A Realistic Data Warehouse Project: an Integration of Microsoft Access® and Microsoft Excel® Advanced Features and Skills
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Cubes Documentation Release 1.0.1
Cubes Documentation Release 1.0.1 Stefan Urbanek April 07, 2015 Contents 1 Getting Started 3 1.1 Introduction.............................................3 1.2 Installation..............................................5 1.3 Tutorial................................................6 1.4 Credits................................................9 2 Data Modeling 11 2.1 Logical Model and Metadata..................................... 11 2.2 Schemas and Models......................................... 25 2.3 Localization............................................. 38 3 Aggregation, Slicing and Dicing 41 3.1 Slicing and Dicing.......................................... 41 3.2 Data Formatters........................................... 45 4 Analytical Workspace 47 4.1 Analytical Workspace........................................ 47 4.2 Authorization and Authentication.................................. 49 4.3 Configuration............................................. 50 5 Slicer Server and Tool 57 5.1 OLAP Server............................................. 57 5.2 Server Deployment.......................................... 70 5.3 slicer - Command Line Tool..................................... 71 6 Backends 77 6.1 SQL Backend............................................. 77 6.2 MongoDB Backend......................................... 89 6.3 Google Analytics Backend...................................... 90 6.4 Mixpanel Backend.......................................... 92 6.5 Slicer Server............................................. 94 7 Recipes 97 7.1 Recipes............................................... -
Normalized Form Snowflake Schema
Normalized Form Snowflake Schema Half-pound and unascertainable Wood never rhubarbs confoundedly when Filbert snore his sloop. Vertebrate or leewardtongue-in-cheek, after Hazel Lennie compartmentalized never shreddings transcendentally, any misreckonings! quite Crystalloiddiverted. Euclid grabbles no yorks adhered The star schemas in this does not have all revenue for this When done use When doing table contains less sensible of rows Snowflake Normalizationde-normalization Dimension tables are in normalized form the fact. Difference between Star Schema & Snow Flake Schema. The major difference between the snowflake and star schema models is slot the dimension tables of the snowflake model may want kept in normalized form to. Typically most of carbon fact tables in this star schema are in the third normal form while dimensional tables are de-normalized second normal. A relation is danger to pause in First Normal Form should each attribute increase the. The model is lazy in single third normal form 1141 Options to Normalize Assume that too are 500000 product dimension rows These products fall under 500. Hottest 'snowflake-schema' Answers Stack Overflow. Learn together is Star Schema Snowflake Schema And the Difference. For step three within the warehouses we tested Redshift Snowflake and Bigquery. On whose other hand snowflake schema is in normalized form. The CWM repository schema is a standalone product that other products can shareeach product owns only. The main difference between in two is normalization. Families of normalized form snowflake schema snowflake. Star and Snowflake Schema in Data line with Examples. Is spread the dimension tables in the snowflake schema are normalized. Like price weight speed and quantitiesie data execute a numerical format. -
The Design of Multidimensional Data Model Using Principles of the Anchor Data Modeling: an Assessment of Experimental Approach Based on Query Execution Performance
WSEAS TRANSACTIONS on COMPUTERS Radek Němec, František Zapletal The Design of Multidimensional Data Model Using Principles of the Anchor Data Modeling: An Assessment of Experimental Approach Based on Query Execution Performance RADEK NĚMEC, FRANTIŠEK ZAPLETAL Department of Systems Engineering Faculty of Economics, VŠB - Technical University of Ostrava Sokolská třída 33, 701 21 Ostrava CZECH REPUBLIC [email protected], [email protected] Abstract: - The decision making processes need to reflect changes in the business world in a multidimensional way. This includes also similar way of viewing the data for carrying out key decisions that ensure competitiveness of the business. In this paper we focus on the Business Intelligence system as a main toolset that helps in carrying out complex decisions and which requires multidimensional view of data for this purpose. We propose a novel experimental approach to the design a multidimensional data model that uses principles of the anchor modeling technique. The proposed approach is expected to bring several benefits like better query execution performance, better support for temporal querying and several others. We provide assessment of this approach mainly from the query execution performance perspective in this paper. The emphasis is placed on the assessment of this technique as a potential innovative approach for the field of the data warehousing with some implicit principles that could make the process of the design, implementation and maintenance of the data warehouse more effective. The query performance testing was performed in the row-oriented database environment using a sample of 10 star queries executed in the environment of 10 sample multidimensional data models. -
