The State of Data Management – Why Data Warehouse Projects Fail

Organizations are increasingly investing in cloud data warehouses to help them make the most of their valuable data assets. However, the process of identifying and moving data into a data warehouse is not always straightforward, all too often inhibiting progress and success.

In part one of our new two-part study, “The State of Data Management – Why Data Warehouse Projects Fail, we found that 83% of organizations are not fully satisfied with the performance and output of their data management and data warehousing initiatives. 

Together with independent research firm Vanson Bourne, we surveyed 500 IT Decision Makers (ITDMs) at businesses in the US and UK to understand their data management challenges, the vital role data warehouses play, and the road to success.

Some key findings from our research include:

  • Nearly nine in ten (88%) of ITDMs experience challenges trying to load data into data warehouses, with the biggest inhibitors being legacy technology, complex data types and formats, data silos, and data access issues tied to regulatory requirements
  • The average enterprise has 115 distinct applications and data sources, with almost half of them (49%) siloed and disconnected from one another
  • 89% of ITDMs are worried these data silos are holding them back
  • ITDMs report that, on average, 42% of data management processes that could be automated are currently being done manually, taking up valuable time and resources
  • As a result, almost all respondents (93%) believe improvements are needed in how they collect, manage, store, and analyze data

Download “The State of Data Management – Why Data Warehouse Projects Fail now.

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