These KPIs need to be
Posted: Thu Feb 13, 2025 3:48 am
A data strategy needs to have a clear definition of key performance indicators that map to the overall business strategy. measured at an overall organizational level. Based on business needs or strategy, if metrics need to be measured at edge locations for real-time decision-making or quicker turnaround time, the data strategy needs to consider KPIs for separate edge locations as well.
A data strategy needs to comprehensively cambodia whatsapp number data cover both data integration methods and analytics tools. For analytics at the edge, the data integration method is expected to be simple, since the raw data will be in a specific format. However, for analytics in the cloud, data integration technologies are expected to be complicated due to disparate data structures and the need to transform to a common structure before using it for analytics purposes.
Data strategy needs to cover security, latency, and bandwidth considerations. If applicable, it also needs to cover data transfer through international boundaries.
Data strategy needs to call out the hardware limitations of deploying analytics solutions in the edge and cloud, as both solutions have pros and cons. In the case of edge analytics, the effectiveness of analytics is dependent on the computation power in the edge site. If there are resource constraints in running analytics in the edge, the strategy needs to consider an alternative, nearby edge site that can perform the task.
A data strategy needs to comprehensively cambodia whatsapp number data cover both data integration methods and analytics tools. For analytics at the edge, the data integration method is expected to be simple, since the raw data will be in a specific format. However, for analytics in the cloud, data integration technologies are expected to be complicated due to disparate data structures and the need to transform to a common structure before using it for analytics purposes.
Data strategy needs to cover security, latency, and bandwidth considerations. If applicable, it also needs to cover data transfer through international boundaries.
Data strategy needs to call out the hardware limitations of deploying analytics solutions in the edge and cloud, as both solutions have pros and cons. In the case of edge analytics, the effectiveness of analytics is dependent on the computation power in the edge site. If there are resource constraints in running analytics in the edge, the strategy needs to consider an alternative, nearby edge site that can perform the task.