Featured Product
This Week in Quality Digest Live
Management Features
Dirk Dusharme @ Quality Digest
Retailers that don’t use technology to streamline operations will lose business
Knowledge at Wharton
Create, communicate, and implement the change. Then let employees self-lead.
Karla Jo Helms
How innovators can mitigate the status quo pushback
Sachin Waiker
A study of motorcycle makers shows how focusing on one market for too long can reduce companies’ ability to survive
Gleb Tsipursky
Videoconferences are ill-suited for traditional brainstorming. Try this method instead.

More Features

Management News
Eiger Fleet to enable more control and automation of distributed manufacturing
Is the future of quality management actually business management?
Sept. 16, 2021, at the Duke Energy Center in downtown Cincinnati
Morse has a long history with the center, both as a faculty researcher and for serving as the center's deputy director since 2010
Siemens introduces PCBflow, a secure, cloud-based solution for accelerating design-to-manufacturing handoff for printed circuit boards
Includes global overview and new additive manufacturing section
Tech aggravation can lead to issues with employee engagement, customer experience, and business results
Harnessing the forces that drive your organizations success

More News

Gary Lyng

Management

Big Data Storage Costs: What You Don’t Know Can Cost You

Is your organization maximizing its big data investments?

Published: Wednesday, August 4, 2021 - 12:03

To uncover the value in data, analysts need powerful combinations of tools to locate data, wherever they are, and regardless if they are structured or unstructured. Most companies don’t realize that their current data-search approaches can’t access distributed information and can’t extract information within unstructured documents. This severely limits their ability to translate data into profit.

How does big data search and retrieval work?

Traditionally, when you think of search-and-retrieval tools, you picture a search tool that lets you find data based on the parameters you define. This is certainly the case; however, it shouldn’t be the only thing your retrieval tools and process can do, or else your data management—and analysis—will be severely deficient.

Search tools are useful for finding specific files or data, but they won’t reveal anything else unless you ask for it specifically. Although that sounds like a streamlined process, it excludes other data hidden on your across-distributed-data infrastructure. What about those misnamed files that you’ll never find?

If your tool can’t do much more than retrieve data and put it back, then you don’t have a clear picture of the data in your organization. When you don’t have deep understanding of your data, problems can fester below the surface, driving up your data costs and, more important, burying valuable data in a heap of unsearchable clutter.

Storage costs and avoidance

Data are created at such a high volume that many IT executives don’t know what to do with them. In fact, far too many executives likely have no idea how their company’s data are stored, whether they have been replicated, or what the company’s internal data-management practices are.

Add in the fact that data storage has never been more affordable, and it’s no wonder why so many companies have decided to add more storage when they run up against their limit. But this is like buying a bigger closet instead of just cleaning out the one you have.

Part of the problem is that basic search tools can’t discover data. Like a SEAL Team on a mission, basic search tools avoid any and all distractions, bringing back their target with no regard for the rest of your data. You need a recon team to give you a clear picture of your whole file system.

Picture a powerful, automated search and classification tool that examines every inch of your file system and reports back on what it found. It can be asked to retrieve any data that haven’t been accessed in ages and find those hidden data that your regular retrieval system can’t. With that knowledge, you can keep your storage costs down.

Compliance risk

Companies ignoring data management by adhering to inadequate search software could put themselves at regulatory compliance risk. Strict data laws in the European Union, as well as in the United States, particularly in California and Virginia, put the legal burden of managing consumer data squarely on the shoulders of companies. If legally protected data accidentally—or nefariously—leak, the company can be liable for significant fines.

Another important data-management aspect for compliance risk is how companies internally process data subject access requests (DSAR). Any California-based consumer has the right, under the California Consumer Privacy Act (CCPA), to access their personal data. This includes requesting information on stored data and requesting information about the data safeguards the organization provides.

If your retrieval system doesn't reveal hidden data or help you find sensitive information in unstructured files, then you can’t secure that information. Cyber and ransomware attacks are on the rise, and the cost of a data breach can be staggering.

Labor expenses

Uncluttering terabytes of data takes a significant amount of time, and simply hiring more data managers and analysts may not be the most efficient approach. Internal data-management practices and processes must change if the goal is to identify and locate all company data, mitigate risk, reduce cost, and create value.

Like adding storage, adding analysts alone won’t boost a company’s efficiency or solve any underlying data management issues.

The cost of lost opportunities

Data management experts note that just counting the hard costs overlooks other hidden costs your data impose on your business. If your data are poorly prepared, your business intelligence might fail to deliver the insights you need to make smart decisions. Not knowing your data can cost you in potential profits.

Discuss

About The Author

Gary Lyng’s picture

Gary Lyng

Gary Lyng is the CMO of Aparavi, the leading data intelligence and automation software and services company that helps companies find and unlock the value of data—no matter where it lives. Aparavi’s SaaS platform finds, automates, governs, and indexes distributed data. Aparavi ensures secure access for modern data demand of analytics, machine learning, and collaboration.