Analytics Code Metrics Retail 
Dynatrace
SEPTEMBER 10, 2020
For most who work in the retail sector, the pandemic has been an unwelcome test of our ability to cope with disruption. In eight months, retailers offering curbside pickup increased from 7% to 44%, reflecting rapidly changing consumer preferences. You’ll benefit through ad hoc analytics to drive real-time collaboration.
Dynatrace
JULY 29, 2022
What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.
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Dynatrace
JULY 29, 2022
What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.
Dynatrace
FEBRUARY 18, 2020
On the other side of the organization, application owners have hired teams of analysts to dig through web analytics tools to gain insights into the customer experience. Welcome to Dynatrace Digital Business Analytics. What does this mean and how can you unlock Digital Business Analytics? Digital Business Analytics in action.
Dynatrace
NOVEMBER 6, 2023
As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. Remote management and automated alerting are, therefore, crucial.
Dynatrace
JANUARY 22, 2024
Software project managers can optimize development processes by analyzing workflow data, such as development time, code commits, and testing phases. Retailers can analyze how factors such as demand, competition, and market trends affect pricing. Government.
Dynatrace
OCTOBER 17, 2023
retail giant, initially tied to an ingest-centric pricing vendor, found itself manually curbing costs by limiting daily log ingestion to 3 TB and reducing retention periods. Consequently, the company’s mean time to identify (MTTI) and mean time to resolve (MTTR) during peak retail seasons was too slow. Enhanced code-level visibility.
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