As the amount of data on earth continues to explode, managing it has become more difficult than ever. While gathering data is fairly easy, retrieving it can be a nightmare if your company does not employ the best practices of data retrieval. Ultimately, overlooking this important step in data management can cost your company hundreds of thousands in lost productivity and wasted resources.
Data analysts refer to a healthy body of data as a data lake. Navigable, clean, safe to drink from: a data lake is the ideal environment for your company. But many companies’ lakes end up being data swamps: festering pools of unusable data. How do you know which one your company has? Just look at your data retrieval processes.
5 Signs That Your Data Retrieval Is Inefficient
1. You Have to Access Multiple Databases
The Problem: If you or your workers are constantly scouring multiple databases to put together all the data they need, you have a retrieval problem. This phenomenon occurs when data is created by separate applications or is divided by your company’s structure. We call these data silos, and they can seriously hamper your company’s efficiency.
Data silos can form in a few situations. When different programs create their own data sets, you will need to access them using their respective programs. This makes data retrieval far more laborious. Silos can also develop when multiple departments or branches within your company have their own sets of data.
The Solution: Ensure all your data is indexed in one searchable data lake. Whether your data is located in the cloud, at the edge, on endpoints, or in a combination of these, an effective data management platform should break down silos by indexing your company’s entire data set. You can then capture, manage, retain, and deliver content in one single open platform.
2. You Don’t Know Where Data Is
The Problem: Just like misplacing your car keys, not knowing where your data is will slow down your workday. This frequently occurs when employees determine file organization and folder hierarchies independently. Each person or department has its own approach to organization, making retrieval a pain.
Another common cause is that the people who gather data are not always the same people who need to retrieve and analyze it. When one hand doesn’t know what the other is doing, retrieval slows down.
The Solution: A data intelligence platform can serve as a custom-tailored search engine for your unstructured data. Perform laser-focused searches to find what you need 300% faster, no matter where those files are located.
3. Metadata Is Missing
The Problem: Relevant to the second point, metadata is crucial for optimal data management. Metadata gives information about data itself such as where or when it was produced. Poor data gathering practices can lead to a lack of metadata, making it hard to search for.
Without metadata, your employees’ only option is to search for filenames and hope they were named appropriately. If searching doesn’t produce useful results quickly, you’re going to have retrieval issues on a regular basis.**The Solution:** If you’re missing common metadata fields like date published or author, are there hidden fields that could prove useful in finding the right files? Aparavi’s [data discovery tool](/us/solutions/discovery-automated-classification) searches through 70+ metadata fields and allows you to build custom queries for more advanced metadata searches.
If you still don’t have the information you need to find the right files, a tool that can perform in-file content searches, such as the text contained in a .docx file, can prove extremely useful. The Aparavi Platform gives you more ways to find the files you need when you need them.
4. You Encounter Duplicates or Inconsistent Data
The Problem: Even if you know where your data is and can find it quickly, if you’re running into duplicates of files or data that doesn’t quite match, the retrieval process comes to a screeching halt. Now your data analysts have to determine which file is the correct one before they can proceed.
There are a number of ways that this can occur ranging from bad backup practices to human error. Regardless of how this data comes to be, it needs to be removed if you want to optimize your workflow.
The Solution: Use data intelligence to identify and then either move or defensibly delete ROT (redundant, outdated, or trivial) data. Resolve conflicts between duplicate files, and prevent further duplication of ROT data by breaking down data silos.
5. You Frequently Ask Colleagues for Access
The Problem: Data is often locked behind poorly managed access permissions and server barriers. It can be extremely frustrating when you know exactly what you need and where it is, only to be met with denial due to a lack of access permissions.
Now the entire job is on hold while your employees are emailing others for access or running down the hall to beg IT to let them do their work.
The Solution: An effective data management platform makes it incredibly easy for the right people to find the files they need, regardless of their level of technical expertise. It also allows administrators to control user permissions so your employees can find, access, or modify particular files without disrupting your data or creating noncompliance risks.
How Bad Data Retrieval Costs Your Company
All the retrieval problems we’ve described have an economic impact on your business. However, these costs are mostly hidden and difficult to quantify without a careful analysis. Here are some areas you should scrutinize.
Reduced Employee ProductivityDue to the issues we’ve described, data analysts unfortunately spend very little time analyzing. According to [an IDC study](https://www.itproportal.com/features/study-reveals-how-much-time-is-wasted-on-unsuccessful-or-repeated-data-tasks/#:~:text=The%20IDC%20study%2C%20based%20on,is%20spent%20on%20actual%20analysis.), only 27% of their time goes to actual analysis. Nearly 37% is spent searching for data in the first place.
Considering that an average analyst’s salary exceeds $80,000, that’s about $30,000 wasted per individual. The same IDC study estimates that US organizations waste $1.7M a year per 100 employees on payroll.
Hindered Communication Between Departments
Data silos and access permission problems limit your employees’ ability to communicate and transfer information. A recent Panopto report showed that the average employee wastes 5.3 hours a week just waiting for information from fellow coworkers. If your employees could access each other’s data more efficiently, much of this idle time would be put to better use.
Interestingly, the study also noted that workers will often just recreate data even though they know it already exists somewhere else. Waiting is torture: your employees want to work. Help them do it by tearing down those barriers.
Wasted IT Resources
Sloppy data management also wastes IT resources. Redundant data takes up extra space on servers. Constant transfers of data across departments or cloud storage locations create cloud egress fees, consume network bandwidth, and slow down other processes.
A 2019 study from the European Insight Intelligent Technology Index claims that about 30% of money spent on cloud resources go unutilized, in part because workers are busy managing shoddy data.
An Intelligent Solution
Aparavi’s intelligent data management platform solves all these problems with a single solution. Aparavi scans all your data and unifies it under a single platform, making it easy to add metadata and find duplicates or redundant files. Its powerful search function works by intelligently identifying key details from various files.
Best of all, your entire organization can use it and ensure that everyone works on the same data, rather than creating silos and separate copies. Permissions control is a breeze within the platform. If you would like to know more about how Aparavi can streamline your data, contact Aparavi today to talk with our consultants.