From micromobility to last-mile delivery, mobility and transportation use cases are inherently geospatial. Whether you’re planning expansion into a new city or territory or optimizing rider / fleet operations, mobility companies are turning to spatial analytics to find greater profitability in a time of rapidly rising costs and fluctuating consumer demand.
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TDWI research has found that organizations are increasingly modernizing their data warehouse environments. Often the current environment is not sufficient to support new analytics initiatives or they need to support new data types for analytics. Many enterprises are moving to the cloud as part of this journey. In fact, cloud data warehouses and cloud data lakes are already mainstream. The popularity of automated tools is growing as environments become more complex.
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The HAProxy Data Plane API enables you to configure your HAProxy load balancers programmatically. This latest release, version 2.5, expands coverage of existing HAProxy configuration directives, fixes bugs, and optimizes performance.
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As data and analytics environments become increasingly complex, organizations can no longer afford to perform many operations manually. According to TDWI research, automation (in general) is one of the top three priorities for analytics. We see automation occurring throughout the data and analytics life cycle. Automation increasingly leverages embedded AI/ML algorithms (i.e., infused in the software) to help perform tasks such as profiling and cleansing data, identifying sensitive data, data mapping, surfacing insights, or building machine learning models.
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