IDC Report: Calming the Storm with Cloud Native Data Integration

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Page 2 #US47518521 IDC TECHNOLOGY SPOTLIGHT Calming the Storm with Cloud-Native Data Integration these demands, take advantage of cloud scale and elasticity, and reclaim control of data in the cloud. Cloud-native data warehouses offer some flexibility of data type and schema, but they still require a mediator to handle ingestion and transformation of the diverse and dynamic data used by companies competing in the digital economy. Cloud-native data, data lakes, and data warehouses require cloud-native data integration solutions that can also take advantage of cloud scalability and elasticity to help calm the storm. Benefits of Cloud-Native Data Integration Cloud-native data integration not only takes advantage of cloud scale and elasticity but also benefits from cloud "ease of use," leveraging straightforward graphical user interfaces for design, development, and deployment of data integration pipelines. This accessible approach is helping unlock efficiency and productivity gains with the new generation of data-native workers. Regardless of specific roles, there are common traits and behaviors that define a new generation of workers (and citizens) in today's data-rich world. IDC has defined people in these roles as a generation: Generation Data, or Gen D for short. Gen D workers are data natives — data is what they work in and with to complete their tasks, tactical and/or strategic. The 80/20 rule has long been touted in the world of data and analytics: Analysts spend 80% of their time looking for and preparing data and only 20% of their time doing analysis and getting insight out of the data. In 2017, IDC ran a survey that validated the 80/20 rule, as we asked respondents how much time they spent on each of these data activities. This underscores the continued importance of data preparation, including cloud-native data transformation, as part of the data value chain. A 2021 IDC survey on data culture asked a similar question (see Figure 1). The good news from that survey is the ratio is closer to 70/30 now, suggesting that efficiency has improved, perhaps because tools are improving and making it easier for Gen D to be successful. The bad news is that effectiveness has not improved: On average, 50% of the time people are still unsuccessful at completing data activities in a reasonable and expected time frame. Cloud-native data integration solutions provide the opportunity to make data integration more accessible and easier to use, helping the data-native worker be more efficient and effective in data activities. FIGURE 1: Distribution of Data Activity Time Q Approximately how many hours per week on average do you spend on each of the following data- and analytics-related activities? n = 455 Source: IDC's Data Culture End-User Survey, 2021 Discovery (25%) Preparat ion (27%) Prot ect ion (21%) Analysis (28%)

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