...OLAP In computing, online analytical processing, or OLAP ( /ˈoʊlæp/), is an approach to answering multi-dimensional analytical (MDA) queries swiftly.[1] OLAP is part of the broader category of business intelligence, which also encompasses relational database report writing and data mining.[2] Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM),[3] budgeting and forecasting, financial reporting and similar areas, with new applications coming up, such as agriculture.[4] The term OLAP was created as a slight modification of the traditional database term OLTP (Online Transaction Processing).[5] OLAP tools enable users to analyze multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing.[6] Consolidation involves the aggregation of data that can be accumulated and computed in one or more dimensions. For example, all sales offices are rolled up to the sales department or sales division to anticipate sales trends. By contrast, the drill-down is a technique that allows users to navigate through the details. For instance, users can view the sales by individual products that make up a region’s sales. Slicing and dicing is a feature whereby users can take out (slicing) a specific set of data of the OLAP cube and view (dicing) the slices from different viewpoints. Databases configured...
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...Question: Give examples of how OLAP works and its Predictive Analytics INTRODUCTION On-line analytical Processing (OLAP) refers to a computer-based processing with a capability of manipulating and analyzing large volumes of data from multiple perspectives (different points of view). It is one technique you can use to transform data into information. The original system of the OLAP is also known as the multi-dimensional cube or hyper cube. For example, a user can request that data be analyzed to display a spread-sheet showing all of a company's products sold in Ghana in the month of January, compare revenue figures with those for the same products in March, and then see a comparison of other product sales in Ghana in the same time period. Historical Background The first fully functional on-line analytical system was introduced in 1970 by Express, and later in 1995, the Oracle acquired the release for the resource of information. The formal launching for acquisition of OLAP was held in 2007. Oracle also released its own system called Essbase using the OLAP theoretical background and functionality. In 1998, Microsoft stepped in for upgrading and advancement in the OLAP technology. Microsoft worked on the mainstream idea and developed highly advanced online analytical system that is deployed in many large organizations today. Types of OLAP There are 3 types of the on-line analytical systems each with different properties according to the level of use. Multi-dimensional OLAP ...
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...have been established and maintaining long term relationships with leading enterprise in primary metals, metalworking, and other basic process industries all over the world. Quaker is a $544.1 million dollar company. The company is publicly traded on the New York Stock exchange, and has a long track record of financial consistency and strength. Today, they have business and production presence in every major manufacturing country in the world. Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. (Search Data Management, searchdatamanagement.techtarget.com). Hillman group is the manufacturer and distributor of engraving technologies and hardware. Jim Honerkamp is the CIO of...
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...(a) What is Data Mining? What is OLAP? How is data mining different from OLAP? Data mining: Data mining is essential utilized today by organizations with an in number buyer center retail, budgetary, correspondence, and promoting associations. It empowers these organizations to figure out relationships around "interior" components, for example, value, item positioning, or staff abilities, and "outer" variables, for example, financial pointers, rivalry, and client demographics. Also, it empowers them to figure out the effect on deals, client fulfillment, and corporate benefits. At long last, it empowers them to "penetrate down" into synopsis data to view part transactional information. OLAP: OLAP stays for Online Analytical Processing and is designing used to accumulate, regulate and process multidimensional data and outfit brisk access to this data for demonstrative purposes. OLAP is for the most part used inside business reporting for promoting, deals, human possession organization and diverse business fields. OLAP mulls over brisk execution of complex database requests continuously. OLAP energizes complex data sees through data turning, complex data transforming, and data showing. OLAP manages dimensional information, which takes into account much quicker execution of complex database inquiries contrasted with social database administration frameworks. The information structure that OLAP make from the social information is called OLAP block. OLAP solid shapes might be...
