Patent Application
20210406936
Embodiments relate to techniques for computer operations. More particularly, embodiments relate to preservation of price calculation data in performance of price calculation operations.
In business operations, the generation of price calculations is often a computationally intensive task. Each sales item of a large sales order or other pricing transaction may require a different price calculation method, with each method requiring numerous processes, with each process being based on either an input or a result of a prior process.
Because of the nature providing calculations, any adjustment in any portion of a price calculation, such as modification of a calculation, addition of a discount, change in quantity of purchase, or similar adjustment, can require a full recalculation of the pricing. For this reason, back and forth adjustments with a customer on a purchase or quote generally requires the performance of multiple full pricing processes.
Further, if there are issues regarding a previous price calculation process that require auditing or investigation, there is generally little information available regarding how the pricing result was reached. While the final pricing outcome and the date of the price calculation may be available, this will not explain how a particular result was reached.
Embodiments are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements.
In the following description, numerous specific details are set forth. However, embodiments may be practiced without these specific details. In other instances, well-known circuits, structures and techniques have not been shown in detail in order not to obscure the understanding of this description.
In some embodiments, an apparatus, system, or process is to provide for collection and preservation of price calculation data in performance of pricing operations. In some embodiments, price calculation data for a pricing transaction is collected and preserved such that subsequent requests to provide incremental price calculation in which calculations are limited to modified elements to improve efficiency in pricing operations, and to improve customer experience in requesting sales transactions or receiving price quotes or bids.
In some embodiments, an apparatus, system, or process provides for incremental pricing of products. Instead of pricing an entire sales transaction with each request for a price calculation, data is preserved (including sales transaction, pricing plan, intermediate price calculations, etc.) in memory such that subsequent requests to price the same sales transaction may be reduced to delta price calculation requests, wherein a delta price calculation request refers to an operation to only calculate what is impacted by the most recent change to the sales transaction.
In some embodiments, an apparatus, system, or process further preserves audit data, with information and precise computation trails for pricing being provided so that customers can understand how a price was generated. In some embodiments, an apparatus, system, or process further includes illustration/visualization provided using the collected price calculation data set. In this manner, a visual reference is provided to illustrate a pricing method or a pricing waterfall to assist customers in understanding how the pricing engine applies pricing functions for the calculation of price.
In some embodiments, price calculation data collection is provided as a part of a pricing engine, with implementation hooks being provided to add pricing and audit information with finely grained details including, but not limited to, the pricing function, the price before the application of any function, the end result for the application of the function, and any other details that an administrator, sales manager, end user, or other party may wish to have to understand how a price was generated. In some embodiments, the data collection can also be exposed as part of an interface for customization so that parties may inject additional information that they wish to add to their audit.
As used herein, “sales transaction” or “transaction” refers to any sales order, quote, bid, shopping cart, or other inquiry regarding one or more sales items, with each sales item including a certain quantity.
The core platform 200 may include a public application programming interface (API) 110 for connection of multiple different types of clients that may generate operation requests, including requests to the pricing service 120 for price calculations. The requests may include business to business (B2B) requests 140 and configure-price-quote (CPQ) requests 142 provided within the core platform 100, and partner or independent software vendor (ISV) requests 144 received from outside the core platform 100. Other types of requests for price calculations may also be received.
The pricing service 120 in particular includes a getPrice function 130 to determine pricing for one or more sales items in a transaction, the sales items being any combination of goods and services, and to generate a price calculation data set based on the pricing operation. In a basic operation, the getPrice function for a particular request includes initialization of the pricing operation 132, sales price calculation for each sales item of the request 134, and aggregation of the price calculations to generate a pricing output 136 to be provided to the client. In some embodiments, the sale item price calculation 134 includes application of a particular pricing method for a sales item, wherein each sales item may utilize a different pricing method.
