![Data Warehousing (1/15)
• Process of constructing and using (i.e. access heterogeneous
data sources) a data warehouse.
• Volume of data handled can be very high, particularly when
considering the requirements for historical data analysis.
• Example
– Amazon, Flipkart, Ebay, etc. use data warehousing for business
intelligence.
• Multi-tiered Data Warehousing Model
– Tiers
• [Data Warehouse Server] – [OLAP server] – [Front-end tools]
– Data flow between the three Tiers
• Pre-Data Warehouse -> Data Cleansing -> Data Repository ->
Front-end Analytics
25-Aug-2017 10 of 99](https://image.slidesharecdn.com/applicationmiddlewareoverview-180428135953/85/Application-Middleware-Overview-10-320.jpg)
Application Middleware Overview
- 2. At a Glance • Data Warehousing • Introduction to Common Messaging System • Web Tier Deployment, Application Servers & Clustered Deployment • IBM Notes & Dominos (Email) 25-Aug-2017 2 of 99
- 4. Data Warehouse • Conceptualized by Bill Inmon, 1990 • Data Warehouse or Enterprise Data Warehouse – An integrated collection of databases (DB) rather than a single database. – A data warehouse is a centralized data repository that stores data from multiple diverse (heterogeneous/homogenous) information sources. • Data repository which mostly includes historical/archived data. • Features of Data warehouses – Constructed by integrating data from heterogeneous sources – Provides information of a particular time period. – Non-volatile and separated from operational DB. 25-Aug-2017 4 of 99
- 5. Data Mining • Patented by HNC Software Inc., San Diago in 1980s • Process of extracting meaningful data from data warehouse. i.e. Knowledge Discovery from a Data warehouse – Relies on the data compiled in the data warehousing phase in order to detect meaningful patterns. – Finding patterns, trends & correlations ease understanding and decision making. – Knowledge can be used for prediction (as in Businesses i.e. Business Intelligence). 25-Aug-2017 5 of 99
- 6. OLTP v/s OLAP (1/4) • Organizations have Evaluational DB & Operational DB. – Online Analytical Processing (OLAP) • Software tools that are used in knowledge mining & acquiring intelligence. – Online Transaction Processing (OLTP) • Software tools that provide support to transaction-oriented applications on the Internet. • Typically, OLTP systems are used for order entry, financial transactions, customer relationship management (CRM) and retail sales. 25-Aug-2017 OLTP: Run a Business OLAP : Improving Business 6 of 99
- 7. OLTP v/s OLAP (2/4) • Scenario 1: – You want to build an online store/website. What do you want it to do: • Store actual products & their associated price. • You want to be able to make transactions, possibly involving a user buying a product (that's a relation). • Store user data, passwords, previous transactions..... • You want to be able to find data for a particular user, change it's name... Basically perform INSERT, UPDATE, DELETE operations on a user data. Same with products, etc. 25-Aug-2017 OLTP is a Good fit 7 of 99
- 8. OLTP v/s OLAP (3/4) • Scenario 2 : – Now, You have your own online store/website. What exactly do you want to know with your store/website. • “Total money spend for all users” • “What is the most sold product?”. • “Why do users prefer Type-1 over Type-2 of the same product?”. • “Why is sales of certain products low in a certain month?”. • “Why do your store getting less users compared with a similar store?” • This falls into the analytics/business intelligence domain. 25-Aug-2017 OLAP is a Good fit 8 of 99
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- 10. Data Warehousing (1/15) • Process of constructing and using (i.e. access heterogeneous data sources) a data warehouse. • Volume of data handled can be very high, particularly when considering the requirements for historical data analysis. • Example – Amazon, Flipkart, Ebay, etc. use data warehousing for business intelligence. • Multi-tiered Data Warehousing Model – Tiers • [Data Warehouse Server] – [OLAP server] – [Front-end tools] – Data flow between the three Tiers • Pre-Data Warehouse -> Data Cleansing -> Data Repository -> Front-end Analytics 25-Aug-2017 10 of 99
- 12. Online Transaction Processing • Core database • For transactions and routine tasks 25-Aug-2017 12 of 99
- 13. Data about data, i.e. information about data tables in OLTP System. 25-Aug-2017 13 of 99
- 14. Data Warehousing (5/15) • Meta-Data Repository (1/3) – Additional metadata are created & captured for timestamping any of the following: • Extracted data or Source of the extracted data • Missing fields (Added by data cleaning or integration processes) – Serves as a Directory • Used to locate the contents of the data warehouse. – Serves as a Guide to • Mapping of data (When data are transformed from the operational environment to the data warehouse environment). • Algorithms used for summarization (between current detailed data & lightly summarized data, and between lightly summarized data & highly summarized data). 25-Aug-2017 14 of 99
