By Clive Bearman, Director of Product Marketing for Data Integration at Qlik
Organizations have access to more data than ever before. The C-Suite is pushing their teams to leverage these mountains of data for fresh insights and rapid decision making. But despite growing investments in analytics and AI, there are still rampant organizational gaps that limit people’s access to the right data at the decision time. In many instances, those gaps relate to reliance on traditional tools that can’t create the real-time analytics data pipelines needed to be a modern, data-driven enterprise.
The impact of not solving this challenge is significant. Our research with IDC, which surveyed decision makers at 1,200 global organizations, shows that organizations that have strong analytics data pipelines for decision making see real bottom line impact.
- 76% said operational efficiency improved by an average of 17%
- 75% said revenue increased by an average of 17%
- 74% said profit increased by an average of 17%
How can businesses improve their process for transforming data from raw to analytics ready? One key strategy is dumping the data batch process, and pivot from traditional tools to leveraging automation to build on-demand analytics data pipelines.
Traditional methods of data transformation, such as Extract, Transform, Load (ETL), are powerful and have been instrumental in making huge quantities of data ready for analysis. However, such heavy tools are no longer suited to the agile approach to data that modern business demands. Batch processes for moving transactional data into a data lake or data warehouse where it can be governed, cleansed, and queried, for example, can take between six to nine months. This means highly skilled individuals end up spending a huge amount of time transforming data, when their resource could be better invested in higher value activity.
Furthermore, these ‘expert friendly’ tools are just that—Made to be used by experts with a deep knowledge and understanding of the solution. And with nearly a third (31%) of companies globally reporting that a lack of skilled resources is one of the greatest challenges they face in transforming data, its unsurprising that organizations too often rely on just one or two specialists to manage the process.
This presents a massive risk, as their specialized knowledge of the bespoke process leaves the business when they do. When that happens, the data transformation process becomes brittle and risk prone. And when it eventually breaks, significant delays occur while both trying to find a new resource and in the time it takes them to get up to speed so they can unlock valuable data that in the meantime lays dormant.
Organizations must explore how new approaches to data transformation can automate elements of the process and alleviate the pressure on highly skilled staff. Making the shift away from batch uploads of data and toward a continuous model leverages proven technology like Change Data Capture (CDC). This enables data from any source to be replicated and streamed in near real-time for analysis. Some more advanced solutions also eliminate the manual-coding process, automating and accelerating data ingestion, data replication and the loading of data into new locations.
This significantly increases the speed at which data is transformed, and simplifies scripting to lower the technical barrier, relieving the burden on programmers of writing thousands of lines of code when integrating new sources into data warehouses. The move away from manual integration processes also reduces the risk of human error in the scripting process and of specialized expertise leaving the business.
Too many organizations are sitting on a potential goldmine of invaluable insights hidden in raw data. However, the time-intensive, manual processes to transform it into analytics-ready data for analysis is holding too many companies back from realizing its true value. To help organizations transform and use their data at the speed that modern business demands, its critical to deploy technologies that automate the data integration process and relieve highly skilled workers to focus on more complex, creative and value-add tasks.
Learn more about how Qlik’s data integration and cloud analytics solutions can help you turn insights into confident actions.