New data is generating at a rapid pace, especially unstructured information. There are growing demands for AI-enabled analytics, and business users want fast access to data insights. A modern data architecture should deliver on these trends and more, says a recent survey and report by TDWI Research:
“With data application workloads becoming numerous, varied and complex, organizations need a modernized data architecture that delivers faster and more agile paths to insights.”
Yet many enterprises still depend on heterogeneous data systems for their BI and analytics. Traditional applications are constrained by IT-managed datasets too. 54% of respondents say it can take a day or up to a month to add new data to their platforms.
How should organizations modernize their data architecture to meet current demands? TDWI Research provides a number of recommendations. Among them: using cloud services, unified metadata and self-service analytics.
Leverage the Cloud
Instead of on-premise systems with limits on storage and performance, cloud data platforms offer much more flexible, scalable and faster deployment at lower cost. 54% of survey respondents say they already have traditional applications running in the cloud.
At the same time, researchers caution that the rush to “spin up systems in the cloud” could lead to data fragmentation and governance issues. They recommend a balanced data strategy, using cloud data storage as the main ingestion and staging area. Data can then be loaded into warehouses or target analysis platforms.
“Cloud data storage can provide a foundation for a balanced data strategy that includes data from legacy applications and systems. Many organizations focus first on migrating their on-premises data warehouses to the cloud, but by using object storage in the cloud, they can gain the benefits of the cloud sooner and more cost-effectively.”
Establish a Metadata Repository
A central metadata repository, such as a data catalog, helps ensure data quality and consistency by providing definitions, lineage, mapping and other information about data. It also makes it easier for users to find relevant content.
Yet there is room for improvement. While 66% of respondents say increasing data quality and trust would enhance their BI and analytics, 49% indicate their catalogs need a major upgrade.
TDWI recommends that organizations work to establish a complete metadata repository. Using AI-based automation can ensure that the catalog is consistently maintained and up-to-date.
“With traditional manual methods, it is difficult to scale metadata repositories. Modern, AI-driven services provide intelligent automation for complete and accurate data quality profiling, assessment, remediation and monitoring.”
Use Self-Service Analytics
Self-service analytics enables everyday users to freely explore and analyze data, without the constraints of linear queries or dependence on IT. Researchers recommend expanding self-service data interaction, and 54% of respondents agree.
“Self-service solutions integrated with cloud data platforms enable business users to respond to immediate needs for data visualization, analytics, predictive model development and new data exploration. Ease of use is a critical success factor.”
Additional strategies to consider:
- Provide access to a fuller range of data. Consider whether a unified data warehouse/data lake could better handle workloads for business users.
- Integrate analytics with data catalogs. Make it easier to locate datasets, understand data lineage and build trust in the information.
- Increase data literacy. Help everyone increase their skills, proficiency and experience to gain full value from their data.
A Modern Approach
A final word from TDWI Research: “With a modern data architecture, organizations are better able to realize data-driven opportunities for improving operational performance, enhancing customer relationships and accelerating product and service innovation.”
Once organizations adopt a modernization strategy, an innovative partner like Qlik can help them build the right data infrastructure. One that integrates all types of data, and delivers analytics and insights to meet everyone’s needs.
To read the full TDWI report, Modernizing Your Data Architecture to Unlock Business Value, download it here.