E-commerce company Sneakers to the Max wants to strengthen its bottom line with an improved search engine that provides better and quicker results to customers. As a software engineer, your task is to create a structure for importing data into the search engine. You’ll write a Python script to import sneaker data into Elasticsearch. Next, you’ll create an index for the sneakers and use aliases to keep the data available while importing a fresh catalog. To verify your import and gauge the quality of your data, you’ll create a Kibana dashboard. Using Elasticsearch Bulk, you’ll improve the indexing performance of the sneaker data you need. When you’re finished, you’ll have created a complete structure for your imports that enables frequent, regular updates without downtime.

You’re a software engineer for Sneakers to the Max, an e-commerce company that sells sneakers. Its CEO wants to improve the speed and quality of the company’s search engine in hopes of boosting sales. Your task is to optimize the mappings of the Elasticsearch index. You’ll use the Kibana developer console to analyze the current mapping and create a new custom analyzer. To improve search matches—and customer experience—you’ll use the Elasticsearch field mappings to support multiple uses of the same field. You’ll modify the mappings to help customers find the sneakers they’re looking for, even if their search terms are incomplete or contain typos. To further improve CX, you’ll add synonyms to the Elasticsearch configuration to handle searches that use different terms for the same concept.

As a software engineer at Sneakers to the Max, it’s your job to create an API that the e-commerce company’s developers can use to improve search results. You’ll write Python code to create Elasticsearch queries that work best for zero, one, or multiple search terms. To enable the application to interact with the search service, you’ll implement a FastAPI endpoint. You’ll add query filters, including colors and price ranges, to narrow down the results, and you’ll add pagination for when the number of sneakers in the narrowed search results is too large to be displayed on one page. When you’re done, you’ll have created an API that empowers your developers to provide the best matches to customers’ searches and leads to increased sneaker sales.

Help Sneakers to the Max’s customers find the perfect sneakers! As a software engineer at the e-commerce company, your task is to improve its search engine—and hopefully sales—by fine-tuning the order of search results. You’ll adjust the index mapping to import data about sneaker release dates, popularity, and in-stock status. Then, you’ll write extensions to the Elasticsearch queries that boost recent and popular results, forcing out-of-stock sneakers lower. Finally, you’ll use everything you learned to return the most relevant sneakers using a judgment list provided by the product managers. When you’re finished, you’ll have the skills to enhance Elasticsearch queries, while Sneakers to the Max’s customers will easily find the perfect pair.