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SQL Server

SQL Server. Glossary. Peter Gfader. Specializes in C# and .NET (Java not anymore) Testing Automated tests Agile, Scrum Certified Scrum Trainer Technology aficionado Silverlight ASP.NET Windows Forms. SQL Server 2008. DBMS ( Database Management System). Manages databases

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SQL Server

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  1. SQL Server Glossary

  2. Peter Gfader • Specializes in • C# and .NET (Java not anymore) • TestingAutomated tests • Agile, ScrumCertified Scrum Trainer • Technology aficionado • Silverlight • ASP.NET • Windows Forms

  3. SQL Server 2008

  4. DBMS (Database Management System) • Manages databases • Controlling data access • Enforcing data integrity • Managing concurrency

  5. DBMS (Database Management System) • Backup / Restore • Backup • Full • Differential • Transaction log • Recovery model • Simple • Full • Bulk logged

  6. Database • Container for • See picture • Holds tables with rows 

  7. Tables • In relational databases a table is a set of elements with vertical columns and horizontal rows • Central element in a database

  8. Tables

  9. Rows • Also called a record or tuple, represents a single, implicitly structured data item in a table

  10. Columns

  11. Schemas • Logical Container for tables • Good for security and permissions • Logical grouping

  12. Index • Like an index in the back of an encyclopedia • Lookup for whole rows

  13. Non-Clustered Index • A non-clustered index contains the index key values and row locators that point to the storage location of the table data.

  14. Clustered Index • Clustered indexes sort and store the data rows in the table based on their key values. There can only be one clustered index per table.

  15. View • A view is a virtual table based on the result-set of an SQL statement. Example: CREATE VIEW [Current Product List] ASSELECT ProductID,ProductNameFROM ProductsWHERE Discontinued=No SELECT * FROM [Current Product List]

  16. Primary key • Unique key or primary key is a candidate key to uniquely identify each row in a table • Single column or set of columns • No two distinct rows in a table can have the same value(or combination of values) in those columns

  17. Foreign Key • Referential constraint between two tables • Column or a set of columns in one (referencing table) that refers to a column or set of columns in another (referenced) table • Column in referencing must be a primary key or other candidate key in the referenced table

  18. Relationships • There three types of relationships: • One-to-one • One-to-many • Many-to-many

  19. Relationships – One to Many

  20. Transactions • ACID properties • Atomicity (all or none) • Consistency (before and after) • Isolation (others) • Durability (after) • Comprises of unit of work in DBMS, treated in a coherent and reliable way independent of other transactions • Allow for correct recovery from failures and keep a database consistent even in cases of system failure • Provides isolation between programs accessing database concurrently

  21. Language statements • Data Manipulation Language (DML)Examples: SELECT, UPDATE, INSERT statements • Data Definition Language (DDL)Examples: CREATE, ALTER, DROP statements • Data Control Language (DCL)Examples: GRANT, REVOKE statements • Transactional Control Language (TCL)Examples: COMMIT, ROLLBACK statements

  22. SQL Server Compact • Relational Database for applications that run on mobile devices and desktops

  23. SQL Server Filegroups • Provide an opportunity for fine-tuning performance by allowing the movement of specific tables and indexes from one physical drive array to another

  24. Different types of backups • Types of backups • Full or complete • Differential • Transaction log

  25. Different types of backups • Full or Complete • Create stand-alone image of entire database • Restore to same database or create new • Data lost = time of disaster and time of last backup • Storage requirements large • backup size = original database size (if not compressed)

  26. Different types of backups • Differential • Backs up modified data since the last full backup • Data lost = same as with Full backups • Space efficient • Only changes from last full backup

  27. Different types of backups • Transaction Log • Backs up changes since last transaction log backup or last full backup (If no other transaction log backup exists) • The inactive part of the transaction log will also be truncated

  28. Different types of recovery models • Type of recovery models • Simple • Full • Bulk Logged • Backup and restore depend on recovery models

