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The advantages of SSOT architectures include easier prevention of mistaken inconsistencies (such as a duplicate value/copy somewhere being forgotten), and greatly simplified version control. Without a SSOT, dealing with inconsistencies implies either complex and error-prone consensus algorithms, or using a simpler architecture that's liable to lose data in the face of inconsistency (the latter may seem unacceptable but it is sometimes a very good choice; it is how most blockchains operate: a transaction is actually final only if it was included in the next block that is mined).
Deployment of an SSOT architecture is becoming increasingly important in enterprise settings where incorrectly linked duplicate or de-normalized data elements (a direct consequence of intentional or unintentional denormalization of any explicit data model) pose a risk for retrieval of outdated, and therefore incorrect, information. Common examples (i.e., example classes of implementation) are as follows:
An acknowledged prerequisite (of the notion that any given single source of truth can exist) is that it depends on the ontologic condition that no more than a single truth (about any particular fact or idea) exists, an assertion that is ontologic in both the IT sense and the general sense of that word. In many instances, this presents no problem (for example, within particular namespaces, or even across them, as long as naming collisions or broader name conflicts are adequately handled). The broadest contexts (and thus thorniest, regarding ontologic discrepancies) require adequate epistemic regime comparison and reconciliation (or at least negotiation or transactional exchanges). An archetypal example of this class of reconciliation is that two theological seminary libraries, from two different religions (X and Y), could exchange information with an SSOT architecture, but the unification of truth would reside on the level of the statement that "religion X asserts that God is purple whereas religion Y asserts that God is green", rather than on the level of "God is purple" or "God is green".
An ideal implementation of SSOT is rarely possible in most enterprises. This is because many organisations have multiple information systems, each of which needs access to data relating to the same entities (e.g., customer). Often these systems are purchased as commercial off-the-shelf products from vendors and cannot be modified in trivial ways. Each of these various systems therefore needs to store its own version of common data or entities, and therefore each system must retain its own copy of a record (hence immediately violating the SSOT approach defined above). For example, an enterprise resource planning (ERP) system (such as SAP or Oracle e-Business Suite) may store a customer record; the customer relationship management (CRM) system also needs a copy of the customer record (or part of it) and the warehouse dispatch system might also need a copy of some or all of the customer data (e.g., shipping address). In cases where vendors do not support such modifications, it is not always possible to replace these records with pointers to the SSOT.
For organisations (with more than one information system) wishing to implement a Single Source of Truth (without modifying all but one master system to store pointers to other systems for all entities), some supporting architectures are:
An MDM system can act as the source of truth for any given entity that might not necessarily have an alternative "source of truth" in another system. Typically the MDM acts as a hub for multiple systems, many of which could allow (be the source of truth for) updates to different aspects of information on a given entity. For example, the CRM system may be the "source of truth" for most aspects of the customer, and is updated by a call centre operator. However, a customer may (for example) also update their address via a customer service web site, with a different back-end database from the CRM system. The MDM application receives updates from multiple sources, acts as a broker to determine which updates are to be regarded as authoritative (the golden record) and then syndicates this updated data to all subscribing systems. The MDM application normally requires an ESB to syndicate its data to multiple subscribing systems.[2]
In event oriented architectures, it has become increasingly common to find an implementation of the Event Sourcing pattern which stores the system state as an ordered sequence of state changes.[3] To do this, you need an Event Store, a particular type of database designed to hold all the events that change the state of the system. The event store in an Event Sourcing + Command Query Responsibility Separation + Domain Driven Design + Messaging architecture is in fact a "single source of truth", with the additional advantage that it can also act as an Enterprise Service Bus as it can listen directly to the event store for status changes as everything passes by. In addition, by saving all the events, it also plays the role of Data Warehouse. One last advantage is that through this system the Shared Database pattern can be implemented, another technique not mentioned to obtain a single source of truth.
While the primary purpose of a data warehouse is to support reporting and analysis of data that has been combined from multiple sources, the fact that such data has been combined (according to business logic embedded in the data transformation and integration processes) means that the data warehouse is often used as a de facto SSOT. Generally, however, the data available from the data warehouse are not used to update other systems; rather the DW becomes the "single source of truth" for reporting to multiple stakeholders. In this context, the Data Warehouse is more correctly referred to as a "single version of the truth" since other versions of the truth exist in its operational data sources (no data originates in the DW; it is simply a reporting mechanism for data loaded from operational systems).[4]
In software design, the same schema, business logic and other components are often repeated in multiple different contexts, while each version refers to itself as "Source Code". To address this problem, the concepts of SSOT can also be applied to software development principles using processes like recursive transcompiling to iteratively turn a single source of truth into many different kinds of source code, which will match each other structurally because they are all derived from the same SSOT.[5]
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It's no secret that the accounting profession has been slow to adapt to computer technology. The only exceptions have been CPAs' early use of computerized spreadsheet, word processing and tax preparation software.
In the last few years, most CPAs have played catch-up. Some, to their cha grin, have even rushed to try the very latest-and often untested-technology only to discover that they would have been wiser to stick to tried-and-true applications.
This article focuses on five very practical, well-proven technologies that CPAs in all areas of the profession should be using now. If you aren't applying all of them, you're not armed with the most efficient professional tools. In fact, if you aren't familiar with any of them, then you seriously lag behind the times and owe it to yourself, your employer or your clients to get on track with them.
Building skills in technology is vital because it will help you become more productive and valuable as a professional. The best way to build expertise with computer tools is to set aside at least two hours a week to learn something new or practice an application you already have.
The major benefit of the new Windows operating systems is multitasking, a technology that allows computers to do more than one job at a time. As if that's not enough, it performs those simultaneous chores with relative data safety. Some perspective: Nearly all software application programs "crash," or freeze up, at one time or another. In earlier versions of Windows (Windows 3.x), such an event typically stalls not only the application but also brings down the entire computer; when that happens, the computer must be rebooted (turned off and then on again). Such a drastic step often results in lost data.
Windows 95 and NT boast numerous other improvements. For example, file names no longer are limited to 11 characters (8 plus 3); they can be as long as 255 characters. Also, Windows 95 and NT manage random-access memory (RAM) more efficiently. In Windows 3.x, it was not enough just to have ample memory. That memory had to be managed properly, usually by other software, or the computer could not access it and the applications that needed memory could not run.
Also, in general the new Windows operating systems run much faster than the earlier versions. Windows 95 and NT can operate on any personal computer as long as it's at least a 386SX. However, compared with newer computers, software runs sluggishly on a 386. As a practical matter, the minimum configuration should be a 486, 50 megahertz (MHz) machine with 16 megabytes (Mb) of RAM, although offices today really should be equipped with Pentium (also referred to as 586) computers.
Windows 95 is designed to handle both a standalone computer and a small network. The network module is built in and can handle as many as 10 computers set up with a file server (a single, powerful computer that delivers application software and files to the various workstations on the network).
When set up as a peer-to-peer network (where each computer can access all the others on the network), Windows 95 can support at least 10 users. However, if the applications being run on the network are not resource-intensive (such as a low-end accounting or tax package), the number of concurrent users can rise to about 35. But if a resource-intensive application, such as a high-end accounting program, is run on the peer-to-peer network, then 10 users is the maximum.
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