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...Open Object Business Intelligence Release 1.0 Tiny SPRL 2009-04-09 CONTENTS i ii Open Object Business Intelligence, Release 1.0 I 1 2 Part 1 : Introduction Goal of the project What is for User? 2.1 2.2 2.3 For the end-user: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . For the administrator user: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . For the developer: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 7 9 9 9 9 11 12 15 3 OLAP 3.1 Who uses OLAP and Why? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Terminologies II 5 6 Part 2 : Architecture Schema Components 6.1 6.2 6.3 6.4 6.5 6.6 The Cube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The CLI interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cube Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Web Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The OpenOffice plugin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Open ERP interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 19 21 21 21 21 22 22 22 23 25 26 7 Extra libraries 8 Introduction to the OpenObject Module 8.1...
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...מערכות מידע שאלות בחינה לדוגמא 1. למה משמשת מערכת לניהול מסדי נתונים DBMS? שילוב רשומות נתונים למערכת אחת נגישות גבוהה ומהירה לנתונים שינויים במבני הנתונים ממשק בין המשתמשים ובין מסד הנתונים 2. מהו ההבדל בין האינטראנט והאקסטרנט? האינטראנט יותר חסכוני מהאקסטרנט האינטראנט מיועד לקהל הרחב ללא הגבלה לעומת האקסטרנט האינטראנט מאפשר תקשורת פנימית של הארגון והאקסטרנט מאפשר תקשורת חיצונית בין שותפים עסקיים אין הבדל 3 מה ההבדל בין עיבוד OLTP לבין עיבוד OLAP? OLAP מתבצע כשלב מכין והכרחי לפני OLTP OLAP מתחקר נתונים בבסיס הנתונים OLTP ;מעדכן נתונים במחסן הנתונים ההבדל בין צורות העיבוד נובע ממהירות הביצוע והאיכות OLAP מתחקר נתונים במחסן הנתוניםOLTP ; רושם נתונים בבסיס הנתונים 4. מהם תפקידיה של מערכת TPS ? הצגת נתונים חריגים לדרג הניהולי הבכיר איתור כשלים אירגוניים ו/או ניהוליים איסוף ורישום נתונים על אירועים, קליטתם ואימותם כל התשובות נכונות 5. מה זה SQL? שפת דור רביעי המהווה תקן לעיבוד המידע במערכות בסיסי נתונים בקשה לקבלת הצעות לפיתוח תקשורת. מערכת מידע להנהלה הבכירה. אף תשובה אינה נכונה. 6. איזה מהבאים מתייחס לדרג ניהול נמוך? מידע סיכומי. מידע חיצוני. מידע מפורט. מידע גרפי. 7. גישת מחזור החיים (SDLC) – מפל המים: יקרה לביצוע. עלולה להסתיים בחוסר התאמת המערכת לצרכים עקב התמשכות תהליך הפיתוח. מאופיינת בסדר פעולות קשיח. כל התשובות נכונות 8. מערכת העושה שימוש בממשק מולטימדיה, התרעות בזמן אמת, וניתוח לעומק Drill Dow EIS/ESS MIS TPS אף תשובה אינה נכונה. 9. מרכיבי מערכת DSS אחסון נתונים, הרצת מודלים אנליטיים...
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...гиперкубом или метакубом), оси которого содержат параметры, а ячейки – зависящие от них агрегатные данные – причем храниться такие данные могут и в реляционных таблицах, но в данном случае мы говорим о логической организации данных, а не о физической реализации их хранения). Вдоль каждой оси данные могут быть организованы в виде иерархии, представляющей различные уровни их детализации. Благодаря такой модели данных пользователи могут формулировать сложные запросы, генерировать отчеты, получать подмножества данных. Технология комплексного многомерного анализа данных получила название OLAP (On-Line Analytical Processing). OLAP – это ключевой компонент организации хранилищ данных. Концепция OLAP была описана в 1993 году Эдгаром Коддом, известным исследователем баз данных и автором реляционной модели данных (см. E.F. Codd, S.B. Codd, and C.T.Salley, Providing OLAP (on-line analytical processing) to user-analysts: An IT mandate. Technical report, 1993). В 1995 году на основе требований, изложенных Коддом, был...