- 15. Data Warehousing (6/15) • Meta-Data Repository (2/3) – A metadata repository should contain the following: • A description of the structure of the data warehouse – Includes schema, view, dimensions, hierarchies, and derived data definitions, as well as data mart locations and contents. • Operational metadata – Includes data lineage (history of migrated data and the sequence of transformations applied to it), currency of data (active, archived, or purged), and monitoring information (warehouse usage statistics, error reports, and audit trails). • The algorithms used for summarization – Includes measure and dimension definition algorithms, data on granularity, partitions, subject areas, aggregation, summarization, and predefined queries and reports. 25-Aug-2017 15 of 99
- 16. Data Warehousing (7/15) • Meta-Data Repository (3/3) – A metadata repository should contain the following: • The mapping from the operational environment to the data warehouse – Includes source databases and their contents, gateway descriptions, data partitions, data extraction, cleaning, transformation rules and defaults, data refresh and purging rules, and security (user authorization and access control). • Data related to system performance – Includes indices and profiles that improve data access and retrieval performance, in addition to rules for the timing and scheduling of refresh, update, and replication cycles. • Business metadata – Include business terms and definitions, data ownership information, and charging policies. 25-Aug-2017 16 of 99
- 17. 25-Aug-2017 Extract from source (OLTP) Clean detect errors in data & rectifies them Transform convert data from legacy/host to warehouse format Load sort, summarize, consolidate, compute views, check integrity, build indices & partitions Refresh propagate the updates from the data sources to the warehouse 17 of 99
- 18. • For effective querying, analysis and decision-making • OLAP (Online Analytical Processing) Design 25-Aug-2017 18 of 99
- 19. • Access layer of data warehouse • Subset of data ware house • Oriented to specific business unit or department E.g. marketing 25-Aug-2017 19 of 99
- 20. To analyze multidimensional data interactively from multiple perspectives 25-Aug-2017 20 of 99
- 21. • Computational process of discovering patterns in large data sets. • To extract information and transform it into an understandable structure for further use. 25-Aug-2017 21 of 99
- 22. Creation and study of the visual representation of data E.g. scatter plot, bar chart. 25-Aug-2017 22 of 99
- 23. Retrieve and present a subset of data for a particular purpose 25-Aug-2017 23 of 99
- 24. Data Information Knowledge Dimensional Modeling (OLTP to OLAP Structure) 25-Aug-2017 24 of 99
- 25. Dimensional Modeling (1/8) • Data warehouses & OLAP tools are based on a multi- dimensional data model. – Note: Operational DB is based on ER Model). • Dimensional modeling (DM) is a set of techniques and concepts used in data warehouse design. • A Dimensional Model is a database structure that is optimized for online queries and Data Warehousing tools. – It is comprised of "fact" and "dimension" tables. • It is especially useful for summarizing and rearranging the data and presenting views of the data to support data analysis. 25-Aug-2017 25 of 99
- 26. Dimensional Modeling (2/8) • Fact – A fact is a collection of related data items, consisting of measures and context data. – Each fact represents • Business item or Business transaction or Event that can be used in analyzing the business or business processes. – In a data warehouse, facts are implemented in the core tables in which all of the numeric data is stored. 25-Aug-2017 26 of 99
- 27. Dimensional Modeling (3/8) • Dimensions – Dimensions are the parameters over which OLAP is performed. • Many analytical processes are used to quantify the impact of dimensions on the facts. – Example • In a database for analyzing all sales of products, common dimensions could be: Time, Location/Region, Customers, Salesperson, Product 25-Aug-2017 Facts Dimensions Business Measurements (Quantified). Textual and descriptive attributes by which users describe objects. E.g. Quantity, Amount, Cost, Taxes. E.g. Product category, Date-time of a transaction. Things that can be summed or aggregated. E.g. sales of a product. Who, where, what, how, when. 27 of 99
- 28. Dimensional Modeling (4/8) • Measure – It is a numeric attribute of a fact, representing performance or behavior of the business related to dimensions. – The measures of multidimensional databases are mostly confined to numerical data though measures can also be applied to spatial, multimedia, or text data. – A measure is located on facts. – Example • sales money, sales volume, quantity supplied, supply cost, transaction amount. 25-Aug-2017 28 of 99
