January 11, 2023
Building the Road Map for Real-Time Data and Analytics
As organizations strive to be more competitive, they often need real time insights; no one wants to make decisions based on stale data. TDWI Research indicates that real-time data collection is already in the mainstream. Some use cases include Inventory Management, Fulfillment, Supply Chain & Logistics in which retailers must be able to assess product availability and consumer demand in real-time. Forward-looking organizations also want to enrich real-time data with other data types to provide even better analytics.
Part of this move to become more real-time involves both infrastructure and analytics platforms. At TDWI, we see many organizations already moving to the cloud to deal with real-time, high volume data. In a recent survey, for instance, more respondents were utilizing a cloud data lake than one on-premises. Organizations are also starting to use newer platforms such as cloud data lakehouses to manage their data. In addition to the move to cloud for data management, organizations are also looking for analytics solutions that can keep up with the intensity of the data they are collecting, while at the same time being useful to multiple Line of Businesses (LOB) throughout the organization.
Join Fern Halper, TDWI’s VP of Research, in a panel discussion with Databricks and Sigma Computing about how to build the roadmap for real time data and analytics. Topics will include:
- How to get started with real-time data
- The state of real-time data and some use cases in the retail industry
- Architectural & Analytics considerations for getting the most out of real time data for fast business decision making
We are Sigma.
Sigma is a cloud-native analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It requires no code or special training to explore billions of rows, augment with new data, or perform “what if” analysis on all data in real-time.