CHAPTER 2 Access 2013: Design View, Queries, Forms and Reports

Total Page：16

File Type：pdf, Size：1020Kb

CHAPTER 2 Access 2013: Design View, Queries, Forms and Reports Objective Type Questions 1. Fill in the blanks:- a. Design b. Form c. Print d. Tables e. Description 2. Write True or False: - a. False b. False c. True d. False e. False 3. Choose the correct option:- a. 255 characters b. Required c. href d. Long Text e. >=1 AND <=500 Descriptive Type Questions a. Describe the four parts of the Field Definition Grid. The Field Definition Grid is there in the Design View. It allows us to specify the field names and data types for the table. We can also give an optional description of each field. The first column is the field selector column. The second column gives any valid Fieldname. The data type corresponding to the field name is given in the third column. The fourth column Description is optional. We can describe the field name here. b. What are the different ways of setting field as Primary key? There are two ways of setting the primary key. The first method is as follows: i. Select the field to be set as primary key. ii. Click Primary key in the Tools group on the Design The second method is: i. Right click the field selector of the column that will be the primary key. ii. Select Primary Key from the context menu. After you set the primary key, a key icon will appear in the grey selector area to the left of the field’s name. c. Why is a form preferred over the Datasheet View for entering data? Form is preferred over the Datasheet View for entering data because forms provide an easy way to enter, edit, delete and view data in a table. One is told or reminded what information has to be supplied. There is uniformity, for convenience in processing. d. How will you switch from Datasheet View to Design View and vice-versa? When working with tables, there are two views available: Datasheet and Design. One easy way to switch between the views is by clicking the down arrow next to the View button on the toolbar (it's the leftmost button). Then select the required view you want from the drop- down list that appears. e. What do you understand by the AutoNumber field in Access? Can you change the data type of any field to AutoNumber? AutoNumber is a type of data used in Microsoft Access tables to generate an automatically incremented numeric counter. It may be used to create an identity column which uniquely identifies each record in a table. Only one AutoNumber field is allowed in each table. We can't change to AutoNumber when data is already there. We would have to add a new column, assign its data type as AutoNumber and then delete the old column and then rename the new column as the old column name. f. Give a validation rule such that a user can enter only the values 1,2 or 3? The validation rule is 1 or 2 or 3. .

Copy Link

Recommended publications

Data Analysis Expressions (DAX) in Powerpivot for Excel 2010
Data Analysis Expressions (DAX) In PowerPivot for Excel 2010 A. Table of Contents B. Executive Summary ............................................................................................................................... 3 C. Background ........................................................................................................................................... 4 1. PowerPivot ...............................................................................................................................................4 2. PowerPivot for Excel ................................................................................................................................5 3. Samples – Contoso Database ...................................................................................................................8 D. Data Analysis Expressions (DAX) – The Basics ...................................................................................... 9 1. DAX Goals .................................................................................................................................................9 2. DAX Calculations - Calculated Columns and Measures ...........................................................................9 3. DAX Syntax ............................................................................................................................................ 13 4. DAX uses PowerPivot data types .........................................................................................................
[Show full text]
(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.
[Show full text]
Ms Sql Server Alter Table Modify Column
Ms Sql Server Alter Table Modify Column Grinningly unlimited, Wit cross-examine inaptitude and posts aesces. Unfeigning Jule erode good. Is Jody cozy when Gordan unbarricade obsequiously? Table alter column, tables and modifies a modified column to add a column even less space. The entity_type can be Object, given or XML Schema Collection. You can use the ALTER statement to create a primary key. Altering a delay from Null to Not Null in SQL Server Chartio. Opening consent management ebook and. Modifies a table definition by altering, adding, or dropping columns and constraints. RESTRICT returns a warning about existing foreign key references and does not recall the. In ms sql? ALTER to ALTER COLUMN failed because part or more. See a table alter table using page free cloud data tables with simple but block users are modifying an. SQL Server 2016 introduces an interesting T-SQL enhancement to improve. Search in all products. Use kitchen table select add another key with cascade delete for debate than if column. Columns can be altered in place using alter column statement. SQL and the resulting required changes to make via the Mapper. DROP TABLE Employees; This query will remove the whole table Employees from the database. Specifies the retention and policy for lock table. The default is OFF. It can be an integer, character string, monetary, date and time, and so on. The keyword COLUMN is required. The table is moved to the new location. If there an any violation between the constraint and the total action, your action is aborted. Log in ms sql server alter table to allow null in other sql server, table statement that can drop is.
