The document provides answers to common interview questions about Oracle Business Intelligence Enterprise Edition (OBIEE), which was previously known as Siebel Analytics. It defines key terms like repository and metadata repository. It also describes the end-to-end lifecycle of a Siebel Analytics project and explains concepts like the three-layer architecture, connection pools, alias tables, and different ways to implement security and manage caching.
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Chapter 5: Discrete Probability Distribution
5.2 - Binomial Probability Distributions
O documento discute o que é estatística e como ela é usada em diferentes contextos. A estatística envolve a coleta, organização e análise de dados, e pode ser usada para salvar vidas, como Florence Nightingale demonstrou, e para avaliar o desempenho esportivo. Clubes usam estatísticas para avaliar jogadores e o Manchester City busca inspirar mudanças na maneira como os dados são analisados.
Este documento descreve o uso de pilhas como listas encadeadas para implementar uma calculadora de notação pós-fixa ou polonesa reversa (NPR). Apresenta uma classe PilhaSE que implementa uma pilha como lista encadeada e mostra como usar esta pilha para avaliar expressões matemáticas escritas em notação pós-fixa, empilhando e desempilhando operandos e realizando operações de acordo com os operadores encontrados. Por fim, sugere atividades como melhorar a calculadora e criar um programa para converter notação infixa em
Este documento apresenta uma aula introdutória sobre estatística ministrada pelo professor João Alessandro em julho de 2012, abordando a definição do tema e suas principais características.
O documento descreve o uso do programa estatístico SPSS para análises estatísticas. Ele discute como criar um banco de dados no SPSS, definir variáveis e inserir dados. Também explica estatísticas descritivas básicas como tabelas de frequência que podem ser geradas no SPSS para resumir dados.
1) Os alunos da turma 5oA responderam a um inquérito sobre seus gêneros de filme preferidos.
2) Francisco organizou os resultados em uma tabela de frequência absoluta que mostrava animação, romance, policial e outros como as categorias mais populares.
3) Ele criou um gráfico de barras para representar visualmente os dados da tabela e mostrar que a animação era o gênero preferido.
O documento discute a importância da estatística no nosso dia-a-dia e em diversas áreas como saúde, economia e engenharia. A estatística pode ser descritiva, para descrever uma realidade, ou indutiva, para estudar características de uma população a partir de uma amostra. Gráficos e tabelas são ferramentas importantes para organizar e visualizar dados estatísticos.
Este documento explica conceitos básicos de estatística, incluindo: (1) estatística serve para coletar, organizar e interpretar dados para tirar conclusões e previsões; (2) população e amostra são conjuntos de elementos estudados; (3) variáveis podem ser qualitativas ou quantitativas. Ele também apresenta um exemplo de construção de tabela de frequências e gráfico de barras para organizar dados sobre número de irmãos de alunos.
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Chapter 6: Normal Probability Distribution
6.1: The Standard Normal Distribution
The document discusses various measures of central tendency and standard scores used to compare scores from different tests. It defines mean, median and mode as measures of central tendency, and explains how the normal distribution results in a bell-shaped curve. It then discusses converting raw scores to standard scores using z-scores and t-scores in order to compare scores from different tests on a common scale. Z-scores indicate the distance from the mean in standard deviations, while t-scores have a mean of 50 and standard deviation of 10.
Uma breve aula sobre teoria dos conjuntos, aula que ministro para alunos de ENEM, concursos militares e matemática para negócios. Visite nosso site e conheça mais a Coens Cursos e Concursos.
Este documento discute variáveis aleatórias discretas e a distribuição binomial. Apresenta as características de uma variável aleatória binomial, incluindo que o experimento deve ser repetido um número fixo de vezes de forma independente, com cada repetição sendo um experimento de Bernoulli. Fornece a notação e propriedades da distribuição binomial, como a fórmula para calcular probabilidades e exemplos numéricos de lançar uma moeda.
O documento apresenta conceitos básicos sobre matrizes, incluindo:
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2) Uma matriz identidade I é uma matriz quadrada com uns na diagonal principal e zeros nos demais elementos;
3) A soma de duas matrizes do mesmo tipo resulta em uma matriz do mesmo tipo obtida somando elementos da mesma posição.
This section discusses five methods for counting the number of possible outcomes in various situations: the multiplication counting rule, factorial rule, permutation rule, permutations rule when some items are identical, and combination rule. It provides examples of counting the number of ways to arrange presidents to visit, rank locations, select ads for different parts of a show, and choose books to review. The examples illustrate how to apply the different counting rules to determine the total number of possible outcomes.
O documento descreve o sistema de coordenadas cartesianas e funções polinomiais do 1o grau. Explica como construir um sistema cartesiano com duas retas perpendiculares e atribuir coordenadas aos pontos. Também define o que é uma função, domínio, conjunto imagem e como representar graficamente funções polinomiais do 1o grau, encontrando seus zeros.
The SUMIFS function allows users to sum a range of cells based on multiple criteria. It can check multiple criteria ranges, unlike the SUMIF function which only checks one criteria. Operators like >, <, = can be used in criteria. The syntax includes specifying the sum range, criteria ranges, and criteria. Examples demonstrate summing values where corresponding cells meet criteria like being greater than 1000 and equal to "East". Cell references can also be used for dynamic criteria evaluation.
