavi can do just that.
3. Find and Remove ROT Data
ROT data refers to data that is redundant, outdated, or trivial. This data is just a waste of space and needs to be defensibly deleted as soon as possible, to minimize costs and risks. Let’s look at how each one can affect your business operations:
Redundancies most often occur when individuals work on local copies of data stored on company servers. Many workers still have the bad habit of dragging a file to their desktop to work on it. Redundant data consumes unnecessary resources, as it takes up space on your machines. In addition, it can create continuity errors when the same file has been duplicated and worked on separately.
With an intelligent system indexing your data, you can immediately identify redundant data and send it straight to the recycle bin or a cheaper storage tier.
Outdated data tends to result from excessive backups. Although backups are a critical component of any data strategy, having too many will take up valuable storage capacity. Old data that hasn’t been touched in years is a good candidate for either deletion or transfer to cheaper archive storage.
The process of identifying outdated data and offloading it from servers is expedited when an automated system is implemented.
Trivial data is harder to quantify than the other types of ROT data we’ve mentioned. What makes data trivial? Generally, trivial data is that which has no value to the operations of the company.
Most commonly, this data is created by employees who take notes or screenshots related to a particular job. Proxy files for images or videos are also good examples, as these no longer serve a purpose once the final file has been compiled. These files can add up to form a significant burden on your business.
4. Index Data in One Searchable Platform
With ROT data gone and a clear picture of how your data is currently developing, you can start to consolidate your data under one roof. Your IT department should develop a roadmap of how they intend to integrate the data from various silos and prevent new ones from forming. Protocols need to be implemented for employees to follow.
Ideally, all of your employees should be working from a central location, manipulating a single file to avoid redundancies. Trivial data can be discarded once it is no longer needed, and an archival schedule will ensure that backups don’t become unwieldy.
The fastest way to achieve mastery over your data to reduce costs and leverage information is to use a platform that indexes everything for you. The Aparavi Platform provides a solution that will analyze all of your data across all of your sources. It finds ROT and helps you eliminate it. Employees from all departments can search for files freely and securely. Essentially, it takes all these keys and opens the door for you.
If you need to get a grip on your data, contact Aparavi to find out how our intelligent data governance platform can solve your data problems.