(BI) Using MS Excel Powerpivot
2018 ASCUE Proceedings Developing an Introductory Class in Business Intelligence (BI) Using MS Excel Powerpivot Dr. Sam Hijazi Trevor Curtis Texas Lutheran University 1000 West Court Street Seguin, Texas 78130 [email protected] Abstract Asking questions about your data is a constant application of all business organizations. To facilitate decision making and improve business performance, a business intelligence application must be an in- tegral part of everyday management practices. Microsoft Excel added PowerPivot and PowerPivot offi- cially to facilitate this process with minimum cost, knowing that many business people are already fa- miliar with MS Excel. This paper will design an introductory class to business intelligence (BI) using Excel PowerPivot. If an educator decides to adopt this paper for teaching an introductory BI class, students should have previ- ous familiarity with Excel’s functions and formulas. This paper will focus on four significant phases all students need to complete in a three-credit class. First, students must understand the process of achiev- ing small database normalization and how to bring these tables to Excel or develop them directly within Excel PowerPivot. This paper will walk the reader through these steps to complete the task of creating the normalization, along with the linking and bringing the tables and their relationships to excel. Sec- ond, an introduction to Data Analysis Expression (DAX) will be discussed. Introduction It is not that difficult to realize the increase in the amount of data we have generated in the recent memory of our existence as a human race. To realize that more than 90% of the world’s data has been amassed in the past two years alone (Vidas M.) is to realize the need to manage such volume. -
Calculated Field in Pivot Table Data Model
Calculated Field In Pivot Table Data Model Frostbitten and unjaundiced Eddie always counteracts d'accord and cowl his tana. New-fashioned and goniometrically,anarchical Ronny however never swop potentiometric his belittlement! Torre enunciatedRevolved Gordan harmonically tunneling or beat-up. or gimlets some doxologies In regular Pivot Tables, you can group numeric, data or text fields. Product of Reliable Bioreactors on Site. Here are exclusive to model in pivot calculated field table data model that data model and used when creating pivot. Power Query, Data model, DAX, Filters, Slicers, Conditional formats and beautiful charts. Eg if you are counting customers that have purchased and have years on rows. Why is this last part important? Depending on the source of data, relationships may or may not be created when the model is initially set up. This data is provided by Microsoft for informational purposes only as an aid to illustrate a concept. To use and limitations and share some limitations of calculated field in pivot table data model. Yeah, good points Derek. Date field, and use it to show a count of orders. Ins menu in the model in pivot calculated field list table that i mentioned earlier, we shall not. Please start a new test to continue. Displays all of the values in each column or series as a percentage of the total for the column or series. This is used to present users with ads that are relevant to them according to the user profile. Note: use the Insert Item button to quickly insert items when you type a formula. -
Business Intelligence and Column-Oriented Databases
Central____________________________________________________________________________________________________ European Conference on Information and Intelligent Systems Page 12 of 344 Business Intelligence and Column-Oriented Databases Kornelije Rabuzin Nikola Modrušan Faculty of Organization and Informatics NTH Mobile, University of Zagreb Međimurska 28, 42000 Varaždin, Croatia Pavlinska 2, 42000 Varaždin, Croatia [email protected] [email protected] Abstract. In recent years, NoSQL databases are popular document-oriented database systems is becoming more and more popular. We distinguish MongoDB. several different types of such databases and column- oriented databases are very important in this context, for sure. The purpose of this paper is to see how column-oriented databases can be used for data warehousing purposes and what the benefits of such an approach are. HBase as a data management Figure 1. JSON object [15] system is used to store the data warehouse in a column-oriented format. Furthermore, we discuss Graph databases, on the other hand, rely on some how star schema can be modelled in HBase. segment of the graph theory. They are good to Moreover, we test the performances that such a represent nodes (entities) and relationships among solution can provide and we compare them to them. This is especially suitable to analyze social relational database management system Microsoft networks and some other scenarios. SQL Server. Key value databases are important as well for a certain key you store (assign) a certain value. Keywords. Business Intelligence, Data Warehouse, Document-oriented databases can be treated as key Column-Oriented Database, Big Data, NoSQL value as long as you know the document id. Here we skip the details as it would take too much time to discuss different systems [21]. -