Hypothesis testing chi square test for independenceNadeem Uddin
This document discusses how to conduct a chi-square test for independence using an example of testing whether a sports team's results are independent of the weather. It explains that the chi-square test is used to determine if there is a significant association between two categorical variables. The procedure involves defining hypotheses, selecting a significance level, calculating the test statistic by summing the squared differences between observed and expected values divided by expected values, comparing the test statistic to a critical value, and making a conclusion about whether to reject or accept the null hypothesis. For the example, the calculated test statistic is less than the critical value, so the null hypothesis that the team's results are independent of the weather is accepted.
This document provides an overview of measures of central tendency including the mean, median, and mode. It discusses how to calculate and interpret each measure using examples with data sets. The mean is calculated by adding all values and dividing by the total number. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently. Other measures discussed include the midrange and calculating the mean from a frequency distribution. Proper rounding of measures is also covered.
Este documento fornece uma introdução à teoria elementar de probabilidades. Discute conceitos básicos como espaço amostral, eventos, probabilidade, operações com eventos e axiomas da probabilidade. Explica como calcular a probabilidade de eventos simples em experimentos aleatórios como lançar dados e retirar cartas de um baralho.
This document provides steps for installing OBIEE 10.1.3.4 server on Windows, including downloading required software, running the executable file, selecting a basic or advanced installation mode, specifying JDK and database locations, verifying installed components, and default usernames and passwords.
JSBI Presentation Big Data Hyperion OBIEE Integration16 2Jeff Shauer
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Real-Time Data Warehousing using Oracle Database and OBIEE - Collaborate'11Mark Rittman
Presentation by Stewart Bryson, Rittman Mead, on real-time data warehousing techniques using the Oracle Database and Oracle Business Intelligence Enterprise Edition. As delivered at Collaborate'11, Orlando, April 2011.
This document provides a three-part summary of building financial reports and dashboards using Oracle Business Intelligence Enterprise Edition (OBIEE) with Essbase as the data source:
1. It outlines the steps to prepare the repository planning document (RPD) by importing the Essbase cube and associated dimensions, hierarchies, and measures into the physical layer of the RPD.
2. It describes how to build the business model and mapping layer by dragging the physical cube into these layers to automatically generate the associated dimensions and relationships.
3. It discusses setting up the presentation layer by dragging objects from the business model layer into catalogs for ad-hoc analysis and testing.
The document discusses Oracle Business Intelligence on cloud computing. It begins with an agenda that covers an introduction to cloud computing, why BI on cloud, options for implementing OBIEE on cloud, challenges and tradeoffs, and demonstrations. It then discusses what cloud computing is and why BI is attractive for cloud. Several options for implementing OBIEE on cloud are presented, along with key challenges. Creative approaches to addressing challenges are explored through mind mapping. The options and tradeoffs involved in balancing priorities and challenges are examined. The presentation concludes with an overview of the company's cloud computing offerings and a demonstration.
Obiee 12c: Look under the bonnet and test driveGuillaume Slee
Presentation from the Infratects Top Gun conference in Berlin, 2016. We'll look at the simplified installation, architecture and administration that OBIEE 12c offers and examine the 11g to 12c out-of-place upgrade.
Obiee and Essbase Integration | MindStream Analysismindstremanalysis
MindStream Analytics can help you learn more about Essbase and its full analytic capabilities. MindStream’s experienced staff includes former Hyperion Essbase developers and certified Hyperion Essbase consultants. We hold various positions throughout the Essbase community including the Oracle Application User Group’s (OAUG) Hyperion Special Interest Group Domain Lead for Essbase. MindStream has the expertise to make your next Essbase implementation a success.
With the launch of OBIEE 11g we can look at some of the key new features in this release. The most obvious changes in OBIEE 11g is around the visual look and feel of the web-based components. Few of the features that we will go through are KPIs and scorecards that are newly introduced and widely used in Oracle BI and KPIs can be manifested as a stand-alone metric or part of a watchlist on a dashboard; and selections that limit the members for a column after aggregation, affecting the display of data in your analysis.
Introduction to OBIEE Metadata
Use of Administration Tool
Concepts of Physical Layer
Concepts of Business Model and Mapping Layer
Concepts of Presentation Layer
Building of these 3 layers
The document discusses new features and enhancements in Oracle Business Intelligence 12c, including:
- Improved front-end usability features like an updated home page, enhanced sorting, and view properties access in compound layouts.
- New data visualization options like Oracle Data Visualization for ad-hoc analysis and mashups of spreadsheets with existing subject areas.
- Changes to installation, configuration, and architecture like a simplified installation process and separation of environment metadata from configuration.
- Upgrades are supported from 11g using a new Baseline Validation Tool to test and compare systems before and after upgrades.
OBIEE Security: It’s a Jungle Out ThereGianni Ceresa
OBIEE developer or administrator, manager, or user - the security of the data displayed as well as the functionality available is the most crucial thing to get right. Whether on OBIEE 11g or 12c, security is all too often the same story: Sounds simple, but many developers underestimate the complexity of a coherent, comprehensive, and successful system-wide security strategy.
