Before the cloud, companies created and stored data by department, but that approach built data silos that made it difficult to share knowledge. When accounting needed information on a marketing campaign, they had to ask marketing for the information. Then, accounting waited until someone in marketing sent them the data. If the data wasn’t complete, the process repeated, and the inefficiencies continued.
Perpetuating data silos results in more than inefficiencies. They can:
- Limit available data
- Threaten data integrity
- Waste resources
- Discourage collaboration
- Weaken security
As markets become more competitive, organizations need to remove all obstacles to success. That includes eliminating data silos.
Making business decisions is difficult. Making those decisions without data is merely guessing. Without complete data, decisions could prove disastrous. For example, suppose the sales department is sponsoring a special event for potential customers. They’ve checked all the boxes, but there are more people than food on the day of the event. What happened?
Each sales region was responsible for providing a headcount. When the final number of attendees tabulated, the last-minute RSVPs were overlooked. The information was stored in a different location from the rest of the attendees. Because the data was not available, the sales department ran out of finger food. Not the best way to impress a group of potential customers.
Eliminating silos would allow an enterprise search engine to retrieve all pertinent information so the mismatch of food and people need not occur. Organizations need to remove silos before moving data to the cloud. Creating an organizational plan for moving on-premise data to the cloud can make data more accessible across an enterprise.
Inconsistencies in data make it difficult for employees to know which copy of the information is the most accurate. For some industries, the lack of integrity is frustrating and inefficient. For others, it can be far more serious. What happens if medical records are spread over several silos based upon the services received?
Patients change their addresses. The updated information is entered into the primary care physician’s database. The new addresses are added to laboratory records but not radiology. Patients may not remember which departments need the information, especially if they haven’t used the services for several years. When a search is conducted for a patient’s records, radiology records are not included because the patient’s data is not a match.
Removing silos increases the quality of information that can be provided. When moving existing data to the cloud, it’s vital to ensure a single source of truth. Taking the time to validate the information before moving is better than having to sort it out after.
How many people need access to the same data? How many times does one person download the same file? Suppose an employee wants to analyze some data in a spreadsheet. The data is downloaded, saved locally, and then analyzed. If a company’s standard procedure is to back up every workstation at the end of the day, the downloaded file is now stored locally, backed up to the server, and residing on the initial server. That’s three copies of the same file. Multiply that by 100s of employees downloading 10s of files every day. It doesn’t take long for storage to fill up.
Moving the same process to the cloud wastes resources as well. There may not be more storage devices, but there will be cloud storage. Again, developing processes that minimize duplication of information helps data integrity and reduces storage costs.
Easy access to information across the enterprise means fewer obstacles to employee collaboration. Think about the people in accounting who had to wait for marketing information to complete their analysis. If the information were available to everyone, accounting could retrieve the information and then collaborate with marketing to provide a more complete analysis.
As more companies move towards digital transformation, collaboration becomes essential to its success. If data access reflects siloed organizations, the transformation will be challenging to achieve. When it’s difficult to share information, employees will stop trying to collaborate because they do not have the tools to be successful.
Using the cloud doesn’t automatically create a collaborative environment and digital transformation. Data storage has to reflect a different way of accessing data. When data is available across the enterprise, more tools that use machine learning or other technologies can be implemented, making it easier for organizations to transform. As companies plan out their cloud storage, they need to ensure that data is accessible not only for employees but also for technologies such as conversational AI chatbots or RPA solutions.
If data does not fall under an overarching security plan, vulnerabilities can creep in. Updates are not systematically applied to all databases, leaving gaps for hackers to leverage. In some instances, credential authentication is not applied equally across all silos, making it easier for data to be stolen. If employees have to remember different usernames and passwords for various databases, most will use the same credentials to access all files. That means that stolen credentials can expose an organization’s entire digital assets to cybercriminals.
Careful consideration of cloud security can minimize the risk of a data breach. Instead of having individual silos using their methods of authentication, there’s a common method that ensures consistency across the enterprise. When deploying enterprise-wide solutions, make sure they can maintain an established level of security.
Clean cloud storage.
Using cloud storage effectively means eliminating data silos and establishing a process for data validation. Removing duplication can reduce storage space and associated costs. Implementing a robust cloud security plan protects crucial assets while enabling knowledge sharing throughout an organization. The best way to effectively use cloud storage is to follow best practices when moving to the cloud and recognize that ongoing monitoring of data storage will be necessary to ensure clean cloud storage.