- 29. Dimensional Modeling (5/8) • Data warehouse Schema – A Data warehouse (Evaluational DBs) requires to maintain a logical description using a Schema. – Date warehouse Schema is defined using DMQL. – Types of Schema • Star Schema • Snowflake Schema • Fact constellation or Galaxy Schema 25-Aug-2017 29 of 99
- 30. Dimensional Modeling (6/8) • Example: Star Schema of a data warehouse for sales 25-Aug-2017 30 of 99
- 31. Dimensional Modeling (7/8) • Example: Snowflake Schema of a data warehouse for sales – Redundancy is reduced by splitting the dimension tables. 25-Aug-2017 31 of 99
- 32. Dimensional Modeling (8/8) • Example: Galaxy Schema of a data warehouse for sales and shipping – Consists of more number of Fact tables. 25-Aug-2017 32 of 99
- 33. Visualization of DM (1/3) • Data cubes are popularly used to visualize a 3D model. – A data cube allows data to be modeled and viewed in 3D. It is defined by dimensions and facts. • Usually a dimensional model consists of more than three dimensions and is referred to as a hypercube. – E.g. Cuboids and Lattice of Cuboids (4D data cube) 25-Aug-2017 33 of 99
- 34. 25-Aug-2017 3-D data cube representation • The above table is represented using 3D data cube according to the three dimensions (time, item, and location) • The measure displayed is dollars sold (in thousands). 34 of 99
- 35. Visualization of DM (3/3) • n-Dimensional data can be visualized with a series of (n-1)- Dimensional “cubes.” – i.e. 4D data cube can be visualized with a series of 3D cubes. – Example: Sales data can be viewed with an additional fourth dimension (such as supplier) using a series of 3D cubes. 25-Aug-2017 35 of 99
- 36. Concept Hierarchy (1/2) • A concept hierarchy defines a sequence of mappings from a set of low-level concepts to higher-level (more general) concepts. • Example: – Consider a concept hierarchy for the dimension “location”. • City values for location include Vancouver, Toronto, NewYork, and Chicago. • Each city, however, can be mapped to the province or state to which it belongs. i.e. Vancouver can be mapped to British Columbia, and Chicago to Illinois. • The provinces and states can in turn be mapped to the country to which they belong, such as Canada or the USA. 25-Aug-2017 36 of 99
- 37. Concept Hierarchy (2/2) • Example: Concept hierarchy for the dimension “location” 25-Aug-2017 37 of 99
- 38. Basic OLAP Operations (1/9) • In the multidimensional model, data are organized into multiple dimensions, and each dimension contains multiple levels of abstraction (different perspectives) to view data. • OLAP provides a user-friendly environment for interactive querying and data analysis through a number of OLAP data cube operations to materialize the different levels of views. including – Roll‐up (drill‐up) – Drill‐down (roll-down) – Slice and dice – Pivot (rotate) – Drill ‐across – Drill ‐through 25-Aug-2017 38 of 99
- 39. Basic OLAP Operations (2/9) • Roll-Up operation – The roll-up operation (also called drill-up or aggregation operation) performs aggregation on a data cube by either climbing up a concept hierarchy (to obtain a less detailed data) for a dimension or dimension reduction. • Drill-down Operations – The drill-down operation (also called roll-down) is the reverse of roll-up operation. – It navigates from less detailed data to more detailed data (i.e. climbing down a concept hierarchy for a dimension). 25-Aug-2017 39 of 99
- 40. Basic OLAP Operations (3/9) • Slice Operation – The slice operation performs a selection on one dimension of the given cube, resulting in a sub-cube. • Dice Operation – The dice operation defines a sub-cube by performing a selection on two or more dimensions. • Pivot Operation – Pivot (also called rotate) is a visualization operation that rotates the data axes in view in order to provide an alternative presentation of the data. 25-Aug-2017 40 of 99
- 41. Basic OLAP Operations (4/9) • Drill-across Operation – This operation executes queries involving (i.e., across) more than one fact table. • Drill-through Operation – This operation uses relational SQL facilities to drill through the bottom level of a data cube down to its back-end relational tables. • Other OLAP operations include – Ranking the top N or bottom N items in lists – Computing moving averages, growth rates, interests, internal rates of return, depreciation, currency conversions, and statistical functions. 25-Aug-2017 41 of 99
- 42. 25-Aug-2017 Roll-up Operation • The example provides information about the sales of home entertainment item • USA = 440+1560 = 2000 • Canada = 395+605 = 1000 42 of 99
- 43. 25-Aug-2017 Drill-down Operation • The example provides information about the sales of security item per month for Vancouver. • Q1 = Jan+Feb+Mar = 150+100+150 = 400 43 of 99