In some embodiments, the pricing service 120 include a price calculation data collection service 150, the service to generate a price calculation data set based at least in part on a calculation of pricing for a particular transaction. The pricing service may further include one or more price data functions that may be selected to receive one or more price calculation data sets, each price data function to perform one or more operations based on such data sets. The price data functions are illustrated as Function-1160, Function-2162, and continuing to Function-n 164. The price data functions may include, but are not limited to, operations for incremental price calculation for a modified transaction, as further illustrated in
Once the price calculation operation is completed, it is difficult to audit the pricing process to provide an explanation without re-creating the price calculation. However, the re-creation of the pricing process may be problematic because the context of the sales transaction may have changed, thus potentially changing the pricing. For example, if the application of particular pricing contract or arrangement depends on factors such as the total amount of sales at that time, the application of a discount within a particular time window, or other context dependent calculations, all such factors must be known in order to generate a correct pricing result.
In some embodiments, an apparatus, system, or process is to collect and preserve price calculation data in a manner and form that allows for incremental price calculation in which a price calculation operation for a transaction may be performed with delta price calculations. As used herein delta price calculation means that only those changes which have been made to the sales transaction since the last price calculation for that sales transaction need to be provided to the pricing engine API. However, in order to support incremental price calculations, the pricing engine will need to preserve intermediate price calculations and any related information.
In some embodiments, a sales transaction 205 is provided to a pricing service 210, the pricing service being illustrated in more detail in
In some embodiments, the pricing service 210 is to automatically generate a price calculation data set 220 based on the calculation of the pricing result 215 for the sales transaction 205. In some embodiments, the price calculation data set is generated contemporaneously with the price calculation, thus enabling the preservation of the current data and actual calculations for the pricing of the sales transaction. The price calculation data set 220 may be utilized in one or more price data functions 230, wherein the price data functions 230 may include incremental price calculation for a modified sales transaction 232, as further illustrated in
In some embodiments, the price calculation data set 220 may include, but is not limited to:
(a) A designated sales transaction identifier for use in identifying and tracking price calculations for specific sales transactions;
(b) Context information for a sales transaction, which may include a client identifier, data and time of the price calculation, sales contract terms, sales history information, and other context information to allow identification of factors that influence the price calculation;
(c) Sales transaction data, including at least identification of the sales items and quantities for the sales transaction;
(d) Identification of the pricing plan utilized in the price calculation;
(e) Any pricing modifications or adjustments applied in the price calculation;
(f) Intermediate price calculations, including pricing before and after each calculation, and any additions or subtractions made in the price calculations; and
(g) Relationships between sales items and related calculations, which may include, but is not limited to, line item groups and derived pricing dependencies for line items. For example, calculations for a total across a line item group are generated and retained.
The process may continue with calling a function for price calculation 312, such as the getPrice function 130 illustrated in
The process may then proceed with a determination whether there are any additional sales items for calculation 332, and, if so, a next sales item is selected 336 and the process can return to calling the getPrice function 312 and resolving the pricing method for the next sales item 316. If there are no additional sales items for calculation 332, the process continues with aggregation of the pricing results for the sales transaction 340. In some embodiments, the process further include collection of price calculation data regarding the aggregation of pricing results (wherein the aggregation may include calculation of totals and application of one or more factors to the total values). In some embodiments, a price calculation data set is then generated for the sales transaction 344, wherein the price calculation data set includes at least the unique identifier for the sales transaction, the context data for the sales transaction, and the collected price calculation data for each one of the one or more sales items of the sales transaction. In some embodiments, price calculation data set further includes collected calculation data for the aggregation of pricing results.
In some embodiments, the generation of the price calculation data set may include one or more additional processes that are not illustrated, such as application encryption processing or data integrity processing to maintain the security and integrity of the collected data for future application.
The process then continue with obtaining a sales item for processing 356, and preserving sales item data 358, including identification of the sales item and the quantity of the sales item for the sales transaction. The process then will proceed with performing the price calculations for the sales item, and preserving calculation data for each calculation process involved in the price calculation. In a particular example, the process may include:
The processes for calculation and data preservation for the sales item 356-382 then may be repeated for each sales item of the sales transaction 384, with the resulting data for all sales items being aggregated to generate the price calculation data set 390. In some embodiments, calculation data may include calculation data for the aggregation of the data for the sales items, including any calculation of totals or the application of one or more factors to such totals to generate a final pricing result.
