Understanding time variance
One required feature of a data warehouse is for it to be "Time Variant", giving us the ability to store data representative as it existed at many points in time in the past. Granularity of time variance and the tracking of changing data over time depends upon the needs of the business and can range from representing data values at the time they are changed on up to any periodic inspection/detection interval (hourly, daily, weekly, monthly).
Time variance allows us to join transaction data to reference data that contains values representative of the time of the event. For example; When a customer changes their address in a sales system, that sales system would just update the address. A data warehouse though would have processes that detect that change and then track that change allowing us to see the customers address before and after that change. This allows us to then tie any sales events to the customer information that was active at the time of the sales event. This would allow you to report sales totals by the city of where the customers lived at the time of the sale, as opposed to sales by city based on where everyone currently lives.
Time variance also allows us to adapt to future changes and accurately report information when data changes in the future. For example; If we use a sales type code of 45 that would mean "Sales to General Public" on our sales orders, any future changes to how we describe that code might change the context of past orders. Consider if we change the code 45 another meaning to "Sales to Free Membership Individuals". Does that mean that any past sales orders with sales-type code 45 are not "Sales to General Public" and are now "Sales to Free Membership"? Having time variance in place, allows the flexibility to either apply the description of the code active at the time of the sale or just use the new code to categorize all past sales.
Customer relationship management (CRM) is a process in which a business or other organization administers its interactions with customers, typically using data analysis to study large amounts of information.
E-commerce is the activity of electronically buying or selling of products on online services or over the Internet. The term was coined and first employed by Dr. Robert Jacobson, Principal Consultant to the California State Assembly's Utilities & Commerce Committee, in the title and text of California's Electronic Commerce Act, carried by the late Commmittee Chairwoman Gwen Moore (D-L.A.) and enacted in 1984. Electronic commerce draws on technologies such as mobile commerce, electronic funds transfer, supply chain management, Internet marketing, online transaction processing, electronic data interchange (EDI), inventory management systems, and automated data collection systems. E-commerce is in turn driven by the technological advances of the semiconductor industry, and is the largest sector of the electronics industry.
Amazon.com, Inc. is an American multinational technology company based in Seattle, Washington, which focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is one of the Big Five companies in the U.S. information technology industry, along with Google, Apple, Microsoft, and Facebook. The company has been referred to as "one of the most influential economic and cultural forces in the world", as well as the world's most valuable brand.
Inventory or stock refers to the goods and materials that a business holds for the ultimate goal of resale, production or utilisation.
Print on demand (POD) is a printing technology and business process in which book copies are not printed until the company receives an order, allowing prints of single or small quantities. While other industries established the build to order business model, "print on demand" could only develop after the beginning of digital printing, because it was not economical to print single copies using traditional printing technology such as letterpress and offset printing.
The point of sale (POS) or point of purchase (POP) is the time and place where a retail transaction is completed. At the point of sale, the merchant calculates the amount owed by the customer, indicates that amount, may prepare an invoice for the customer, and indicates the options for the customer to make payment. It is also the point at which a customer makes a payment to the merchant in exchange for goods or after provision of a service. After receiving payment, the merchant may issue a receipt for the transaction, which is usually printed but can also be dispensed with or sent electronically.
In computing, extract, transform, load (ETL) is the general procedure of copying data from one or more sources into a destination system which represents the data differently from the source(s) or in a different context than the source(s). The ETL process became a popular concept in the 1970s and is often used in data warehousing.
A marketing plan may be part of an overall business plan. Solid marketing strategy is the foundation of a well-written marketing plan so that goals may be achieved. While a marketing plan contains a list of actions, without a sound strategic foundation, it is of little use to a business.
Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
Direct marketing is a form of communicating an offer, where organizations communicate directly to a pre-selected customer and supply a method for a direct response. Among practitioners, it is also known as direct response marketing. By contrast, advertising is of a mass-message nature.
Microsoft Dynamics GP is a mid-market business accounting software or ERP software package marketed in North and South America, UK and Ireland, the Middle East, Singapore, Australia and New Zealand. It is used in many additional countries with partner supported localizations. It uses either Microsoft SQL Server 2005, 2008, 2012, 2014 or 2016 to store data. It is one of four accounting packages acquired by Microsoft that now share the Microsoft Dynamics Business Solutions brand. Dynamics GP is written in a language called Dexterity.
Online shopping is a form of electronic commerce which allows consumers to directly buy goods or services from a seller over the Internet using a web browser or a mobile app. Consumers find a product of interest by visiting the website of the retailer directly or by searching among alternative vendors using a shopping search engine, which displays the same product's availability and pricing at different e-retailers. As of 2020, customers can shop online using a range of different computers and devices, including desktop computers, laptops, tablet computers and smartphones.
A performance indicator or key performance indicator (KPI) is a type of performance measurement. KPIs evaluate the success of an organization or of a particular activity in which it engages.
A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time.
Data cleansing or data cleaning is the process of detecting and correcting corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting.
Supply-chain optimization (SCO) aims to ensure the optimal operation of a manufacturing and distribution supply chain. This includes the optimal placement of inventory within the supply chain, minimizing operating costs including manufacturing costs, transportation costs, and distribution costs. Optimization often involves the application of mathematical modelling techniques using computer software. It is often considered to be part of supply chain engineering, although the latter is mainly focused on mathematical modelling approaches, whereas supply chain optimization can also be undertaken using qualitative, management based approaches.
In information systems design and theory, single source of truth (SSOT) is the practice of structuring information models and associated data schema such that every data element is mastered in only one place. Any possible linkages to this data element are by reference only. Because all other locations of the data just refer back to the primary "source of truth" location, updates to the data element in the primary location propagate to the entire system without the possibility of a duplicate value somewhere being forgotten.
Starting in 1946, American Airlines developed a number of automated airline booking systems known as Reservisor. Although somewhat successful, American's unhappiness with the Reservisor systems led them to develop the computerized Sabre system used to this day.
Event-driven SOA is a form of service-oriented architecture (SOA), combining the intelligence and proactiveness of event-driven architecture with the organizational capabilities found in service offerings. Before event-driven SOA, the typical SOA platform orchestrated services centrally, through pre-defined business processes, assuming that what should have already been triggered is defined in a business process. This older approach does not account for events that occur across, or outside of, specific business processes. Thus complex events, in which a pattern of activities—both non-scheduled and scheduled—should trigger a set of services is not accounted for in traditional SOA 1.0 architecture.
Behavioral analytics is a recent advancement in business analytics that reveals new insights into the behavior of consumers on eCommerce platforms, online games, web and mobile applications, and IoT. The rapid increase in the volume of raw event data generated by the digital world enables methods that go beyond typical analysis by demographics and other traditional metrics that tell us what kind of people took what actions in the past. Behavioral analysis focuses on understanding how consumers act and why, enabling accurate predictions about how they are likely to act in the future. It enables marketers to make the right offers to the right consumer segments at the right time.
