Please post your solution to the Nov. 18 in class exercise to this thread. Best, Chris

-- Nov 18 In-Class Exercise Thread

 Data propogation for product suggestion, where any relevant information about the product 
 like changing prices or overall reviews on the product change can be shown in real time.
 
 Given we know what user might be interested, for e.g. blender
 Source1:
 productTable(product name, product price)
 insert values(blender, 20$)

 Source2:
 doucment{
   name: blender,
   userName: User1,
   reviewer: good
 }
 
 Target1:
         call->  productName, productPrice, user, productReview
 aggregatedTable(blender, 20$, User1, good)
                  
                    

Data propogation for product suggestion, where any relevant information about the product like changing prices or overall reviews on the product change can be shown in real time. Given we know what user might be interested, for e.g. blender Source1: productTable(product name, product price) insert values(blender, 20$) Source2: doucment{ name: blender, userName: User1, reviewer: good } Target1: call-> productName, productPrice, user, productReview aggregatedTable(blender, 20$, User1, good)

-- Nov 18 In-Class Exercise Thread

Data Virtualization - timely access

-- Nov 18 In-Class Exercise Thread

Keyword Advertising: Data consolidation - We want to get information from external source systems and integrate them into the currentdata store. This a useful method of allowing multiple advertisers on to the result page. We can use data consolidation to keep track of data such as which keywords on which they are advertising, how much they are paying for our service, an the price at which they sell their products. There is a high latency to this pattern, so it should be used sparingly (preferably once); thus, a kind of data pipeline should be established so changes are quickly reflected, which leads us to... Changed Data Capture - If there are updates to the external source's tables (say, a change in the website's description or a list of products that are seen on the advertisement result page), we want them to be reflected in our consolidated data store. Say a certain product suddenly becomes very frequently searched; it would be good to be able to implement something like surge pricing i.e. increasing the price in accordance with greater popular interest. This allows for more timely advertisements. Product Suggestion: Data federation - While the pull approach here is rather slow, product suggestion queries tend to be simple enough that they are likely to perform better than others. The reason we want to use Data federation is because it allows for products from different data warehouses to be displayed, and we will want to be querying on certain datapoints such as genres, tags, price, item type, etc. Seeing as we want these queries to be even faster, it would be helpful to add a cache of some kind, so... Data virtualization - If a user is looking at products of specific types, maintaining a cache which stores products keyed to their interests (datapoints like genre, price, item type, etc. that can filter out uninteresting items) would be an extremely useful tool to retaining customers.

-- Nov 18 In-Class Exercise Thread

 Data federation: Using Enterprise information integration, 
 Divide the keyword advertising business logic into external and internal. 
 Make a keyword mapping table with reference to the commercial market.

 complex event processing to trigger more keywords

Data federation: Using Enterprise information integration, Divide the keyword advertising business logic into external and internal. Make a keyword mapping table with reference to the commercial market. complex event processing to trigger more keywords

-- Nov 18 In-Class Exercise Thread

Data Propagation should be used for product suggestion. When calls are being made for product1 (from source1) in adding to cart or searching, the previously stored results stating that product2 is bought together with product1 can be used to call source2 for product2 Data Consolidation and/or Federation should be used for search engine keyword advertising. Firstly, data is brought from many underlying sources. Then, keywords ca be split in internal and external business logic manner.

-- Nov 18 In-Class Exercise Thread

For keyword advertising Data federation can be used since we are taking the data from two sources. The results returned from the keyword search and the advertisements related to the keyword search. For product suggestion Data propagation can be used since when a user buys a product we update both a user's product history and use that to generate a list of product suggestions to the user.

-- Nov 18 In-Class Exercise Thread

Changed Data Capture can be used for keywords search. It can consolidate the data from different data sources using ETL process and using update listeners it can capture the updates in data sources. This allows real time updates to be reflected to end users. Data Propagation can be used for product suggestion. The product displaying handles logic of presenting products to the user. Once the user selects a product, this can be used as trigger to make call to product recommendation application that finds related products to the one selected by the user. It can use two different data stores for storing product data and other the user's history data to use it for better suggestions.

-- Nov 18 In-Class Exercise Thread

 Data propagation can be used for product suggestion on a web store. When a user makes a 
 purchase, the update would be propagated to a store holding user purchase history. The 
 purchase history information would be used to make informed product suggestions.

 Data federation can be used for keyword advertising on a search engine. Demand is created 
 once a user enters a search query in the search engine. Once the search query is parsed 
 for keywords, underlying keyword data sources would be pulled from to match relevant ads.

Data propagation can be used for product suggestion on a web store. When a user makes a purchase, the update would be propagated to a store holding user purchase history. The purchase history information would be used to make informed product suggestions. Data federation can be used for keyword advertising on a search engine. Demand is created once a user enters a search query in the search engine. Once the search query is parsed for keywords, underlying keyword data sources would be pulled from to match relevant ads.

-- Nov 18 In-Class Exercise Thread

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