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...72384831 reciept number…. Database: Collected of records with helps in decision-making process. A database is an organized collection of data. The data are typically organized to model aspects of reality in a way that supports processes requiring information. For example, modelling the availability of rooms in hotels in a way that supports finding a hotel with vacancies. Database management systems (DBMSs) are computer software applications that interact with the user, other applications, and the database itself to capture and analyze data. A general-purpose DBMS is designed to allow the definition, creation, querying, update, and administration of databases. Well-known DBMSs include MySQL, PostgreSQL, Microsoft SQL Server, Oracle,SAP and IBM DB2. A database is not generally portable across different DBMSs, but different DBMSs can interoperate by using standards such as SQL and ODBC or JDBC to allow a single application to work with more than one DBMS. Data warehousing : A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process. Subject-Oriented: A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject. Integrated: A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single...
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...Top Data Management Terms to Know Fifteen essential definitions you need to know Fifteen Essential Data Management Terms We know it’s not always easy to keep up-to-date Contents with the latest data management terms. That’s why we have put together the top fifteen terms and definitions that you and your peers need to know. OLAP (online analytical processing) Star schema What is OLAP (online analytical processing) Fact table OLAP (online analytical processing) is computer processing that enables a Big data analytics Data modeling Ad hoc analysis user to easily and selectively extract and view data from different points of view. For example, a user can request that data be analyzed to display a spreadsheet showing all of a company's beach ball products sold in Florida in the month of July, compare revenue figures with those for the same products in September, and then see a comparison of other product sales in Data visualization Extract, transform, load (ETL) Florida in the same time period. To facilitate this kind of analysis, OLAP data is stored in a multidimensional database. Whereas a relational database can be thought of as two-dimensional, a multidimensional database considers each data attribute (such as product, geographic sales region, and time Association rules (in data mining) Relational database period) as a separate "dimension." OLAP software can locate the intersection of dimensions (all products sold in the...
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...information systems, levels of management decision-making and information systems that enhance the value of information. Students are encouraged to understand the reasons for the development of an information system and its replacement; these will help you identify the benefits and limitations of each type of information system. From EDP to MIS Until the 1960s, the role of most information systems was simple. They were mainly used for electronic data processing (EDP),purposes such as transactions processing, record-keeping and accounting. EDP is often defined as the use of computers in recording, classifying, manipulating, and summarizing data. It is also called transaction processing systems (TPS), automatic data processing, or information processing. Transaction processing systems – these process data resulting from business transactions, update operational databases, and produce business documents. Examples: sales and inventory processing and accounting systems. In the 1960s, another role was added to the use of computers: the processing of data into useful informative reports. The concept of management information systems (MIS) was born. This new role focused on developing business applications that provided managerial end users with predefined management reports that would give managers the information they needed for decision-making purposes. Management information systems – provide information in the form of prespecified reports and displays to support business decisionmaking...
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...LP3 Assignment: Database Applications | Amy Bedard | | MT3500 | 10/24/2015 | A data warehouse is a relational database that is designed to help companies analyze data. It usually contains historical data derived from transaction data, but it can include data from other sources. Data warehouses are defined by subject matter and they enable an organization to consolidate data from several sources. They have the ability to hold multiple subject areas of very detailed information that works to integrate all data sources. A data warehouse environment also includes an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users. A data mart is a simple form of a data warehouse that is focused on a single subject or area of a company such as Sales, Finance, or Marketing. Data marts are often built and controlled by a single department within an organization. The sources could be internal operational systems, a central data warehouse, or external data. Compared to a data warehouse, a data mart often holds a single subject area of summarized information that concentrates on integrating information from one particular subject area. Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis of data warehouses...