As described with regard to
In some embodiments, the price calculation data set for the original sales transaction pricing operation 408, wherein data set may be retrieved based on a unique identifier generated for and associated with the data set. The process proceeds with determination of any differences between the original sales transaction and the revised sales transaction and the effect of the differences on the price calculation for each sales item 412.
In some embodiments, a sales item of the revised sales transaction requiring a revised calculation (i.e., the calculation for the sales item has been affected by the revision to the sales transaction, and at least a portion of the calculation for the sales items needs to be performed) is selected 414. The pricing method for the sales item is resolved 416, and a delta sales item calculation is performed based on the determined differences for the sale item between the original sales transaction and the revised sales transaction 420. The performance of the delta sales item calculation is limited to the identified differences and resulting effects on calculation of each sales item.
For example, a calculation for a first sales item may be modified because of a change in quantity; a calculation of a second sales item may be affected by the change in quantity in the first item even if there is no change in quantity of the second sales item if there is a dependency between the pricing of the first sales item and the second sales item; and a calculation of a third sales item may not affected by the calculations of for the first and second sales items if there are not any relevant dependencies in the calculations. Further, a delta calculation may be limited to a portion of a calculation of pricing for a sales item if only a portion of the calculation is affected by the modification of the sales transaction. In some embodiments, if the effect of a modification is not discernable in comparison, the delta calculation may fall back to a full calculation of any or all sales items.
In some embodiments, determinations regarding differences for sale items between the original sales transaction and the revised sales transaction include differences for relationships between sales items and related calculations, such as line item groups and derived pricing dependencies. In a first example, a calculation for a total for a line item group is stored, and determining differences for sales items includes determining that the stored group total remains valid if no line items in the line item group have changed. In a second example, for a derived pricing dependency that is stored, determining differences for sales items includes determining that a line item having a price derived from one or more other line items remains valid if none of the other line items has changed.
The process then proceeds with a determination whether there are any additional sales items requiring revised calculation 424. If so, then a next sales item is selected 430, the pricing method for the sales item is resolved 416, and the delta sales item price calculation is performed 420.
If there are no additional sales items 424, the pricing results for the revised sales transaction are aggregated with data from the price calculation data set for unchanged calculations to generate an incremental price calculation result for the full revised sales transaction 434.
In a specific example, a sales representative may be editing a reasonably large (such as 100 sales items) quote, and changes the quantity of a particular sales item. In a conventional operation, the pricing engine would generally require recalculation of the pricing of the revised sales transaction. In some embodiments, a pricing engine is only required to recalculate the respective sales item and any other sales items that depend on such sales item (for example, a percentage of a total line item in a quote may be affected). The process may and then aggregate and update the sales transaction totals.
Thus, in order for a requesting party to make use of incremental price calculations, the price engine returns a transaction identifier in the pricing results. The client then can pass that transaction identifier for utilization in future requests. In some embodiments, party may specify with the initial request for price calculation whether incremental price calculation is desired. (Full pricing may be preferable if there are a large number of changes in the sales transaction as the delta price calculation may not provide sufficient processing savings in such case.)
It is noted that a price calculation data set may be generated during the incremental price calculation process, with the processes illustrated in
In some embodiments, an audit trail or explanation of a pricing process is generated based on a price calculation data set, such as illustrated in
In some embodiments, a request for an audit or explanation of all or a portion (one or more sales items) of a sales transaction is received 504, wherein the request includes a transaction identifier for a price calculation data set that was generated at the time of the price calculation. The price calculation data set for the pricing of the sales transaction is then received 508. It is noted that one or more processes may be required to ensure security and data integrity of the price calculation data set, decrypting the data set, checking data integrity of the data set, and similar processes.
In some embodiments, utilizing the retrieved price calculation data set, the process further includes establishing the relevant context for the price calculation operation based context data in the data set 512 and selecting a sales item for the audit or explanation 516. In some embodiments, calculation data for the sales item is identified in the price calculation data set 520, and a record representing the price calculation for the sales item is generated based on the identified calculation 524. For example, the record may represent every factor and calculation in the generation of the pricing result for the sales item. If there are additional sales items to be considered in the request 528, a next sales item is selected 532 and the process continues with identifying the calculation data for the selected sales item 520.
