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42 Cards in this Set
- Front
- Back
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What information is provided by the descriptive analytics employed at Magpie Sensing?
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Graphical analysis allows users to get a good feel for the situation.
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What type of support is provided by the predictive analytics employed at Magpie Sensing?
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Warning of an open shipment seal is predictive analysis.
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How do prescriptive analytics help in business decision making? |
Magpie Sensing can provide prescriptive recommendations for improving the cold storage processes and business decision making. It helps users dial in the optimal temperature setting and guides equipment purchases. |
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List the components of and explain the Business Pressures–Responses–Support Model.
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The components of the pressure-response-support model are business pressures, companies’ responses to these pressures, and computerized support.
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What are some of the major factors in today's business environment?
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Market-related, Consumer demand-related, Technology-related and Societal
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What are some of the major response activities that organizations take?
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· Employing strategic planning
· Using new and innovative business models · Restructuring of business processes · Participating in business alliances · etc... |
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Define BI.
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BI is an umbrella term that combines architectures, tools, databases, applications, and methodologies. Its major objective is to enable interactive access to data, enable manipulation of these data, and provide business managers and analysts the ability to conduct appropriate analysis.
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List and describe the major components of BI. |
BI systems have four major components: the data warehouse (analogous to the data in the DSS architecture), business analytics and business performance management (together, analogous to models in the DSS architecture), and the user interface (which corresponds to the component of the same name in the DSS architecture). |
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Define OLTP |
OLTP (online transaction processing) is a type of computer processing where the computer responds immediately to user requests. Each request is considered to be a transaction, which is a computerized record of a discrete event, such as the receipt of inventory or a customer order. |
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Define OLAP
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OLAP (online analytical processing) is processing for end-user ad hoc reports, queries, and analysis. Separating the OLTP from analysis and decision support provided by OLAP enables the benefits of BI.
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Define analytics. |
The process of developing actionable decisions or recommendations for actions based upon insights generated from historical data. |
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What is descriptive analytics? What are the various tools that are employed in descriptive analytics? |
This refers to knowing what is happening in the organization and understanding some underlying trends and causes of such occurrences. This involves, first of all, consolidation of data sources and availability of all relevant data in a form that enables appropriate reporting and analysis. From this we can develop appropriate reports, queries, alerts and trends using reporting tools and techniques. |
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How is descriptive analytics different from traditional reporting? |
They can now move toward generating actionable intelligence from their transactional business data. |
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What is a data warehouse? How can data warehousing technology help to enable analytics?
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Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. This provides competitive intelligence and advantage within the company and their market.
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What is predictive analytics? How can organizations employ predictive analytics? |
Use of tools that help determine the probable future outcome for an event or the likelihood of a situation occurring. These tools help identify relationships and patterns. |
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What is prescriptive analytics? What kinds of problems can be solved by prescriptive analytics?
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Used to recognize what is going on as well as likely forecast and make decisions to achieve the best performance possible. The goal is to provide a decision or a recommendation for a specific action.
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What is Big Data analytics? |
Big data analytics is the process of examining large amounts of different data types, or big data, in an effort to uncover hidden patterns, unknown correlations and other useful information. |
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What are the sources of Big Data?
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Major sources of such data are clickstreams from web sites, postings on social media sites, data from traffic, sensors or weather.
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What are the characteristics of Big Data? |
Big Data is data usually in the form of being structured, unstructured, or in a stream and so forth. |
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Why is it important for Isle to have an EDW? |
An enterprise data warehouse (EDW) gathers and provides data needed to tell Isle of Capri what customers respond to, so the casinos can adapt their offerings. The information provided by the EDW lets Isle deepen its understanding of customers, so it can efficiently give them more of the kinds of entertainment they are looking for. |
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What were the business challenges or opportunities that Isle was facing? |
Before implementing the EDW, casino managers had to wait to review monthly data until the second week of the following month. The time lag made it difficult for casinos to identify what actions were appealing to customers in time to respond. |
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What is a data warehouse?
