Cost development in Companies for Data Management and Data Integration

A recent study by Gartner found that the average cost for data management and integration is around 10% of an organization's IT budget. This cost is expected to increase in the coming years as organizations continue to generate more data and adopt new technologies to manage and integrate it.

Here are some of the key findings from the Gartner study:

• The cost of data management and integration is expected to grow at a rate of 5% per year.
• The largest cost driver is data lakes, which account for 40% of the total cost.
• The second largest cost driver is data integration, which accounts for 30% of the total cost.
• The third largest cost driver is data governance, which accounts for 20% of the total cost.

The study also found that the cost of data management and integration is highly correlated with the size of the organization. Larger organizations tend to have higher costs due to the complexity of their data environments and their need to support more users.

Here are some of the factors that can affect the cost of data management and integration:

• The size and complexity of the organization's data environment. Larger organizations with more data sources and applications tend to have higher costs.
• The number of users and the type of access they need to data. Organizations that need to provide access to a large number of users or that require specialized access for certain types of users tend to have higher costs.
• The frequency with which data is updated and the need to maintain data quality. Organizations that need to update data frequently or that must adhere to strict data quality standards tend to have higher costs.
• The use of third-party data sources and the need to integrate data from multiple sources. Organizations that rely on third-party data sources or that need to integrate data from multiple sources tend to have higher costs.

Organizations can take several steps today to reduce the cost of data management and integration:

• Standardize data formats and naming conventions. This will make it easier to integrate data from multiple sources and reduce the need for manual data cleansing.
• Use metadata to track and manage data assets. This will help organizations to avoid duplication of effort and to identify and fix data quality issues.
• Automate data processes whenever possible. This will free up IT staff to focus on more strategic initiatives and reduce the risk of human error.
• Leverage cloud-based data management and integration solutions. Cloud-based solutions can provide a more cost-effective and scalable way to manage data.
• Partner with vendors for data management and integration services. This can provide organizations with access to expertise and resources that they may not have in-house.

By taking these steps, organizations can manage their data costs more effectively and reap the benefits of better data management and integration.