If there are no additional sales items to be considered in the request 528, the generated data for the price calculations is aggregated 536, and a report is then generated for the audit or explanation addressing all or a portion of the price calculation for the sales transaction 540. In some embodiments, audit or explanation may include a visualization of the pricing operation illustrated in
In some embodiments, upon receipt of a request for a visualization of a previous price calculation process for a sales transaction 604, which may include all or any portion of the pricing process, and a price calculation data set for the sales transaction is retrieved 608. A first sales item is selected for visualization 612, and the calculation data for the pricing of the selected sales item is retrieved from the price calculation data set 616.
In some embodiments, an illustration of each calculation process in the pricing of the sales item is generated based on the retrieved calculation data 620. For example, each price calculation provided in
If there are additional sales items to be considered in the request 624, a next sales item is selected 628 and the process continues with retrieving the calculation data for the selected sales item 618 and the generation of the illustration for the calculation process for such sales item 620. If there are no additional sales items to be considered 624, a report may be generated in response to the request, the report include each generated price calculation visualization 632.
In the illustrated price waterfall diagram, the price of a given product is reflected on the ‘y’ axis (i.e., the vertical axis) and the various adjustments to the list price are represented on the ‘x’ axis (horizontal axis). The bars with cross-hatching represent price reductions applied to the previous process in the price waterfall diagram. The shaded bars represent ‘price points’ and typically define the boundary between pricing functions that comprise the pricing method that results in this price waterfall diagram.
In the illustrated example, commencing with the list price, there are discount price reductions resulting in an invoice price; payment terms and consignment inventory price reductions resulting in the effective price; freight, expediting, and custom bar coding price reductions resulting in the net price; custom service and other price reductions resulting in the pocket price; and the cost of goods sold (COGS) resulting in the pocket margin. Many other pricing reductions and price points may be present in other examples. Each data element in the illustration is based on data from the price calculation data set, including:
Get List Price—Obtaining the List Price.
Calculate Invoice Price—Subtracting discounts from the List Price to generate the Invoice Price.
Calculate Effective Price—Subtracting payment terms and consignment inventory from the Invoice Price to generate the Effective Price.
Calculate Net Price—Subtracting freight, expediting, and custom barcoding from the Effective Price to generate the Net Price.
Calculate Pocket Price—Subtracting discounts from the List Price to generate the Invoice Price.
In the price waterfall diagram provided in
In this manner, a complete visualization of the pricing may be generated for each sales item in a sales transaction based on the price calculation data set for the sales transaction, which may, for example, be provided in connection with to a request for an audit or explanation of pricing of a sales transaction, as illustrated in
Environment 710 is an environment in which an on-demand database service exists. User system 712 may be any machine or system that is used by a user to access a database user system. For example, any of user systems 712 can be a handheld computing device, a smart phone, a laptop or tablet computer, a workstation, and/or a network of computing devices. As illustrated in herein
An on-demand database service, such as system 716, is a database system that is made available to outside users that do not need to necessarily be concerned with building and/or maintaining the database system, but instead may be available for their use when the users need the database system (e.g., on the demand of the users). Some on-demand database services may store information from one or more tenants stored into tables of a common database image to form a multi-tenant database system (MTS). Accordingly, “on-demand database service 716” and “system 716” may be used interchangeably herein. A database image may include one or more database objects. A relational database management system (RDMS) or the equivalent may execute storage and retrieval of information against the database object(s). Application platform 718 may be a framework that allows the applications of system 716 to run, such as the hardware and/or software, e.g., the operating system. In an embodiment, on-demand database service 716 may include an application platform 718 that enables creation, managing and executing one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 712, or third-party application developers accessing the on-demand database service via user systems 712.