Multi Approval Process
The App for O365 MULTI APPROVAL PROCESS User – Administrator guides Version 2.0 https://ltaddins.com +84 946 579 539 [email protected] The App for O365 MENU Overview ...................................................................................................................................................... 4 User guides ................................................................................................................................................. 9 Submit a request .................................................................................................................................... 9 Approve/Reject a request ..................................................................................................................... 9 Cancel the request ............................................................................................................................... 10 View my request ................................................................................................................................... 11 View My tasks ....................................................................................................................................... 11 View all completed requests ............................................................................................................... 11 View all rejected requests ................................................................................................................... 12 View all approved requests ................................................................................................................ -
Chapter 7 Multi Dimensional Data Modeling
Chapter 7 Multi Dimensional Data Modeling Fundamentals of Business Analytics” Content of this presentation has been taken from Book “Fundamentals of Business Analytics” RN Prasad and Seema Acharya Published by Wiley India Pvt. Ltd. and it will always be the copyright of the authors of the book and publisher only. Basis • You are already familiar with the concepts relating to basics of RDBMS, OLTP, and OLAP, role of ERP in the enterprise as well as “enterprise production environment” for IT deployment. In the previous lectures, you have been explained the concepts - Types of Digital Data, Introduction to OLTP and OLAP, Business Intelligence Basics, and Data Integration . With this background, now its time to move ahead to think about “how data is modelled”. • Just like a circuit diagram is to an electrical engineer, • an assembly diagram is to a mechanical Engineer, and • a blueprint of a building is to a civil engineer • So is the data models/data diagrams for a data architect. • But is “data modelling” only the responsibility of a data architect? The answer is Business Intelligence (BI) application developer today is involved in designing, developing, deploying, supporting, and optimizing storage in the form of data warehouse/data marts. • To be able to play his/her role efficiently, the BI application developer relies heavily on data models/data diagrams to understand the schema structure, the data, the relationships between data, etc. In this lecture, we will learn • About basics of data modelling • How to go about designing a data model at the conceptual and logical levels? • Pros and Cons of the popular modelling techniques such as ER modelling and dimensional modelling Case Study – “TenToTen Retail Stores” • A new range of cosmetic products has been introduced by a leading brand, which TenToTen wants to sell through its various outlets. -
ER/Studio Enterprise Data Modeling
ER/Studio Enterprise Data Modeling ER/Studio®, a model-driven data architecture and database design solution, helps companies discover, document, and reuse data assets. With round-trip database support, data architects have the power to thoroughly analyze existing data sources as well as design and implement high quality databases that reflect business needs. The highly-readable visual format enhances communication across job functions, from business analysts to application developers. ER/Studio Enterprise also enables team and enterprise collaboration with its repository. • Enhance visibility into your existing data assets • Effectively communicate models across the enterprise Related Products • Improve data consistency • Trace data origins and whereabouts to enhance data integration and accuracy ER/Studio Viewer View, navigate and print ER/Studio ENHANCE VISIBILITY INTO YOUR EXISTING DATA ASSETS models in a view-only environ- ment. As data volumes grow and environments become more complex corporations find it increasingly difficult to leverage their information. ER/Studio provides an easy- Describe™ to-use visual medium to document, understand, and publish information about data assets so that they can be harnessed to support business objectives. Powerful Design, document, and maintain reverse engineering of industry-leading database systems allow a data modeler to enterprise applications written in compare and consolidate common data structures without creating unnecessary Java, C++, and IDL for better code duplication. Using industry standard notations, data modelers can create an infor- quality and shorter time to market. mation hub by importing, analyzing, and repurposing metadata from data sources DT/Studio® such as business intelligence applications, ETL environments, XML documents, An easy-to-use visual medium to and other modeling solutions. -