Often the final solution is a mix of simple or no security and complex "tactical" solutions (hacks), and each new additional project just adds more chaos.
In this session we will discuss in detail the different security layers of OBIEE (RPD, Presentation Service, and Catalog), and a standard and universal approach will be offered. This solution is able to match most requirements while remaining flexible enough to be extended for the most extreme needs. From the small departmental setup to a full corporate BI solution: a single model to rule them all.
How to Integrate OBIEE and Essbase / EPM Suite (OOW 2012)Mark Rittman
Oracle plans to integrate Oracle Essbase and the EPM product suite with Oracle Business Intelligence Enterprise Edition and Oracle Fusion Middleware. So with the latest release of Oracle Business Intelligence Enterprise Edition, 11.1.1.6, how do you connect Oracle Business Intelligence Enterprise Edition to your Oracle Essbase databases and how well does it handle Oracle Essbase features such as scenario and account dimensions, changing outlines, and unbalanced/parent-child hierarchies? How well do Oracle Business Intelligence Enterprise Edition’s ad hoc reporting tools handle Oracle Essbase hierarchies and member selections in the 11.1.1.6 release? Can we still embed Oracle Business Intelligence Enterprise Edition dashboards in Oracle Workspaces? Learn the answers in this session.
The document provides instructions for installing OBIEE 11g, including prerequisites like having Oracle 11g already installed, running the Repository Creation Utility to set up schemas, and configuring the weblogic domain. It also describes loading a sample SalesApp repository and verifying the change in the NQSConfig.ini file. The document concludes by providing contact details for the company iWare Logic that specializes in Oracle applications and technologies.
This document provides an overview of Oracle BIEE (Business Intelligence Enterprise Edition) including its components, advantages, architecture, and features. It discusses Oracle BIEE Answers and interactive dashboards. Key components include Oracle BI Client, Presentation Services, Server, Repository, Scheduler, Answers, and Interactive Dashboards. Benefits include simplified report production, insights, and a single version of truth. The presentation concludes with information on iWare Logic's Oracle BIEE services.
The document provides an overview of Oracle's BI product OBIEE (Oracle Business Intelligence Enterprise Edition), formerly known as Siebel Analytics. It discusses Oracle's BI strategy and architecture, as well as key features of OBIEE configuration, development, and the 11g release. Links are provided for additional product details on Oracle's website.
Here are some list of important interview questions that we've put together. A comprehensive list of questions to help you get through your first interview. We've made sure that the most probable questions asked during interviews are covered in this list. START LEARNINIG OBIEE 11g Here : www.wiziq.com/course/15860
This document provides a three-part summary of building financial reports and dashboards using Oracle Business Intelligence Enterprise Edition (OBIEE) with Essbase as the data source:
1. It outlines the steps to prepare the repository planning document (RPD) by importing the Essbase cube and associated dimensions, hierarchies, and measures into the physical layer of the RPD.
2. It describes how to build the business model and mapping layer by dragging the physical cube into these layers to automatically generate the associated dimensions and relationships.
3. It discusses setting up the presentation layer by dragging objects from the business model layer into catalogs for ad-hoc analysis and testing.
This document provides a three-part summary of building financial reports and dashboards using Oracle Business Intelligence Enterprise Edition (OBIEE) with Essbase as the data source:
1. It outlines the steps to prepare the repository planning document (RPD) by importing the Essbase cube and associated dimensions, hierarchies, and measures into the physical layer of the RPD.
2. It describes how to build the business model and mapping layer by dragging the physical cube into these layers to automatically generate the associated dimensions and relationships.
3. It discusses setting up the presentation layer by dragging objects from the business model layer into catalogs for ad-hoc analysis and testing.
The document summarizes new features in Oracle Hyperion Calculation Manager Release 11.1.2.4.000, including:
- Support for parallel processing in member range components to optimize calculations.
- Ability to deploy Essbase rules with runtime prompts directly to Essbase.
- Import of Essbase calc scripts with runtime prompt variables.
- New design-time prompt functions and custom defined functions.
- Ability to search and replace text in the Variable Designer.
Obiee11g building logical dimension hierarchyAmit Sharma
This document provides step-by-step instructions for building a logical dimension hierarchy in OBIEE 11g. It covers creating the logical dimension object, adding levels and keys, setting the preferred drill path, creating presentation hierarchies, testing the hierarchy, and creating level-based and shared measures. Building the hierarchy involves defining the parent-child relationships between attributes, adding logical levels and keys, and mapping the hierarchy to presentation layers where it can be used in analysis.
Microsoft SQL Server 2008 Analysis Services provides unified views of business data to support OLAP, KPI scorecards, and data mining. It allows for reporting, OLAP analysis, partitioning cubes across servers for scalability, and defining security roles and dimension security. MDX is the query language used to analyze cube data.
The document provides an overview of a Power BI training course. The course objectives include learning about connecting to data sources, transforming data, building data model relationships, using DAX functions to transform data, and creating visualizations. It discusses topics like importing data from CSV and Excel files into Power BI, using Power Query to transform data, establishing relationships between tables in the data model, using measures and columns with DAX, and building basic and dynamic visualizations. It also provides resources for sample data files and additional learning materials for the course.