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...coming from sources like Facebook, Twitter, RFID readers, sensors, and so on. Your management wants to derive information from both the relational data and the unstructured data and wants this information as soon as possible. What should you do? Hadoop may be the answer! What is Hadoop? Hadoop is an open source project of the Apache Foundation. It is a framework written in Java originally developed by Doug Cutting who named it after his son's toy elephant. Hadoop uses Google’s MapReduce and Google File System technologies as its foundation. It is optimized to handle massive quantities of data which could be structured, unstructured or semi-structured, using commodity hardware, that is, relatively inexpensive computers. This massive parallel processing is done with great performance. Hadoop replicates its data across multiple computers, so that if one goes down, the data is processed on one of the replicated computers. It is a batch operation handling massive quantities of data, so...
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...Week 3 Tutorial Exercise Introduction to Data Warehousing Task 1 Answer to Discussion Question: * How is a data warehouse different from a database? Ans : Data Warehouse 1. Used for Online Analytical Processing (OLAP). This reads the historical data for the Users for business decisions. 2. The Tables and joins are simple since they are de-normalized. This is done to reduce the response time for analytical queries. 3. Data – Modelling techniques are used for the Data Warehouse design. 4. Optimized for read operations. 5. High performance for analytical queries. 6. Is usually a Database. Database 1. Used for Online Transactional Processing (OLTP) but can be used for other purposes such as Data Warehousing. This records the data from the user for history. 2. The tables and joins are complex since they are normalized (for RDMS). This is done to reduce redundant data and to save storage space. 3. Entity – Relational modeling techniques are used for RDMS database design. 4. Optimized for write operation. 5. Performance is low for analysis queries. * Describe the major components of a data warehouse. * Ans: 1. Multi Dimensional Data: * Data Mart are normally a multi dimensional database using industry standard STAR Schema approach. This will include: * Dimensions tables * Fact Tables * Hierarchies (For Drill down and drill across) * Role Models (Multiple references of Dimension to...
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...collecting, consolidating, and organizing data for reporting and analysis with tools such as online analytical processing (OLAP) and data mining. Although data warehouses are built on relational database technology, the design of a data warehouse database differs substantially from the design of an online transaction processing system (OLTP) database. The topics in this paper address approaches and choices to be considered when designing and implementing a data warehouse. The paper begins by contrasting data warehouse databases with OLTP databases and introducing OLAP and data mining, and then adds information about design issues to be considered when developing a data warehouse with Microsoft® SQL Server™ 2000. A data warehouse supports an OLTP system by providing a place for the OLTP database to offload data as it accumulates, and by providing services that would complicate and degrade OLTP operations if they were performed in the OLTP database. Without a data warehouse to hold historical information, data is archived to static media such as magnetic tape, or allowed to accumulate in the OLTP database. If data is simply archived for preservation, it is not available or organized for use by analysts and decision makers. If data is allowed to accumulate in the OLTP so it can be used for analysis, the OLTP database continues to grow in size and requires more indexes to service analytical and report queries. These queries access and process large portions of the continually growing...
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...report, we’ll identify what SCM is, the difference it makes between real-time processing versus analytical processing. Then we will identify the benefits it will bring to the Rainforest Company and how to get an edge in the competitive global market. In order to understand SCM, we must first describe what it actually is. Supply Chain Management (SCM) is a system that includes planning, executing and controlling all activities involved in raw material sourcing and procurement, converting raw materials to finished products, and warehousing and delivering finished products to customers. (Stair and Reynolds, 2012, p. 389). In other words, it is a system that bridges the gap between the manufacturer and the consumer by supplying goods and services without the intervention of a retailer such as a department or grocery store. In an attempt to put this in perspective, we looked into the activity of Amazon.Com and how their process works from the supplier to finally reaching the consumer. When looking into the supply chain structure and strategies of Amazon.com’s website, we discovered that their methodology is much similar to most companies that exercise the SCM system method ranging from suppliers, subcontractors and manufacturers all the way to transporters, warehouses, retailers and finally the customer. Jeff Bezos, who founded Amazon.com, Inc. back in 1994, originally started his vision as an online bookstore. Later, they soon diversified by selling DVDs, CDs, MP3 downloads...
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