The Software Works Fine – Organizational Problems Are The Main Barrier to Effective Data Management

• Building required data management competencies is a common problem for organizations.
• Users use data management tools for classic business intelligence tasks, trend topics are hardly used.
• Comparing the opinions of the user companies with those of the software vendors, it appears that the vendors are somewhat ahead of the curve in their assessment of current customer requirements.

The analyst firm BARC published The Data Management Survey 20 today. The second edition of this annual study analyzes feedback from a survey of 782 professionals on the selection and use of data management software.

One in three companies claim to have no significant problems with their data management software and technological problems in general are rare. About one in ten bemoan overcomplexity in development and operation or inflexible licensing models.

However, the most common problems reported by data management users are organizational in nature. 26% of survey respondents cite a lack of internal know-how as a problem. Organizational challenges and company politics are also experienced by 19% and 16% respectively.

“This comes as no great surprise,” said Timm Grosser, Senior BARC Analyst and author of The Data Management Survey 20. “In other BARC surveys, companies frequently complain of a knowledge gap and a lack of maturity. Building up the right skills seems to be a general issue, which for some companies cannot be fully addressed by external resources. After all, there is a lack of skilled workers in this market. Right now, there is clearly a discrepancy between the potential of software in principle and the added value that is being achieved with it in reality.”

Customers use data management tools for classic business intelligence tasks – the adoption of trends is limited

The focus on business intelligence (BI) is clearly evident when looking at the tasks performed with data management tools. Data integration is performed by 61% of survey participants and BI/data warehousing by 59%.

“This may be due to a general BI focus in the panel of respondents or possibly a sign of the maturity level of participating companies,” said Grosser. “Alternatively, it could be interpreted that experience with technologies for data labs is not yet widespread. Our experience shows that some organizations are well aware of lab technologies, but there are still a lot of open questions relating to data science.”

37% of respondents use their technology for data warehouse automation (DWA). Regardless of whether a database, a data integration tool or a special DWA tool is used, the automation of data warehouse routine activities appears to be an important goal.

Comparing the opinions of user companies with those of software vendors, it seems that providers have a rather premature view of current customer requirements. Vendors tend to view their tools as being suitable in topical areas such as self-service analytics (39%), data discovery (38%) and even advanced analytics/machine learning/AI (37%) and data cataloging (32%). However, the latter two topics in particular are not yet on the agenda of users.