This document discusses the Excel add-in for data mining. It allows users to mine data with a few clicks using advanced algorithms without needing experience in data mining or SQL server configuration. The add-in contains sections for data preparation, modeling, accuracy validation, and connection. Data can be explored, cleaned, and prepared for modeling. Common modeling techniques like classification, estimation, clustering and association are supported. Accuracy of models can be validated against real data.
This document discusses the Excel add-in for data mining. It allows users to mine data with a few clicks using advanced algorithms without needing experience in data mining or SQL server configuration. The add-in contains sections for data preparation, modeling, accuracy validation, and connection. Data can be explored, cleaned, and prepared for modeling. Common modeling algorithms like decision trees, clustering, and association rules are available. Accuracy and validation tools allow testing models on real data. The add-in combines the power of SQL Server Analysis Services with the ease of use of Excel.
Create a basic performance point dashboard epcEPC Group
This document provides instructions for creating a basic PerformancePoint dashboard with three key elements:
1) It describes creating a simple dashboard that contains a scorecard, an analytic grid report, and a filter.
2) It orients the user to the Dashboard Designer user interface which is divided into four main areas: the ribbon, workspace browser, center pane, and details pane.
3) It guides the user through creating the dashboard items - selecting a data source, creating an analytic grid report to display data from the source, selecting or creating KPIs, and then generating a scorecard and filter to populate the new dashboard.
Solved Practice questions for Microsoft Querying Data with Transact-SQL 70-76...KarenMiner
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The document provides information on using the BEX Query Designer in SAP BW. It describes key components of the Query Designer including info providers, query elements, variables, reusable structures, formulas, and calculated key figures. The Query Designer allows users to define queries, filters, and calculations not available directly in the info providers to retrieve and analyze data from SAP BW.
This document summarizes a presentation given by Mohammed Imran Alam of ActiveHealth on integrating Xcelsius and Crystal Reports. The presentation covered using the OpenDocument method for hierarchical drilldowns, creating list of values (LOVs) using universe prompts, customizing parameters in Crystal Reports, and tips for improving performance. Integration methods discussed included using Flash variables, XML variables, and the Crystal data consumer. The presenter provided resources and emphasized using dynamic sorting, wildcards in prompts, and the OpenDocument method for drilldowns and hyperlinks.
The document discusses designing dimensional models for data warehouses and business intelligence systems. It provides an overview of key concepts in dimensional modeling including facts, dimensions, and the importance of conformed dimensions to enable analysis across multiple business processes. It also describes the process of designing dimensional models, including defining facts and dimensions, bringing them together into a star schema, and using a bus matrix to map business processes to dimensional models.
The document discusses interfacing with end users in ASP.NET. It provides two programming models - Web Forms and WCF Services. Web Forms enables creating user interfaces and application logic, while WCF Services enables remote server-side functionality access. It also discusses creating a basic web form in ASP.NET that displays the current date and time when a button is clicked to demonstrate the Web Forms model. Common controls like labels, textboxes, buttons are also summarized with their properties and events.
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The document defines conceptual, logical, and physical data models and compares their key features. A conceptual model shows entities and relationships without attributes or keys. A logical model adds attributes, primary keys, and foreign keys. A physical model specifies tables, columns, data types, and other implementation details.
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Obiee interview questions and answers faq
1. OBIEE Interview Questions and Answers FAQ
admin
Categories: Business Intelligence
OBIEE Interview Questions and Answers FAQ
These questions are related to what previously known as Siebel Analytics is now known as
OBIEE i.e Oracle Business Intelligence Enterprise Edition.
” Define repository in terms of Siebel Analytics
o Repository stores the Meta data information. Siebel repository is a file system ,extension
of the repository file. rpd.
o META DATA REPOSITORY
o With Siebel Analytics Server, all the rules needed for security, data modeling, aggregate
navigation, caching, and connectivity is stored in metadata repositories.
o Each metadata repository can store multiple business models. Siebel Analytics Server
can access multiple repositories
” What is the end to end life cycle of Siebel Analytics?
o Siebel Analytics life cycle
1. Gather Business Requirements
2. Identify source systems
3. Design ETL to load to a DW if source data doesn’t exist.
4. Build a repository
5. Build dashboard or use answers for reporting.
6. Define security (LDAP or External table…)
7. Based on performance, decide on aggregations and/or caching mechanism.
8. Testing and QA.
” What were you schemas? How does Siebel Architecture works? Explain the three
layers. How do you import sources?
o There are five parts of Siebel Architecture.