Microsoft Access 2019 Textbook
MICROSOFT ACCESS 2019 Tutorial and Lab Manual David Murray Microsoft Access 2019 Tutorial and Lab Manual David Murray University at Buffalo Copyright © 2020 by David J. Murray This work is licensed under a Creative Commons Attribution 4.0 International License. It is attributed to David J. Murray and the original work can be found at mgs351.com. To view a copy of this license, visit creativecommons.org/licenses/by/4.0/. Kendall Hunt Publishing Company previously published this book. Microsoft Access 2019 Tutorial and Lab Manual is an independent textbook and is not affiliated with, nor has been authorized, sponsored, or otherwise approved by Microsoft Corporation. Printed in the United States of America First Printing, 2014 ISBN 978-1-942163-02-2 This book is dedicated to my loving wife Amy and my precious daughter Giacinta. Table of Contents Preface .....................................................................................................vi Chapter 1 – Overview of Microsoft Access Databases ................................1 Chapter 2 – Design and Create Tables to Store Data ..................................7 Chapter 3 – Simplify Data Entry with Forms .............................................19 Chapter 4 – Obtain Valuable Information Using Queries ..........................32 Chapter 5 – Create Professional Quality Output with Reports ..................47 Chapter 6 – Design and Implement Powerful Relational Databases …..…..58 Chapter 7 – Build User-Friendly Database Systems ..................................68 Chapter -
Sharing Files with Microsoft Office Users
Sharing Files with Microsoft Office Users Title: Sharing Files with Microsoft Office Users: Version: 1.0 First edition: November 2004 Contents Overview.........................................................................................................................................iv Copyright and trademark information........................................................................................iv Feedback.................................................................................................................................... iv Acknowledgments......................................................................................................................iv Modifications and updates......................................................................................................... iv File formats...................................................................................................................................... 1 Bulk conversion............................................................................................................................... 1 Opening files....................................................................................................................................2 Opening text format files.............................................................................................................2 Opening spreadsheets..................................................................................................................2 Opening presentations.................................................................................................................2 -
MICROSOFT TEAMS: PARENT/GUARDIAN GUIDE Online Learning for More Information and Resources
MICROSOFT TEAMS: PARENT/GUARDIAN GUIDE www.frankstonisd.net Online Learning for more information and resources. OVERVIEW AND ACCESS Overview Microsoft Classroom Teams is a digital hub for all Office 365 products and tools. Teams is one of the tools that teachers will use to share content, connect with students, give assignments, or provide activities and resources for student learning. Terms and Classroom Teams is collaborative and has many areas for students to access Features information and engage with their teacher and other students. Here are some common terms and features found in a Classroom Team. • Me Space = Blue bar along the left and top. This area is used to navigate around Teams. • We Space = Collaborative area in the middle of the Teams window. Information and content here are generally visible to everyone that is part of the Team. • Channel = A way to organize different Tabs (Files, Posts, and teacher-created content) around a topic. Every Classroom Team includes a General Channel. • Posts = This is where students and their teacher have conversations that everyone can participate in. Online Classroom Team sites are used for teacher-to-student Access interaction and contact. Students will access their Teams content by logging into their ClassLink account at: launchpad.classlink.com/frankston Students in grades PreK – 3rd will be issued Scan Cards. Students can also access Teams through their FISD student email at: https://login.microsoftonline.com/ When prompted, students will login with their FISD email add ress and password. Students may also download and install the M icrosoft Teams app for their FISD or personal device.