[Show full text]
Query Execution in Column-Oriented Database Systems by Daniel J
Query Execution in Column-Oriented Database Systems by Daniel J. Abadi [email protected] M.Phil. Computer Speech, Text, and Internet Technology, Cambridge University, Cambridge, England (2003) & B.S. Computer Science and Neuroscience, Brandeis University, Waltham, MA, USA (2002) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science and Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2008 c Massachusetts Institute of Technology 2008. All rights reserved. Author......................................................................................... Department of Electrical Engineering and Computer Science February 1st 2008 Certifiedby..................................................................................... Samuel Madden Associate Professor of Computer Science and Electrical Engineering Thesis Supervisor Acceptedby.................................................................................... Terry P. Orlando Chairman, Department Committee on Graduate Students 2 Query Execution in Column-Oriented Database Systems by Daniel J. Abadi [email protected] Submitted to the Department of Electrical Engineering and Computer Science on February 1st 2008, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science and Engineering Abstract There are two obvious ways to map a two-dimension relational database table onto a one-dimensional storage in- terface:
[Show full text]
Quick-Start Guide
Quick-Start Guide Table of Contents Reference Manual..................................................................................................................................................... 1 GUI Features Overview............................................................................................................................................ 2 Buttons.................................................................................................................................................................. 2 Tables..................................................................................................................................................................... 2 Data Model................................................................................................................................................................. 4 SQL Statements................................................................................................................................................... 5 Changed Data....................................................................................................................................................... 5 Sessions................................................................................................................................................................. 5 Transactions.......................................................................................................................................................... 6 Walktrough
[Show full text]
Column-Stores Vs. Row-Stores: How Different Are They Really?
Column-Stores vs. Row-Stores: How Different Are They Really? Daniel J. Abadi Samuel R. Madden Nabil Hachem Yale University MIT AvantGarde Consulting, LLC New Haven, CT, USA Cambridge, MA, USA Shrewsbury, MA, USA [email protected] [email protected] [email protected] ABSTRACT General Terms There has been a significant amount of excitement and recent work Experimentation, Performance, Measurement on column-oriented database systems (“column-stores”). These database systems have been shown to perform more than an or- Keywords der of magnitude better than traditional row-oriented database sys- tems (“row-stores”) on analytical workloads such as those found in C-Store, column-store, column-oriented DBMS, invisible join, com- data warehouses, decision support, and business intelligence appli- pression, tuple reconstruction, tuple materialization. cations. The elevator pitch behind this performance difference is straightforward: column-stores are more I/O efficient for read-only 1. INTRODUCTION queries since they only have to read from disk (or from memory) Recent years have seen the introduction of a number of column- those attributes accessed by a query. oriented database systems, including MonetDB [9, 10] and C-Store [22]. This simplistic view leads to the assumption that one can ob- The authors of these systems claim that their approach offers order- tain the performance benefits of a column-store using a row-store: of-magnitude gains on certain workloads, particularly on read-intensive either by vertically partitioning the schema, or by indexing every analytical processing workloads, such as those encountered in data column so that columns can be accessed independently. In this pa- warehouses.