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- 47. Data Mart (1/5) • A data mart is a repository of data that is designed to serve a particular community of knowledge workers. • It groups related data sets for specific sets of customers or specific business area. • Why Data Mart? – Maintain temporary copy of data from few fact tables which does not change frequently for analysis. It is discarded after analysis. – Decrease load on a Data warehouse by making a copy of fact tables in separate server. Refreshed periodically. – Simulation of new scenarios by changing data. • Data in a Data warehouse cannot be changed without affecting performance. 25-Aug-2017 47 of 99
- 48. Data Mart (2/5) • Vs Data Warehouse – Data Warehouses have an enterprise-wide depth. – Data Mart is a subset of the data warehouse and is usually smaller and focus on a particular subject or department. The information in data marts pertains to a single departments. – All data marts together create a data warehouse. 25-Aug-2017 48 of 99
- 49. Data Marts (3/5) • Type-1: Dependent data mart – Data from Data warehouse are aggregated, restructured & summarized with Enterprise context. – Built to achieve improved performance and availability, better control & lower telecommunication costs resulting from local access of data relevant to a specific department. 25-Aug-2017 49 of 99
- 50. Data Marts (4/5) • Type-2: Independent data mart – No centralized data warehouse. – Number of sources are few. – All aspects of the ETT process (Extract, transform, transfer) should be dealt. – Preferred when a solution is required within a shorter time. 25-Aug-2017 50 of 99
- 51. Data Marts (5/5) • Type-3: Hybrid data mart – Combine input from sources other than only from a data warehouse. 25-Aug-2017 51 of 99
- 52. Warehouse Modeling Approaches • Modelling Approaches – Global data warehouse architecture – Independent data mart architecture – Interconnected data mart architecture 25-Aug-2017 52 of 99
- 53. Global data warehouse architecture (1/2) • Designed and constructed based on the needs of the whole enterprise. • Supports a large part of or the entire corporation that has the necessity for a fully integrated data warehouse with a greater degree of data accessibility & usage across departments. • Issue – Setting up this kind of data warehouse is time and cost involved when it is spanning multiple geographic locations. 25-Aug-2017 53 of 99
- 54. Global data warehouse architecture (2/2) 25-Aug-2017 54 of 99 TDM – Transaction Data Mart POS – Point of Sale EDW – Enterprise Data Warehouse
- 55. Independent Data Mart architecture • Independent data mart architecture implies stand-alone data marts that are controlled by a particular workgroup or department to meet their needs. • Major constraint – Minimal integration and lack of a more global view of the data. • i.e. The data in any particular data mart will be accessible only to those in the workgroup or department of business that owns the data mart. • The workgroup or department would decide what source data to load into the data mart, when to update it, who can access it and where it resides. 25-Aug-2017 55 of 99
- 56. • It is basically a distributed implementation. • Although separate data marts are implemented in a particular workgroup or department, they can be integrated or interconnected, to provide a more enterprise-wide or corporate-wide view of the data. • This architecture creates some complexities such as the workgroup or department which would control and manage the environment, manage the data which is common to multiple data marts. 25-Aug-2017 Interconnected data mart architecture (1/2) 56 of 99
- 57. Interconnected data mart architecture (2/2) 25-Aug-2017 57 of 99
- 59. Message Queuing • Message queuing (MQ) is the inter-process communication and information exchange between two or more co- operating processes. • MQ is accomplished by directing messages to a memory- or disk-based queue as an intermediate storage point. • MQ applications are generally designed so that the messages flow in a request/reply fashion. – After the messaging system accepts the message from the application, the application is free to continue work. – It is the responsibility of the messaging system to deliver the message to the target queue (or) to take the appropriate action if the messaging system cannot deliver the message. 25-Aug-2017 59 of 99
- 60. Application Integration- Business Need • Organizations use many applications and the services provided by them, which were built over a period of time. • These applications provide different functionality and are implemented using different technologies/programming languages while they run on different OSs and hardware. • Discrete applications need to communicate to serve business requirement. • Integrating applications is a need for every organization. • Applications can communicate using middleware. 25-Aug-2017 60 of 99