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"...a pool of data produced to support decision making,” and "...a subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management's decision-making process."
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How does a data warehouse differ from a database? |
Technically a data warehouse is a database, albeit with certain characteristics to facilitate its role in decision support.
Most databases are highly normalized, in part to avoid update anomalies. Data warehouses are highly denormalized for performance reasons. |
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What is an ODS? |
Operational Data Store is the database from which a business operates on an on-going basis. |
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Differentiate among a data mart, an ODS, and an EDW.
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- An ODS (Operational Data Store) is the database from which a business operates on an ongoing basis.
- Both an EDW and a data mart are data warehouses. An EDW is an all-encompassing DW that covers all subject areas of interest to the entire organization. - A data mart is a smaller DW designed around one problem, organizational function, topic, or other suitable focus area. |
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Explain the importance of metadata. |
Metadata, “data about data,” are the means through which applications and users access the content of a data warehouse, through which its security is managed, and through which organizational management manages, in the true sense of the word, its information assets. |
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Describe the data warehousing process. |
1. Data are imported from various internal and external sources. 2. Data are cleansed and organized consistently with the organization’s needs. 3. a. Data are loaded into the enterprise data warehouse, or b. Data are loaded into data marts. 4. a. If desired, data marts are created as subsets of the EDW, or b. The data marts are consolidated into the EDW. 5. Analyses are performed as needed |
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Describe the major components of a data warehouse.
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Data sources - Data are sourced from operational systems and possibly from external data sources.
Data extraction - Data are extracted using custom-written or commercial software called ETL. Data loading - Data are loaded into a staging area, where they are transformed and cleansed. The data are then ready to load into the data warehouse. Comprehensive database - This is the EDW that supports decision analysis by providing relevant summarized and detailed information. Metadata - Metadata are maintained for access by IT personnel and users. Metadata include rules for organizing data summaries that are easy to index and search. Middleware tools - Middleware tools enable access to the data warehouse from a variety of front-end applications. |
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List the alternative data warehousing architectures discussed in this section. |
Independent data marts, data mart bus architecture, hub-and-spoke architecture, centralized data warehouse, federated data warehouse |
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Which data warehousing architecture is the best? Why?
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No claims can be made for a particular architecture's superiority over the others.
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Describe data integration. |
Comprises of three major processes that, when correctly implemented, permit data to be accessed and made accessible to an array of ETL and analysis tools and the data warehousing environment: data access, data federation, and change capture. |
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Describe the three steps of the ETL process. |
Extraction - reading data from one or more databases Transformation - converting the extracted data from its previous form into the form in which it need to be so that it can be placed into a data warehouse or simply into another database Load - putting data into the data warehouse |
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Why is the ETL process so important for data warehousing efforts? |
This process is important because it is designed to load the warehouse with integrated and cleansed data. |
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Compare: DBMS and Data Warehouse |
-DBMS, highly normalized, less redundancy, minimize transaction processing time, individual records
-DW, not normalized, lots of redundancy, minimize analysis processing time, summarized data |
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Compare: ER diagrams vs. Star Schema
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-all of the foreign keys of star schema are in the facts table
-ER diagrams don't show where to put foreign/primary keys |
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Normalization vs. Redundancy |
-for analysis purpose |
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Compare: TPS (Transaction Processing System) vs. DSS (Decision Support System) |
-TPS automates handling of data about business activities
-DSS provides interactive environment for decision making
-TPS is for DBMS, where DSS is for Data Warehouse |
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Compare: OLTP (Online Transaction Processing) vs. OLAP (Online Analytical Processing)
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-OLTP are constantly involved in handling updates, handles routine on-going business
-OLAP systems are involved in extracting information from data stored by OLTP systems and provide correct information in a timely manner |
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Four main characteristics of Data Warehousing |
* Subject oriented * Integrated * Time-variant * Nonvolatile |
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Architectures |
-Independent data mart -Data mart bus -Hub-and-spoke -Centralized -Federated |
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Architecture |
Descriptive Predictive Prescriptive |
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Differences |
Analytics or Data Sciences |