The users of user systems 712 may differ in their respective capacities, and the capacity of a particular user system 712 might be entirely determined by permissions (permission levels) for the current user. For example, where a salesperson is using a particular user system 712 to interact with system 716, that user system has the capacities allotted to that salesperson. However, while an administrator is using that user system to interact with system 716, that user system has the capacities allotted to that administrator. In systems with a hierarchical role model, users at one permission level may have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users will have different capabilities with regard to accessing and modifying application and database information, depending on a user's security or permission level.
Network 714 is any network or combination of networks of devices that communicate with one another. For example, network 714 can be any one or any combination of a LAN (local area network), WAN (wide area network), telephone network, wireless network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. As the most common type of computer network in current use is a TCP/IP (Transfer Control Protocol and Internet Protocol) network, such as the global internetwork of networks often referred to as the “Internet” with a capital “I,” that network will be used in many of the examples herein. However, it should be understood that the networks that one or more implementations might use are not so limited, although TCP/IP is a frequently implemented protocol.
User systems 712 might communicate with system 716 using TCP/IP and, at a higher network level, use other common Internet protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTP is used, user system 712 might include an HTTP client commonly referred to as a “browser” for sending and receiving HTTP messages to and from an HTTP server at system 716. Such an HTTP server might be implemented as the sole network interface between system 716 and network 714, but other techniques might be used as well or instead. In some implementations, the interface between system 716 and network 714 includes load sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a plurality of servers. At least as for the users that are accessing that server, each of the plurality of servers has access to the MTS′ data; however, other alternative configurations may be used instead.
In one embodiment, system 716, shown in
One arrangement for elements of system 716 is shown in
Several elements in the system shown in
According to one embodiment, each user system 712 and all of its components are operator configurable using applications, such as a browser, including computer code run using a central processing unit such as an Intel Core series processor or the like. Similarly, system 716 (and additional instances of an MTS, where more than one is present) and all of their components might be operator configurable using application(s) including computer code to run using a central processing unit such as processor system 717, which may include an Intel Core series processor or the like, and/or multiple processor units. A computer program product embodiment includes a machine-readable storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the embodiments described herein. Computer code for operating and configuring system 716 to intercommunicate and to process webpages, applications and other data and media content as described herein are preferably downloaded and stored on a hard disk or solid state drive (SSD), but the entire program code, or portions thereof, may also be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disk (DVD), compact disk (CD), microdrive, and magneto-optical disks, and magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, e.g., over the Internet, or from another server, as is well known, or transmitted over any other conventional network connection as is well known (e.g., extranet, VPN, LAN, etc.) using any communication medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for implementing embodiments can be implemented in any programming language that can be executed on a client system and/or server or server system such as, for example, C, C++, HTML, any other markup language, Java™ JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).
According to one embodiment, each system 716 is configured to provide webpages, forms, applications, data and media content to user (client) systems 712 to support the access by user systems 712 as tenants of system 716. As such, system 716 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (e.g., in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (e.g., one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically and/or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to include a computer system, including processing hardware and process space(s), and an associated storage system and database application (e.g., OODBMS or RDBMS) as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database object described herein can be implemented as single databases, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and might include a distributed database or storage network and associated processing intelligence.
User system 712, network 714, system 716, tenant data storage 722, and system data storage 724 were discussed above in
Application platform 718 includes an application setup mechanism 838 that supports application developers' creation and management of applications, which may be saved as metadata into tenant data storage 722 by save routines 836 for execution by subscribers as one or more tenant process spaces 804 managed by tenant management process 810 for example. Invocations to such applications may be coded using PL/SOQL 834 that provides a programming language style interface extension to API 832. A detailed description of some PL/SOQL language embodiments is discussed in commonly owned U.S. Pat. No. 7,730,478 entitled, “Method and System for Allowing Access to Developed Applicants via a Multi-Tenant Database On-Demand Database Service”, issued Jun. 1, 2010 to Craig Weissman, which is incorporated in its entirety herein for all purposes. Invocations to applications may be detected by one or more system processes, which manage retrieving application metadata 816 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.