- 61. Middleware • Lies in between two applications as a mediator. • Middleware facilitates interoperability of applications. • It simplifies communications of complex application running on different environments. • Middleware reduces time and resources on various factors like designing, coding of applications. • It serves as a link between applications running on discrete environments. 25-Aug-2017 61 of 99
- 62. Message-Oriented Middleware (1/4) • Middleware that enables communication between applications using messages. – Message: The data that the application wants to communicate with other application. • Advantages – Asynchronous interaction of applications – Loosely coupled – Reliability • The loss of message due to system or network failure is prevented by store and forward mechanism. – Availability • The ripple effect of one system failure is avoided as the applications are loosely coupled. 25-Aug-2017 62 of 99
- 63. Message-Oriented Middleware (2/4) 25-Aug-2017 63 of 99
- 64. Message-Oriented Middleware (3/4) • Synchronous interaction – Both the sender and receiver are to be active at the same time. – End-to-end communication – Ex: Telephone • Asynchronous interaction – Sender and receiver are loosely coupled and are not to be active at the same time. – Store and forward communication concept is used. – Ex: e-mail 25-Aug-2017 64 of 99
- 65. Message-Oriented Middleware (4/4) • Coupling – The pairing of two items/applications. – Types of coupling • Loosely coupled: The two different applications can interact without adapting to the source or target systems. • Tightly coupled: The two systems/applications are said to be tightly coupled if they cannot interact with one another because of the difference. i.e. Two different systems cannot interact. 25-Aug-2017 65 of 99
- 66. IBM Websphere MQ (1/3) • Message-Oriented Middleware from IBM. • Introduced in 1993 as MQ Series. • Can make communication possible for applications running on powerful machines like servers with applications running on systems less powerful like mobile devices and tablets. • Queues – Used to store all messages that are waiting to be processed or routed. • MQ Objects – Queue Manager, Channels, Messaging • Messaging – Programs communicate by sending data in messages. 25-Aug-2017 66 of 99
- 67. IBM Websphere MQ (2/3) • Queue Managers – Piece of software which is responsible for accepting and delivering messages. • Channels – Provides a communication path between Queue Managers on the same/different platforms. • Applications put their messages on the queue -> Queues act as a temporary storage space for messages till the receiving application picks up the message. 25-Aug-2017 67 of 99
- 68. IBM Websphere MQ (3/3) 25-Aug-2017 68 of 99
- 70. Cluster Deployment • Server Cluster – Set of servers that is grouped together and managed together to share work load. – Provides high availability, scalability and manageability for various applications and resources. • The servers (nodes) in the cluster remain in constant communication, if any one of the node in the cluster fails, another node begins to provide service. • Clustering enables Enterprise applications to scale beyond the limits of one server. – Applications hosted to be highly available as there are other servers to run the application in case of failure at one server. 25-Aug-2017 70 of 99
- 71. Benefits of Server Clustering (1/2) • Implementing clustering technologies ensure high availability for mission critical applications and services and the operations of a failed node are immediately resumed by another node in the cluster. • Cluster technologies also reduce single points of failure on your network because they provide a higher level of availability. • Nodes in the cluster are also able to automatically resume its previous operations if it is brought online again. This basically means that no manual configuration is necessary to initiate the failback process. 25-Aug-2017 71 of 99
- 72. Benefits of Server Clustering (2/2) • Cluster Service enables access to resources and services during planned downtime. There is no need to interrupt client access. • Clustering technologies reduce downtime associated with scheduled maintenance because you can move the operations of one node to another node before you perform any upgrades. 25-Aug-2017 72 of 99
- 74. Web Tier Deployment (1/5) • Multi tier architecture consists of – Client tier – Web tier – Business logic tier – Database tier 25-Aug-2017 74 of 99
- 75. Web Tier Deployment (2/5) • Client tier – Browsers and other applications that the user uses to connect the enterprise application from a remote location through network. • Web Tier – HTTP Server serves static HTTP content and routes incoming HTTP requests to the application server. • Business Logic Tier – Application Server hosts the enterprise application, which consists of dynamic web pages and application business logic. • Database Tier – Database Server Hosts the database to store business data for the application. 25-Aug-2017 75 of 99
