Data Quality Before Quantity

This means that, at least in theory, SAP’s existing customers are in an excellent position to use their data to optimize internal processes and develop new business models in order to remain competitive. An IDC study on the current data situation shows that the reality is different, however: Developing innovative cases is not trivial, and data-driven innovations are not currently an issue for three quarters of German companies because good data quality is one of the biggest challenges in data management for 37 percent of decisionmakers. 66 percent of organizations see the cloud as the central solution for all data issues.

IDC surveyed IT and business decisionmakers from 261 organizations with more than 100 employees in Germany last year, providing detailed insights into implementation plans, challenges, and success factors in storage, data management, and data governance.

Data quantity but little quality

The amount of data worldwide is expected to grow to 143 zettabytes by 2024, according to IDC estimates. Almost one-third of the companies surveyed are experiencing annual data growth of between 31 and 60 percent. This very dynamic and heterogeneous data environment requires a new approach in companies.

“The growing volume and variety of data are both a curse and a blessing. The great business potential of data can hardly be tapped with existing solutions and processes, and data-driven business models are thus becoming a distant future. However, no decisionmaker can afford to slow down,” explains Matthias Zacher, Senior Consulting Manager and Project Manager, IDC.

For 37 percent of those surveyed, ensuring high data quality is one of the key challenges. The different aspects of it are diverse and complex, ranging from capturing all relevant data and understanding the data context to data governance and data security. For these reasons, companies are reluctant to prepare and analyze their data end-to-end and for all business units in the required quality.

Flexibility and efficiency

The demand for cloud-based storage solutions is currently growing disproportionately and unsurprisingly for both primary and secondary workloads. In the medium term, IDC expects IT organizations to adopt a variety of solutions, with a growing dominance of cloud-based and hybrid approaches. Consequently, companies will sustainably improve their flexibility and agility, and thus their ability to react to changes in the market and to unexpectedly complex situations.

In many organizations, data governance and data intelligence solutions are available alongside traditional data management tools, but the study shows that the penetration rate is still far too low. For example, only a good third of companies use data mining tools or master data management tools. Apparently, there is still a need for comprehensive explanation among many decisionmakers about how they can use modern solutions in data management. IDC believes that solution providers have a duty to convince and educate with best practices and potential use cases.

The cloud is continuously developing into an integral part of the IT landscape. Many IT and business decisionmakers in all sectors, in mid-sized and large companies, have defined the cloud as a part or core element of their modernization strategy and are using it with growing success in more and more business areas. This has significant implications for data usage. Data managers expect solutions for data management and data analysis from cloud-native workloads as well as suitable tools for data use in highly widespread hybrid scenarios. The path to the cloud is becoming more and more predefined. Two-thirds of respondents already see the cloud as the central instance for all data issues – a view that is in line with IDC’s assessments.

Integration, automation, the use of modern tools across the entire process chain, and continuous optimization of data processes across all IT and business domains are the key to success. This must be the common goal of providers and users. Most companies have recognized the challenges in theory, but they need to make many adjustments in order to be prepared for the challenges of digital transformation and to be able to use their data comprehensively for innovation.