Each application server 800 may be communicably coupled to database systems, e.g., having access to system data 725 and tenant data 723, via a different network connection. For example, one application server 8001 might be coupled via the network 714 (e.g., the Internet), another application server 800N-1 might be coupled via a direct network link, and another application server 800N might be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are typical protocols for communicating between application servers 800 and the database system. However, it will be apparent to one skilled in the art that other transport protocols may be used to optimize the system depending on the network interconnect used.
In certain embodiments, each application server 800 is configured to handle requests for any user associated with any organization that is a tenant. Because it is desirable to be able to add and remove application servers from the server pool at any time for any reason, there is preferably no server affinity for a user and/or organization to a specific application server 800. In one embodiment, therefore, an interface system implementing a load balancing function (e.g., an F5 BIG-IP load balancer) is communicably coupled between the application servers 800 and the user systems 712 to distribute requests to the application servers 800. In one embodiment, the load balancer uses a least connections algorithm to route user requests to the application servers 800. Other examples of load balancing algorithms, such as round robin and observed response time, also can be used. For example, in certain embodiments, three consecutive requests from the same user could hit three different application servers 800, and three requests from different users could hit the same application server 800. In this manner, system 716 is multi-tenant, wherein system 716 handles storage of, and access to, different objects, data and applications across disparate users and organizations.
As an example of storage, one tenant might be a company that employs a sales force where each salesperson uses system 716 to manage their sales process. Thus, a user might maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (e.g., in tenant data storage 722). In an example of an MTS arrangement, since all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system having nothing more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, if a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates as to that customer while waiting for the customer to arrive in the lobby.
While each user's data might be separate from other users' data regardless of the employers of each user, some data might be organization-wide data shared or accessible by a plurality of users or all of the users for a given organization that is a tenant. Thus, there might be some data structures managed by system 716 that are allocated at the tenant level while other data structures might be managed at the user level. Because an MTS might support multiple tenants including possible competitors, the MTS should have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that may be implemented in the MTS. In addition to user-specific data and tenant specific data, system 716 might also maintain system level data usable by multiple tenants or other data. Such system level data might include industry reports, news, postings, and the like that are sharable among tenants.
In certain embodiments, user systems 712 (which may be client systems) communicate with application servers 800 to request and update system-level and tenant-level data from system 716 that may require sending one or more queries to tenant data storage 722 and/or system data storage 724. System 716 (e.g., an application server 800 in system 716) automatically generates one or more SQL statements (e.g., one or more SQL queries) that are designed to access the desired information. System data storage 724 may generate query plans to access the requested data from the database.
Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined categories. A “table” is one representation of a data object and may be used herein to simplify the conceptual description of objects and custom objects. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or record of a table contains an instance of data for each category defined by the fields. For example, a CRM database may include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table might describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some multi-tenant database systems, standard entity tables might be provided for use by all tenants. For CRM database applications, such standard entities might include tables for Account, Contact, Lead, and Opportunity data, each containing pre-defined fields. It should be understood that the word “entity” may also be used interchangeably herein with “object” and “table”.
In some multi-tenant database systems, tenants may be allowed to create and store custom objects, or they may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. U.S. patent application Ser. No. 10/817,161, filed Apr. 2, 2004, with US Patent granted U.S. Pat. No. 7,779,039, entitled “Custom Entities and Fields in a Multi-Tenant Database System”, and which is hereby incorporated herein by reference, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In certain embodiments, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.
The examples illustrating the use of technology disclosed herein should not be taken as limiting or preferred. The examples are intended to sufficiently illustrate the technology disclosed without being overly complicated and are not intended to illustrate all of the technologies disclosed. A person having ordinary skill in the art will appreciate that there are many potential applications for one or more implementations of this disclosure and hence, the implementations disclosed herein are not intended to limit this disclosure in any fashion.
One or more implementations may be implemented in numerous ways, including as a process, an apparatus, a system, a device, a method, a computer readable medium such as a computer readable storage medium containing computer readable instructions or computer program code, or as a computer program product comprising a computer usable medium having a computer readable program code embodied therein.
Other implementations may include a non-transitory computer readable storage medium storing instructions executable by a processor to perform a method as described above. Yet another implementation may include a system including memory and one or more processors operable to execute instructions, stored in the memory, to perform a method as described above.