- 76. Web Tier Deployment (3/5) 25-Aug-2017 76 of 99
- 77. Web Tier Deployment (4/5) • Network Aspects – HTTP Server which the user is connecting should be in Demilitarized zone. – Application server and Database servers are placed in more secure internal network. – All the requests are routed through the HTTP server. • Demilitarized Zone (DMZ) – In order to provide security to web server, the web server is kept between two firewalls. The area between these two firewalls is called DMZ. • First firewall between Internet and Web server stops the unwanted traffic • The firewall between Web server and Intranet keeps the intranet secure from unauthorized access. 25-Aug-2017 77 of 99
- 78. Web Tier Deployment (5/5) 25-Aug-2017 78 of 99
- 79. Application Servers • Application server provides the environment for an enterprise application to run. • Application servers host the business logic for the client applications using various protocols including HTTP. • Web server provides static pages whereas the application server enhances the capability of webserver by providing dynamic, customized pages by executing the business logic. 25-Aug-2017 79 of 99
- 81. Introduction (1/2) • “Lotus Notes” was developed in 1989 by Lotus Development Corporation. • IBM bought the Lotus Corporation in 1995 and it became known as the “Lotus Development division” of IBM and later in 2015 called “IBM Collaboration Solutions”. • IBM Notes (earlier Lotus Notes) & IBM Domino (earlier Lotus Domino) are the client and server of a collaborative client- server software platform sold by IBM. 25-Aug-2017 81 of 99
- 82. Introduction (2/2) • Components of the IBM Notes & Domino product – IBM Notes client application (Based on Eclipse since version 8) – IBM Notes client • A rich client • A web client (E.g. IBM iNotes) • A mobile email client (E.g. IBM Notes Traveler) – IBM Domino server (E.g. IBM XWorks server) • A cross platform application server which supports data replication to other servers and clients for offline access – IBM Domino Administration Client – IBM Domino Designer (Eclipse-based IDE) • Creating client-server applications that run within Notes framework. 25-Aug-2017 82 of 99
- 83. Lotus Architecture • IBM Lotus Domino Server and Lotus Notes client works together to integrate client and server environment. 25-Aug-2017 83 of 99
- 84. Lotus Notes • IBM Notes can be used as an email client without an IBM Domino server, for example, as an IMAP client • Lotus Notes clients can access Lotus Domino data both on Servers & in the local machine providing portable access to the data. – IBM Notes can also be used with other IBM Domino applications and databases. • IBM Notes and Domino – Provides Standard Application include: e-mail, calendars, to-do list, contact management, discussion forum, file sharing, and instant messaging. – In addition to these standard applications, an organization may use • IBM Domino Designer (development environment) & • Other tools (develop additional integrated applications such as request approval/workflow and document management). 25-Aug-2017 84 of 99
- 85. Lotus Notes Database (1/3) • Lotus notes database file extension is *.nsf – i.e. Notes Storage Facility (*.ncf). • Each database file has its own security called Access Control List. • Access Control List – Lotus Domino and Notes uses access control list to determine the level of access of users and servers to database. • Levels assigned to users determine the tasks that users can perform on a database. • The 7 access levels in Lotus Domino and Notes are – No access, Depositor, Reader, Author, Editor, Designer, Manager 25-Aug-2017 85 of 99
- 86. Lotus Notes Database (2/3) Access level Allows users to Assign to Manager • Modify the database ACL. • Encrypt the database. • Delete the database. • Perform all tasks allowed by lower access levels. Two people who are responsible for the database. Then if one person is absent, the other can manage the database. Designer • Modify all database design elements. • Perform all tasks allowed by lower access levels. A database designer and/or the person responsible for future design updates. Editor • Create documents. • Edit all documents, including those created by others. • Read all documents Any user allowed to create and edit documents in a database. 25-Aug-2017 86 of 99
- 87. Lotus Notes Database (3/3) Access level Allows users to Assign to Author • Create documents • Edit the documents where there is an Authors field in the document and the user is specified in the Authors field. Users who need to contribute documents to a database. Reader • Read documents Users who only need to read documents in a database but not create or edit documents. Depositor • Create documents, but otherwise has no access Users who only need to contribute documents but who do not need to read or edit their own or other users' documents. No Access • Has no access. Terminated users, users who do not need access to the database, or users who have access on a special basis. 25-Aug-2017 87 of 99