  29. Different types of recovery models • Simple • No transaction log • No transaction log backup available • Restore = full database or differential backup • Recover data = most recent full database or differential backup. • Use when data is not critical and losing all transaction since the last backup is not an issue

  30. Different types of recovery models • Full • Full, differential, or transaction log backups available • Recover data = point of failure or specific point in time • Use when data is critical, point of time recovery is a requirement, and bulk operations are performed throughout the day

  31. Different types of recovery models • Bulk-logged • Bulk-logged = Full, but • The following operations are minimally logged and not fully recoverable: SELECT INTO, bulk-load operations, CREATE INDEX, text and image operations. • Use when data is critical, point of time recovery is a requirement, but backing up bulk operations would bog down the system

  32. Different types of backups and recovery models • Set Recovery Model from database’ properties

  33. Different types of backups and recovery models • Set backup type during backup process • based on the recovery model

  34. SQL Server Services

  35. SSIS (SQL Server Integration Services) • Is a platform for data integration (combining data residing in different sources and providing users with a unified view of these data) and workflow applications(automates, at least to some degree, a process or processes) • Fast and flexible data warehouse tool

  36. SSIS (SQL Server Integration Services) • Extract, Transform, Load (ETL) and integration capabilities, enabling organizations to more easily manage data from a wide array of data sources. • New features SQL 2008: • Creating scripts with C# and VB • New SSIS connectors for SAP BW, Oracle and Teradata

  37. SSAS(SQL Server Integration Services) • Collection of Online Analytical Processing (OLAP) and Data Mining Services supplied in Microsoft SQL Server

  38. SSAS - Cube • Data structure that allows fast analysis of data • Extensions to the two-dimensional array of a spreadsheet • Company might wish to analyse some financial data by product, by time-period, by city, by type of revenue and cost, and by comparing actual data with a budget

  39. SSAS – Cube (Diagram)

  40. Dimension • Used to slice main data • Dimensions organize data with relation to an area of interest • Attribute based on column from table or view • Think of categorization of data • (Customer, Productcategory, Date,...)

  41. Measure • Property in data warehouse to perform calculations (aggregations) • Numbers • Used for aggregation on measure column of Fact table :-)

  42. Fact table • Contains two basic types of columns: • Attribute columns • Foreign key relationships to dimension tables • Measure columns • Define the granularity of a fact table and its measure group

  43. SSAS - KPI(Key Performance Indicator) • Measures are commonly used to help an organization define and evaluate how successful it is, typically in terms of making progress towards its long-term organizational goals

  44. SSAS - OLAP(Online analytical processing) • Approach to quickly answer multi-dimensional analytical queries

  45. SSAS - ROLAP(Relational Online Analytical Processing) • Differs significantly in that it does not require the pre-computation and storage of information • Access the data in a relational database and generate SQL queries to calculate information at the appropriate level when an end user requests it • Creating summary tables or aggregations which summarize the data at any desired combination of dimensions

  46. SSAS - MOLAP (Multidimensional Online Analytical Processing) • It requires the pre-computation and storage of information in the cube - the operation known as processing • This data in an optimized multi-dimensional array storage rather then relational database

  47. SSAS - HOLAP(Hybrid Online Analytical Processing) • Combination of ROLAP and MOLAP which are other possible implementation of OLAP • Allows to store part of the data in the MOLAP store and another part of the data in ROLAP store.

  48. SSAS - Data Mining • Sometimes called data or knowledge discovery • It is the process of analysing data from different perspectives and summarizing it into useful information • This information is useful to increase revenue, cuts costs, or both • Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases

  49. SSRS(SQL Server Reporting Services) • Server-based report generation software system • Prepare and deliver a variety of interactive and printed reports

  50. Thank You! Gateway Court Suite 10 81 - 91 Military Road Neutral Bay, Sydney NSW 2089 AUSTRALIA ABN: 21 069 371 900 Phone: + 61 2 9953 3000 Fax: + 61 2 9953 3105 info@ssw.com.auwww.ssw.com.au

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