[Show full text]
Columnar Storage in SQL Server 2012
Columnar Storage in SQL Server 2012 Per-Ake Larson Eric N. Hanson Susan L. Price [email protected] [email protected] [email protected] Abstract SQL Server 2012 introduces a new index type called a column store index and new query operators that efficiently process batches of rows at a time. These two features together greatly improve the performance of typical data warehouse queries, in some cases by two orders of magnitude. This paper outlines the design of column store indexes and batch-mode processing and summarizes the key benefits this technology provides to customers. It also highlights some early customer experiences and feedback and briefly discusses future enhancements for column store indexes. 1 Introduction SQL Server is a general-purpose database system that traditionally stores data in row format. To improve performance on data warehousing queries, SQL Server 2012 adds columnar storage and efficient batch-at-a- time processing to the system. Columnar storage is exposed as a new index type: a column store index. In other words, in SQL Server 2012 an index can be stored either row-wise in a B-tree or column-wise in a column store index. SQL Server column store indexes are “pure” column stores, not a hybrid, because different columns are stored on entirely separate pages. This improves I/O performance and makes more efficient use of memory. Column store indexes are fully integrated into the system. To improve performance of typical data warehous- ing queries, all a user needs to do is build a column store index on the fact tables in the data warehouse.
[Show full text]
SQL Data Manipulation Language (DML)
The Islamic University of Gaza Faculty of Engineering Dept. of Computer Engineering Database Lab (ECOM 4113) Lab 2 SQL Data Manipulation Language (DML) Eng. Ibraheem Lubbad SQL stands for Structured Query Language, it’s a standard language for accessing and manipulating databases. SQL commands are case insensitive instructions used to communicate with the database to perform specific tasks, work, functions and queries with data. All SQL statements start with any of the keywords like SELECT, INSERT, UPDATE, DELETE, ALTER, DROP, CREATE, USE, SHOW and all the statements end with a semicolon (;) SQL commands are grouped into major categories depending on their functionality: Data Manipulation Language (DML) - These SQL commands are used for storing, retrieving, modifying, and deleting data. These Data Manipulation Language commands are CALL, DELETE, EXPLAIN, INSERT, LOCK TABLE, MERGE, SELECT and UPDATE. Data Definition Language (DDL) - These SQL commands are used for creating, modifying, and dropping the structure of database objects. The commands are ALTER, ANALYZE, AUDIT, COMMENT, CREATE, DROP, FLASHBACK, GRANT, PURGE, RENAME, REVOKE and TRUNCATE. Transaction Control Language (TCL) - These SQL commands are used for managing changes affecting the data. These commands are COMMIT, ROLLBACK, and SAVEPOINT. Data Control Language (DCL) - These SQL commands are used for providing security to database objects. These commands are GRANT and REVOKE. In our lab we will use university schema (you can open it by click on file) SELECT Statement: The SELECT statement retrieves data from a database. The data is returned in a table-like structure called a result-set. SELECT is the most frequently used action on a database.
[Show full text]
Introduction to Data Types and Field Properties Table of Contents OVERVIEW
Introduction to Data Types and Field Properties Table of Contents OVERVIEW ........................................................................................................................................................ 2 WHEN TO USE WHICH DATA TYPE ........................................................................................................... 2 BASIC TYPES ...................................................................................................................................................... 2 NUMBER ............................................................................................................................................................. 3 DATA AND TIME ................................................................................................................................................ 4 YES/NO .............................................................................................................................................................. 4 OLE OBJECT ...................................................................................................................................................... 4 ADDITIONAL FIELD PROPERTIES ........................................................................................................................ 4 DATA TYPES IN RELATIONSHIPS AND JOINS ....................................................................................................... 5 REFERENCE FOR DATA TYPES .................................................................................................................