- 88. Lotus Domino (1/7) • Lotus Domino Server is a computer that stores the Lotus notes applications and runs services that manipulate Lotus Notes data. • During the installation of the Domino Server, there are three server set-ups. – Domino Utility Server – Domino Messaging Server – Domino Enterprise Server – Custom Domino Server 25-Aug-2017 88 of 99
- 89. Lotus Domino (2/7) 25-Aug-2017 89 of 99
- 90. Lotus Domino (3/7) • Domino Utility Server – Provides Application services only. – It supports Domino clusters. – This server does not include Messaging services. • Domino Messaging Server – Provides Messaging services. – Does not support Application services or Domino clusters. • Domino Enterprise Server – Provides both Messaging services and Application services. • Customize Domino Server – Provides customized services. – We can select the services according to our requirement. 25-Aug-2017 90 of 99
- 91. Lotus Domino (4/7) • Lotus Domino Server Files – Names.nsf • Contains detailed information about users, groups, servers for managing the domino servers. – Admin4.nsf • This file tracks and stores information about administration tasks. – Certlog.nsf • Maintains certified lotus domino IDs. – Events4.nsf • Stores information about monitoring tools & list of server messages. – Log.nsf • Stores information about performance, statistics of domino server. – Mail.box • Stores mail from a user that is in route to the other users. 25-Aug-2017 91 of 99
- 92. Lotus Domino (5/7) • Server Document – Registration with Domino Server implies the following • Create a server ID for the new server & certify it with certifier ID. • Create a Server document for the new server in the Domino Directory. • Encrypt and attach the server ID to the Server document and also save on a disk/file on the server. • Add the server name to the “LocalDomainServers” group in the Domino Directory. • Create an entry for the new server in the Certification Log (CERTLOG.NSF). – Review: What is a Server Document? 25-Aug-2017 92 of 99
- 93. Lotus Domino (6/7) • Internet Services – During the installation of Domino server the following Internet Services can be opted • Web browsers (HTTP services) • Internet mail clients (SMTP, POP3 and IMAP services) • Directory services (LDAP services) 25-Aug-2017 93 of 99
- 94. Lotus Domino (7/7) • Lotus Domino Organization – A Lotus Domino organization defines the naming hierarchy for a Lotus Domino environment. – Organization name can be the same as the domain name. • Organization Units – An Organization unit defines as organizations hierarchy as it relates to the people. – It represents the geographical locations or the department name. • Organization Certifiers – Organization certifiers is a special file created during the first lotus domino server setup in the organization. – Organization certifieris used to certify the resources in the entire infrastructure. 25-Aug-2017 94 of 99
- 95. Lotus Notes Client (1/4) • Types – Standard Client • Standard client runs on top of the eclipse framework. • The user interface is re-designed in mail, calendar and contacts of instant messaging. – Basic Client • Basic client resembles like the older version of lotus notes interface and the functionality. 25-Aug-2017 95 of 99
- 96. Lotus Notes Client (2/4) • Client Installation – Lotus Notes • This application is used for working with lotus notes applications like email, calendar etc. • We can use this application for other mail server’s client using POP3, IMAP and SMTP. – Lotus Designer • This application is used for adding or changing functionality to the new or existing lotus notes application. – Domino Administrator • This application is used for administering the domino server systems. 25-Aug-2017 96 of 99
- 97. Lotus Notes Client (3/4) • Client Installation (contd.) – Productivity Tools • Productivity tools are used to complete day to day activities more efficiently using applications like documents, spread sheets and presentation files. – Notes ID • ID file is an identification file created during the server creation (called Server ID), and user creation (called User ID). • An ID file has the information about their name, security certificates, password and the private and the public key. 25-Aug-2017 97 of 99
- 98. Lotus Notes Client (4/4) • Types of Certificates – Notes Certificates • Stored in ID file that associate with the public key. • Certificates are used to authorize the users and the servers to access the Domino server. – Internet (X.509) Certificates • Used to access a server using SSL authentication. • Internet certificates are also stored in the Lotus notes ID file. 25-Aug-2017 98 of 99