Implementations may include:
In some embodiments, a system includes one or more processors for processing of data; a memory for storage of data; an application programming interface (API) to receive requests for price calculations from one or more clients; a pricing service to generate pricing for transactions, wherein, in response to receiving a request for a first transaction from a first client, the first transaction including one or more sales items, including the system to generate a unique transaction identifier, record context data for calculation of the first transaction, calculate a pricing result for each of the one or more sales items, and collect price calculation data representing calculation of each of the one or more sales items, aggregate the pricing results for the one or more sales items to generate a final pricing result for the first transaction, generate a price calculation data set including at least the transaction identifier, the context data for the calculation of the first transaction, and the price calculation data for each of the one or more sales items, and store the price calculation data set in the memory; and a plurality of price data functions, each price data function to perform one or more operations based at least on part on the price calculation data set.
In some embodiments, one or more non-transitory computer-readable storage mediums having stored thereon executable computer program instructions that, when executed by one or more processors, cause the one or more processors to perform operations including receiving a request for a price calculation for a first transaction, the first transaction including one or more sales items; generating a unique transaction identifier; recording context data for calculation of the first transaction; calculating a pricing result for each of the one or more sales items, and collecting price calculation data representing calculation of each of the one or more sales items; aggregating the pricing results for the one or more sales items to generate a final pricing result for the first transaction; generating a price calculation data set including at least the transaction identifier, the context data for the calculation of the first transaction, and the price calculation data for each of the one or more sales items; and, upon receiving a request, performing one or more of a plurality of price data functions, each price data function to perform one or more operations based at least on part on the price calculation data set.
In some embodiments, a method includes receiving a pricing request for a first transaction at a pricing service, the first transaction including a plurality of sales items; generating a unique transaction identifier; recording context data for calculation of the first transaction; calculating a pricing result for each of the plurality of sales items, and collecting price calculation data representing calculation of each of the plurality of sales items; aggregating the pricing results for the plurality of sales items to generate a final pricing result for the first transaction, and collecting calculation data representing the aggregation of the pricing results; automatically generating a price calculation data set including at least the transaction identifier, the context data for the calculation of the first transaction, and the price calculation data for each of the plurality of sales items and for the aggregation of pricing results; and, upon receiving a request, performing one or more of a plurality of price data functions, each price data function to perform one or more operations based at least on part on the price calculation data set.
Embodiments may be provided, for example, as a computer program product which may include one or more machine-readable media (including a non-transitory machine-readable or computer-readable storage medium) having stored thereon machine-executable instructions that, when executed by one or more machines such as a computer, network of computers, or other electronic devices, may result in the one or more machines carrying out operations in accordance with embodiments described herein. A machine-readable medium may include, but is not limited to, floppy diskettes, optical disks, CD-ROMs (Compact Disc-Read Only Memories), and magneto-optical disks, ROMs, RAMs, EPROMs (Erasable Programmable Read Only Memories), EEPROMs (Electrically Erasable Programmable Read Only Memories), magnetic tape, magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing machine-executable instructions.
Moreover, embodiments may be downloaded as a computer program product, wherein the program may be transferred from a remote computer (e.g., a server) to a requesting computer (e.g., a client) by way of one or more data signals embodied in and/or modulated by a carrier wave or other propagation medium via a communication link (e.g., a modem and/or network connection).
It is to be noted that terms like “node”, “computing node”, “server”, “server device”, “cloud computer”, “cloud server”, “cloud server computer”, “machine”, “host machine”, “device”, “computing device”, “computer”, “computing system”, and the like, may be used interchangeably throughout this document. It is to be further noted that terms like “application”, “software application”, “program”, “software program”, “package”, “software package”, and the like, may be used interchangeably throughout this document. Also, terms like “job”, “input”, “request”, “message”, and the like, may be used interchangeably throughout this document.
Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
While concepts been described in terms of several embodiments, those skilled in the art will recognize that embodiments not limited to the embodiments described but can be practiced with modification and alteration within the spirit and scope of the appended claims. The description is thus to be regarded as illustrative instead of limiting.