1. Clients
2. Siebel analytics Web Server
3. Siebel analytics server
4. Siebel analytics scheduler
5. data sorces
o Metadata that represents the analytical Model Is created using the siebel Analytics
Administration tool.
o Repository divided into three layer
1. Physical – Represents the data Sources
2. Business – models the Data sources into Facts And Dimension
3. Presentation – Specifies the users view of the model;rendered in Siebel answer
” If you have 3 facts and 4 dimension and you need to join would you recommend
joining fact with fact? If no than what is the option? Why you won’t join fact to fact?
o In the BMM layer, create one logical table (fact) and add the 3 fact table as logical table
source
2. ” What is connection pool and how many connection pools did you have in your last
project?
o connection pool is needed for every physical database.
o It contains information about the connection to the database, not the database itself.
o Can use either shared user accounts or can use pass-through accounts -Use: USER and
PASSWORD for pass through .
o We can have multiple connection pools for each group to avoid waitin
” Purpose of Alias Tables
o An Alias table (Alias) is a physical table with the type of Alias. It is a reference to a logical
table source, and inherits all its column definitions and some properties from the logical
table source. A logical table source shows how the logical objects are mapped to the
physical layer and can be mapped to physical tables, stored procedures, and select
statements. An alias table can be a reference to any of these logical table source types.
o Alias Tables can be an important part of designing a physical layer. The following is a list
of the main reasons to create an alias table:
” To reuse an existing table more than once in your physical layer (without having to import
it several times)
” To set up multiple alias tables, each with different keys, names, or joins
o To help you design sophisticated star or snowflake structures in the business model layer.
Alias tables are critical in the process of converting ER Schemas to Dimensional Schemas.
” How do you define the relationship between facts and dimensions in BMM layer?
o Using complex join ,we can define relationship between facts and dimentions in BMM
layer.
” What is time series wizard? When and how do you use it?
o We can do comparison for certain measures ( revenue.,sales etc.. ) for current year vs
previous year, we can do for month or week and day also
o Identify the time periods need to be compared and then period table keys to the previous
time period.
o The period table needs to contain a column that will contain “Year Ago” information.
o The fact tables needs to have year ago totals.
o To use the “Time series wizard”. After creating your business model right click the
business model and click on “Time Series Wizard”.
o The Time Series Wizard prompts you to create names for the comparison measures that
it adds to the business model.
o The Time Series Wizard prompts you to select the period table used for the comparison
measures
o Select the column in the period table that provides the key to the comparison period. This
column would be the column containing “Year Ago” information in the period table.
o Select the measures you want to compare and then Select the calculations you want to
generate. For ex: Measure: Total Dollars and calculations are Change and Percent change.
o Once the Time series wizard is run the output will be:
a) Aliases for the fact tables (in the physical layer)
b) Joins between period table and alias fact tables
c) Comparison measures
d) Logical table sources
3. o In the General tab of the Logical table source etc you can find “Generated by Time Series
Wizard” in the description section
o Then you can add these comparision measures to the presentation layer for your reports.
o Ex: Total sales of current qtr vs previous qtr vs same qtr year ago
” Did you create any new logical column in BMM layer, how?
o Yes. We can create new logical column in BMM layer.
o Example: Right click on fact table -new lgical column-give name for new logical column
like Total cost.
o Now in fact table source,we have one option column mapping, in that we can do all
calculation for that new column.
” Can you use physical join in BMM layer?
o yes we can use physical join in BMM layer.when there is SCD type 2 we need complex
join in BMM layer.
” Can you use outer join in BMM layer?
o yes we can.When we are doing complex join in BMM layer ,there is one option type,outer
join is there.
” What are other ways of improving summary query reports other than Aggregate
Navigation and Cache Management
” Indexes
” Join algorithm
” Mat/view query rewrite
” Web proper report design its optimal by making sure that it is not getting any addition
column or rows
” What is level-base matrics?
o Leval-base matrics means, having a measure pinned at a certain level of the dimension.
For Example, if you have a measure called “Dollars”, you can create a “Level Based
Measure” called “Yearly Dollars” which (you guessed it) is Dollars for a Year. This measure
will always return the value for the year even if you drill down to a lower level like quarter,
month… etc. To create a level based measure, create a new logical column based on the
original measure (like Dollars in the example above). Drag and drop the new logical column
to the appropriate level in the Dimension hierarchy (in the above example you will drag and
drop it to Year in Time Dim
o A LBM is a metric that is defined for a specific level or intersection of levels.
o Monthly Total Sales or Quarterly Sales are the examples.
o You can compare monthly sales with quarterly sales. You can compare customer orders
this quarter to orders this year
” What is logging level?Where can you set logging levels?
o You can enable logging level for individual users; you cannot configure a logging level for
a group.
o Set the logging level based on the amount of logging you want to do. In normal
operations, logging is generally disabled (the logging level is set to 0). If you decide to
enable logging, choose a logging
4. o level of 1 or 2. These two levels are designed for use by Siebel Analytics Server
administrators.
o Set Logging Level
1. In the Administration Tool, select Manage > Security.
2. The Security Manager dialog box appears.
3. Double-click the user.s user ID.
4. The User dialog box appears.
5. Set the logging level by clicking the Up or Down arrows next to the Logging Level field
” What is variable in sieble?
o You can use variables in a repository to streamline administrative tasks and modify
metadata content dynamically to adjust to a chainging data environment.The Administration
Tool includes a Variable Manager for defining variables
” What is system variable and non system variable?
o System variables
o System variables are session variables that the Siebel Analytics Server and Siebel
Analytics Web use for specific purposes. System variables have reserved names, which
cannot be used for other kinds of variables (such as static or dynamic repository variables,
or for nonsystem session variables).
o When using these variables in the Web,preface their names with NQ_SESSION. For
example, to filter a column on the value of the variable LOGLEVEL set the filter to the
Variable NQ_SESSION.LOGLEVEL.
o Nonsystem variables.
o A common use for nonsystem session variables is setting user filters. For example, you
could define a nonsystem variable called SalesRegion that would be initialized to the name
of the user.s sales region. You could then set a security filter for all members of a group that
would allow them to see only data pertinent to their region.
o When using these variables in the Web, preface their names with NQ_SESSION. For
example, to filter a column on the value of the variable SalesRegion set the filter to the
Variable NQ_SESSION.SalesRegion.
