"Best Practices in Retail: In-memory Analytics Implementation", report discusses how different retailers can benefit from in-memory analytics, with advice provided for IT vendors. The technology helps them to perform multidimensional analysis of various KPIs such as sales, customer preferences, products and more for any store, irrespective of time and location. To determine the most efficient use of in-memory analytics, this report analyzes multiple best practice approaches from different retailers.
In-memory analytics can help retailers speed up the time to insight, especially where large data volumes are concerned. It is particularly beneficial for cases that require real-time analytics with very low latency, which includes supply chain management and customer insight for scenarios such as identifying opportunities at the point of sale (POS) or by an aisle through digital communications with customers.
- In-memory analytics enable retailers to manage, analyze and respond to queries in real-time and with less complexity
- In-memory analytics can help to perform multidimensional analysis of various KPIs such as sales, customer preferences, products and more for any store, irrespective of time and location
- A large number of retailers such as Wal-Mart, Tesco, Carrefour, Costco and others are already capitalizing on the benefits of in-memory analytics implementations
- Get a detailed understanding of the usage and importance of in-memory analytics in retail. This report can help you pitch solutions to retailers that include in-memory analytics technology and to gain insight into retailers' priorities and challenges.
2. Case study: Wal-Mart Stores Inc.
2.1 Retailer Overview
2.2 Challenges faced by the retailer
2.3 Solutions deployed
2.4 Implementation process
2.5 Benefits realized
3. Case study: CARREFOUR S.A.
3.1 Retailer Overview
3.2 Challenges faced by the retailer
3.3 Solutions deployed
3.4 Implementation process
3.5 Benefits realized
4. Advice for IT Vendors
5.1 Further reading
5.2 Contact the authors