[Show full text]
Creating Tables and Relationships
Access 2007 Creating Databases - Fundamentals Contents Database Design Objectives of database design 1 Process of database design 1 Creating a New Database.............................................................................................................. 3 Tables ............................................................................................................................................ 4 Creating a table in design view 4 Defining fields 4 Creating new fields 5 Modifying table design 6 The primary key 7 Indexes 8 Saving your table 9 Field properties 9 Calculated Field Properties (Access 2010 only) 13 Importing Data ............................................................................................................................. 14 Importing data from Excel 14 Lookup fields ................................................................................................................................ 16 Modifying the Data Design of a Table ........................................................................................20 Relationships ................................................................................................................................22 Creating relationships 23 Viewing or editing existing relationships 24 Referential integrity 24 Viewing Sub Datasheets 26 . Page 2 of 29 Database Design Time spent in designing a database is time very well spent. A well-designed database is the key to efficient management of data. You need to think about what information is needed and
[Show full text]
The Relational Model: Details the Relational Model Overview 1
112 The Relational Model: Details • After completing this chapter, you sould be able to . explain the concepts of the Relational Model, Schemas, state, domains . explain applications and problems of null values, . explain integrity constraints and their importance, . explain the meaning of keys and foreign keys, . read various notations for relational schema, . develop simple relational schemas. 113 The Relational Model Overview 1. Relational Model Concepts: Schema, State 2. Null Values 3. Constraints: General Remarks 4. Key Constraints 5. Foreign Key Constraints 114 Example Database (1) STUDENTS RESULTS SID FIRST LAST EMAIL SID CAT ENO POINTS 101 Ann Smith ... 101 H 1 10 102 Michael Jones (null) 101 H 2 8 103 Richard Turner ... 101 M 1 12 104 Maria Brown ... 102 H 1 9 102 H 2 9 EXERCISES 102 M 1 10 CAT ENO TOPIC MAXPT 103 H 1 5 103 M 1 7 H 1 Rel.Alg. 10 H 2 SQL 10 M 1 SQL 14 115 Example Database (2) • Columns in table STUDENTS: . SID: “student ID” (unique number) . FIRST, LAST, EMAIL: first and last name, email address (may be null). • Columns in table EXERCISES: . CAT: category (H: Homework, M/F: midterm/final exam) . ENO: exercise number within category . TOPIC, MAXPT: topic of exercise, maximum number of points. • Columns in table RESULTS: . SID: student who handed in exercise (references STUDENTS) . CAT, ENO: identification of exercise (references EXERCISE) . POINTS: graded points 116 Data Values (1) • All table entries are data values which conform to some given selection of data types. • The set of available data types is determined by the RDBMS (and by the supported version of the SQL standard).
[Show full text]
Dynamic Information with IBM Infosphere Data Replication CDC
Front cover IBM® Information Management Software Smarter Business Dynamic Information with IBM InfoSphere Data Replication CDC Log-based for real-time high volume replication and scalability High throughput replication with integrity and consistency Programming-free data integration Chuck Ballard Alec Beaton Mark Ketchie Anzar Noor Frank Ketelaars Judy Parkes Deepak Rangarao Bill Shubin Wim Van Tichelen ibm.com/redbooks International Technical Support Organization Smarter Business: Dynamic Information with IBM InfoSphere Data Replication CDC March 2012 SG24-7941-00 Note: Before using this information and the product it supports, read the information in “Notices” on page ix. First Edition (March 2012) This edition applies to Version 6.5 of IBM InfoSphere Change Data Capture (product number 5724-U70). © Copyright International Business Machines Corporation 2012. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . ix Trademarks . x Preface . xi The team who wrote this book . xii Now you can become a published author, too! . xvi Comments welcome. xvii Stay connected to IBM Redbooks . xvii Chapter 1. Introduction and overview . 1 1.1 Optimized data integration . 2 1.2 InfoSphere architecture . 4 Chapter 2. InfoSphere CDC: Empowering information management. 9 2.1 The need for dynamic data . 10 2.2 Data delivery methods. 11 2.3 Providing dynamic data with InfoSphere CDC . 12 2.3.1 InfoSphere CDC architectural overview . 14 2.3.2 Reliability and integrity . 16 Chapter 3. Business use cases for InfoSphere CDC . 19 3.1 InfoSphere CDC techniques for transporting changed data .
[Show full text]