” What are different types of variables? Explain each.
o There are two classes of variables:
1. Repository variables
2. Session variables.
Repository variables.
A repository variable has a single value at any point in time. There are two types of
repository variables:
static : This value persists, and does not change until a Siebel Analytics Server
administrator decides to change it.
dynamic:The values are refreshed by data returned from queries. When defining a dynamic
repository variable, you will create an initialization block or use a preexisting one that
contains a SQL query. You will also set up a schedule that the Siebel Analytics Server will
follow to execute the query and periodically refresh the value of the variable.
Session Variables
Session variables are created and assigned a value when each user logs on. There are two
types of session variables:
5. 1.system
2.nonsystem.
” What are the cache management? Name all of them and their uses. For Event
polling table do u need the table in your physical layer?
o Monitoring and managing the cashe is cache management.There are three ways to do
that.
o Disable caching for the system.(INI NQ config file), Cashe persistence time for specified
physical tables and Setting event polling table.
o Disable caching for the system.(INI NQ config file :
You can disable caching for the whole system by setting the ENABLE parameter to NO in
the NQSConfig.INI file and restarting the Siebel Analytics Server. Disabling caching stops
all new cache entries and stops any new queries from using the existing cache. Disabling
caching allows you to enable it at a later time without losing any entries already stored in
the cache.
o Cashe persistence time for specified physical tables :
You can specify a cachable attribute for each physical table; that is, if queries involving the
specified table can be added to the cache to answer future queries. To enable caching for a
particular physical table, select the table in the Physical layer of the Administration Tool and
select the option Make table cachable in the General tab of the Physical Table properties
dialog box. You can also use the Cache Persistence Time settings to specify how long the
entries for this table should persist in the query cache. This is useful for OLTP data sources
and other data sources that are updated frequently, potentially down to every few seconds.
o Setting event polling table :
Siebel Analytics Server event polling tables store information about updates in the
underlying databases. An application (such as an application that loads data into a data
mart) could be configured to add rows to an event polling table each time a database table
is updated. The Analytics server polls this table at set intervals and invalidates any cache
entries corresponding to the updated tables.
o For event polling table ,It is a standalone table and doesn’t require to be joined with other
tables in the physical layer
” What is Authentication? How many types of authentication.
o Authentication is the process by which a system verifies, through the use of a user ID and
password, that a user has the necessary permissions and authorizations to log in and
access data. The Siebel Analytics Server authenticates each connection request it receives.
” Operaing system autentication
” External table authentication
” Database authentication
” LDAP authentication
” What is object level security?
o There are two types of object level security: Repository level and Web level
o Repository level : In presention layar we can set Repository level security by giving
permission or deny permission to users/groups to see particular table or column.
o web level:thisprovides security for objects stored in the siebel anlytics web catlog,such
as dashboards,dashboards pages,folder,and reportsyou can only view the objects for which
6. you are authorized. For example,a mid level manager may not be granted access to
a dashboard containing summary information for an entire department.
” What is data level security?
o This controls the type an amount of data that you can see in a report.When multiple users
run the same report the results that are returned to each depend on their access rights and
roles in the organization.For example a sales vice president sees results for alll regions,
while a sales representative for a particular region sees onlu datafor that region.
” What is the difference between Data Level Security and Object Level Security?
o Data level security controls the type and amount of data that you can see in a
reports.Objectlevel security provides security for objects stored in the siebel analytics web
catlog, like dashboards,dashboards pages,folder,and reports.
” How do you implement security using External Tables and LDAP?
o Instead of storing user IDs and passwords in a Siebel Analytics Server repository, you can
maintain lists of users and their passwords in an external database table and use this table
for authentication purposes. The external database table contains user IDs and passwords,
and could contain other information, including group membership and display names used
for Siebel Analytics Web users. The table could also contain the names of specific database
catalogs or schemas to use for each user when querying data
o Instead of storing user IDs and passwords in a Siebel Analytics Server repository, you can
have the Siebel Analytics Server pass the user ID and password entered by the user to an
LDAP(Lightweight Directory Access Protocol ) server for authentication. The server uses
clear text passwords in LDAP authentication. Make sure your LDAP servers are set up to
allow this.
” If you have 2 fact and you want to do report on one with quarter level and the other
with month level how do you do that with just one time dimension?
o Using levelbase matrics.
