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By CIO Applications| Monday, October 19, 2020
Developers will develop more tailored experiences based on a company’s data flow, enhancing the system with analytic apps, and minimizing the time required for data-based actions over the BI loop.
FREMONT, CA: Data visualization is the lynchpin that integrates data visually to obtain intelligent data stories that require a business synthesis to see the bigger picture. As various data sources offer benefits in the future, businesses will encounter sophisticated data queries to discover what their data want to convey.
Here are five business intelligence (BI) trends for data visualizations and insights:
Developers will develop more tailored experiences based on a company’s data flow, enhancing the system with analytic apps, and minimizing the time required for data-based actions over the BI loop. Workflows will be more seamless and unified, allowing users to handle one asset through the BI and analytics platform instead of various siloed platforms.
Personalized Data Interactions
The development in NLP systems will allow data owners to get involved with natural data interactions. Because many BI vendors provide direct interactions with data, businesses will understand and collect more economic value from heaps of information warehouses by developing a more natural conversational occurrence.
Data Storytelling Method
As data storytelling is a vital aspect of BI, data analytics dynamics will change the architecture of data storytelling. Data storytelling approaches will foster a conversation around the data and less about likely conclusions.
DataOps and Self-Service BI
DataOps enhances the quality and decreases the cycle time of data management on the operational side. DataOps and self-service BI will aid in seamless data flow throughout warehouses and pipelines across the overall value chain.
Data storage will bring on-premises and cloud storage on a shared platform. More businesses will move to the cloud, introducing the emergence of hybrid product features that will work in the cloud, on-premises, or on both.
See Also: Top NLP Startups