” Did you work on a stand alone Siebel system or was it integrated to other
platforms?
o Deploying the Siebel analytics platform without other Siebel applications is called Siebel
analytics Stand -Alone .If your deployment includes other siebel Analytics Application it
called integrated analytics -You can say Stand-Alone siebel analytics
” How to sort columns in rpd and web?
o Sorting on web column, sort in the rpd its sort order column
” If you want to create new logical column where will you create (in repository
or dashboard) why?
o I will create new logical column in repository.because if it is in repository,you can use for
any report.If you create new logical column in dashboard then it is going to affect on those
reports ,which are on that dashboard.you can not use that new logical column for other
dashboard(or request)
7. ” What is complex join, and where it is used?
o we can join dimention table and fact table in BMM layer using complex join.when there is
SCD type 2 we have to use complex join in Bmm layer.
” If you have dimension table like customer, item, time and fact table like sale and if
you want to find out how often a customer comes to store and buys a particular item,
what will you do?
o write a query as “SELECT customer_name, item_name, sale_date, sum(qty) FROM
customer_dim a, item_dim b, time_dim c, sale_fact d WHERE d.cust_key = a.cust_key
AND d.item_key = b.item_key AND d.time_key = c.time_key GROUP BY customer_name,
item_name, sale_date”
” You worked on standalone or integrated system?
o Standalone.
” If you want to limit the users by the certain region to access only certain data, what
would you do?
o using data level security.
o Siebel Analytics Administrator: go to Manage -> Security in left hand pane u will find the
user, groups, LDAP server, Hierarchy
What you can do is select the user and right click and go to properties, you will find two tabs
named as users and logon, go to user tab and click at permission button in front of user
name you have selected as soon as u click at permission you will get a new window with
user group permission having three tabs named as general ,query limits and filter and you
can specify your condition at filter tab, in which you can select presentation table
,presentation columns ,logical table and logical columns where you can apply the condition
according to your requirement for the selected user or groups.
” If there are 100 users accessing data, and you want to know the logging details of
all the users, where can you find that?
o To set a user.s logging level
1. In the Administration Tool, select Manage > Security.
The Security Manager dialog box appears.
2. Double-click the user.s user ID. The User dialog box appears.
3. Set the logging level by clicking the Up or Down arrows next to the Logging Level field
” How do implement event polling table?
o Siebel Analytics Server event polling tables store information about updates in the
underlying databases. An application (such as an application that loads data into a data
mart) could be configured to add rows to an event polling table each time a database table
is updated. The Analytics server polls this table at set intervals and invalidates any cache
entries corresponding to the updated tables.
” Can you migrate the presentation layer only to different server
o No we can’t do only presentation layer. And ask him for more information and use one of
the above answers
o Create a ODBC connection in the different serve and access the layer.
o Copy the Rpd and migrate it to other server
8. ” Define pipeline. Did you use it in your projects?
o Yes, pipelines are the stages in a particular transaction. assessment, finance etc.
” How do you create filter on repository?
o Where condition on content tab.
” How do you work in a multi user environment? What are the steps?
o Create a shared directory on the network for Multi-user Development (MUD).
o Open the rpd to use in MUD. From Tools->Options, setup the MUD directory to point to
the above directory.
o Define projects within the rpd to allow multiple users to develop within their subject area or
Facts.
o Save and move the rpd to the shared directory setup in point 1.
o When users work in the MUD mode, they open the admin tool and start with
o MUD ->Checkout to checkout the project they need to work on (not use the File open as
you would usually do).
o After completely the development, user checkin the changes back to the network and
merge the changes.
” Where are passwords for userid? Ldap,external table authentication stored
respectively?
o passwords for userid are in siebel analytics server repository Ldap authentication in Ldap
server external database in a table in external database
” Can you bypass siebel analytics server security ?if so how?
o yes you can by-pass by setting authententication type in NQSCONFIG file in the security
section as:authentication_type=bypass_nqs.instanceconfig.xml and nqsconfig.ini are the 2
places
” Where can you add new groups and set permissions?
o you can add groups by going to manage>security>add new groups> You can give
permissions to a group for query limitation and filter conditions.
” what are the things you can do in the BMM layer?
o Aggrigation navigation,level base matrics,time series wizard,create new logical
column,comlex join.
” what is Ragged hierarchy? and how do u manage it
o Ragged Hierarchy is one of the different kinds of hierarchy.
o A hierarchy in which each level has a consistent meaning, but the branches have
inconsistent depths because at least one member attribute in a branch level is unpopulated.
A ragged hierarchy can represent a geographic hierarchy in which the meaning of each
level such as city or country is used consistently, but the depth of the hierarchy varies.
o For example, a geographic hierarchy that has Continent, Country, Province/State, and
City levels defined. One branch has North America as the Continent, United States as the
Country, California as the Province or State, and San Francisco as the City. However, the
hierarchy becomes ragged when one member does not have an entry at all of the levels.
For example, another branch has Europe as the Continent, Greece as the Country, and
Athens as the City, but has no entry for the Province or State level because this level is not
9. applicable to Greece for the business model in this example. In this example, the Greece
and United States branches descend to different depths, creating a ragged hierarchy.
” What is the difference between Single Logical Table Source and Multiple Logical
Table Sources?
o If a logical table in BMM layer has only one Table as the source table then it is Single
LTS.
o If the logical table in BMM layer has more than one table as the sources to it then it is
called Multiple LTS.
o Ex: Usually Fact table has Multiple LTS’, for which sources will be coming from different
Physical tables.
” Can you let me know how many aggregate tables you have in your project? On what basis
have you created them?
o As per resume justification document
” How do you bring/relate the aggregate tables into the Siebel analytics Logical
layer?
o One way of bringing the Aggregate Tables into the BMM layer is by bringing them as
Logical Table sources for the corresponding Fact table.
o This is done by dragging and dropping the aggregate table into the corresponding fact
table. After doing that establish the column mappings and the set the aggregation levels.
” How do you know which report is hitting which table, either the fact table or the
aggregate table?
o After running the report, go to “Administration” tab and go to click on “Manage Sessions”.
There you can find the queries that are run and in the “View Log” option in the Session
Management you can find which report is hitting which table.
” Suppose I have report which is running for about 3 minutes typically. What is the
first step you take to improve the performance of the query?
o Find the sql query of the report in Admin->manage Session-> run the sql query on toad -
>read the explain plan output ->modify the SQL based on the explain plan output
” Suppose you have a report which has the option of running on aggregate table.
How does the tool know to hit the Aggregate table and for that what the steps you
follow to configure them?
o Explain the process of Aggregate navigation
” Have you heard of Implicit Facts? If, so what are they?
o An implicit fact column is a column that will be added to a query when it contains columns
from two or more dimension tables and no measures. You will not see the column in the
results. It is used to specify a default join path between dimension tables when there are
several possible alternatives.
o For example, there might be many star schemas in the database that have the Campaign
dimension and the Customer dimension, such as the following stars:
” Campaign History star. Stores customers targeted in campaign.
” Campaign Response star. Stores customer responses to a campaign.
” Order star. Stores customers who placed orders as a result of a campaign.
In this example, because Campaign and Customer information might appear in many
10. segmentation catalogs, users selecting to count customers from the targeted campaigns
catalog would be expecting to count customers that have been targeted in specific
campaigns.
” To make sure that the join relationship between Customers and Campaigns is through the
campaign history fact table, a campaign history implicit fact needs to be specified in
Campaign History segmentation catalog. The following guidelines should be followed in
creating
” segmentation catalogs:
” Each segmentation catalog should be created so that all columns come from only one
physical star.
” Because the Marketing module user interface has special features that allow users to
specify their aggregations, level-based measures typically should not be exposed to
segmentation users in a segmentation catalog.
” What is aggregate navigation? How do you configure the Aggregate tables in Siebel
Analytics?
o Aggregate tables store precomputed results, which are measures that have been
aggregated (typically summed) over a set of dimensional attributes. Using aggregate tables
is a very popular technique for speeding up query response times in decision support
systems.
o If you are writing SQL queries or using a tool that only understands what physical tables
exist (and not their meaning), taking advantage of aggregate tables and putting them to
good use becomes more difficult as the number of aggregate tables increases. The
aggregate navigation capability of the Siebel Analytics Server, however, allows queries to
use the information stored in aggregate tables automatically, without query authors or query
tools having to specify aggregate tables in their queries. The Siebel Analytics Server allows
you to concentrate on asking the right business question; the server decides which tables
provide the fastest answers.
” (Assume you are in BMM layer) We have 4 dimension tables, in that, 2 tables need
to have hierarchy, then in such a case is it mandatory to create hierarchies for all the
dimension tables?
o No, its not mandatory to define hierarchies to other Dimension tables.
” Can you have multiple data sources in Siebel Analytics?
o Yes.
” How do you deal with case statement and expressions in siebel analytics?
o use expression builder to create case when…then.. end statement
” Do you know about Initialization Blocks? Can you give me an example where you
used them?
o Init blocks are used for instantiating a session when a user logs in.
o To create dynamic variable you have to create IB to write sql statement.
” what is query repository tool?
o It is utility of Seibel/OBIEE Admin tool
o allows you to examine the repository metadata tool
11. o for example: search for objects based on name,type.
o Examine relationship between metadata objects like which column in the presentation
layer maps to which table in physical layer
” what is JDK and why do we need it?
o Java Development Kit (JDK), A software package that contains the minimal set of tools
needed to write, compile, debug, and run Java applets.
” Oracle doesn’t recommend Opaque Views because of performance considerations,
so why/when do we use them?
o an opaque view is a physical layer table that consists of select statement. an opaque view
should be used only if there is no other solution.
” Can you migrate the presentation layer to a different server.
o No we have to migrate the whole web & rpd files
” How do you identify what are the dimension tables and how do you decide them
during the Business/Data modeling?
o Dimension tables contain descriptions that data analysts use as they query the database.
For example, the Store table contains store names and addresses; the Product table
contains product packaging information; and the Period table contains month, quarter, and
year values. Every table contains a primary key that consists of one or more columns; each
row in a table is uniquely identified by its primary-key value or values
” Why do we have multiple LTS in BMM layer?What is the purpose?
o to improve the performance and query response time.
” what is the full form of rpd?
o there is no full form for rpd as such, it is just a repository file (Rapidfile Database)
” how do i disable cache for only 2 particular tables?
o in the physical layer, right click on the table there we will have the option which says
cacheable
” How do you split a table in the rpd given the condition. ( the condition given was
Broker and customer in the same table) Split Broker and customer.
o we need to make an alias table in the physical layer.
” What type of protocol did you use in SAS?
o TCP/IP