What is aggregate table and aggregate fact table ... any examples of both?
Aggregate table contains summarised data. The materialized view are aggregated tables.
for ex in sales we have only date transaction. if we want to create a report like sales by product per year. in such cases we aggregate the date vales into week_agg, month_agg, quarter_agg, year_agg. to retrive date from this tables we use @aggrtegate function.
What is active data warehousing?
An active data warehouse provides information that enables decision-makers within an organization to manage customer relationships nimbly, efficiently and proactively. Active data warehousing is all about integrating advanced decision support with day-to-day-even minute-to-minute-decision making in a way that increases quality of those customer touches which encourages customer loyalty and thus secure an organization's bottom line. The marketplace is coming of age as we progress from first-generation "passive" decision-support systems to current- and next-generation "active" data warehouse implementations
Why do we override the execute method is struts? Plz give me the details?
As part of Struts FrameWork we can decvelop the Action Servlet,ActionForm servlets(here ActionServlet means which class extends the Action class is called ActionServlet and ActionFome means which calss extends the ActionForm calss is called the Action Form servlet)and other servlets classes.
In case of ActionForm class we can develop the validate().this method will return the ActionErrors object.In this method we can write the validation code.If this method return null or ActionErrors with size=0,the webcontainer will call the execute() as part of the Action class.if it returns size > 0 it willnot be call the execute().it will execute the jsp,servlet or html file as value for the input attribute as part of the attribute in struts-config.xml file.
What is the difference between Datawarehousing and BusinessIntelligence?
Data warehousing deals with all aspects of managing the development, implementation and operation of a data warehouse or data mart including meta data management, data acquisition, data cleansing, data transformation, storage management, data distribution, data archiving, operational reporting, analytical reporting, security management, backup/recovery planning, etc. Business intelligence, on the other hand, is a set of software tools that enable an organization to analyze measurable aspects of their business such as sales performance, profitability, operational efficiency, effectiveness of marketing campaigns, market penetration among certain customer groups, cost trends, anomalies and exceptions, etc. Typically, the term “business intelligence” is used to encompass OLAP, data visualization, data mining and query/reporting tools.Think of the data warehouse as the back office and business intelligence as the entire business including the back office. The business needs the back office on which to function, but the back office without a business to support, makes no sense.
What is the difference between OLAP and datawarehosue?
Datawarehouse is the place where the data is stored for analyzing
where as OLAP is the process of analyzing the data, managing aggregations, partitioning information into cubes for indepth visualization.
What is fact less fact table? where you have used it in your project?
Factless table means only the key available in the Fact there is no mesures available.
Why Denormalization is promoted in Universe Designing?
In a relational data model, for normalization purposes, some lookup tables are not merged as a single table. In a dimensional data modeling(star schema), these tables would be merged as a single table called DIMENSION table for performance and slicing data.Due to this merging of tables into one large Dimension table, it comes out of complex intermediate joins. Dimension tables are directly joined to Fact tables.Though, redundancy of data occurs in DIMENSION table, size of DIMENSION table is 15% only when compared to FACT table. So only Denormalization is promoted in Universe Desinging.
What is the difference between ODS and OLTP?
ODS:- It is nothing but a collection of tables created in the Datawarehouse that maintains only current data
where as OLTP maintains the data only for transactions, these are designed for recording daily operations and transactions of a business
What is the difference between datawarehouse and BI?
Simply speaking, BI is the capability of analyzing the data of a datawarehouse in advantage of that business. A BI tool analyzes the data of a datawarehouse and to come into some business decision depending on the result of the analysis.
Is OLAP databases are called decision support system ??? true/false?
TRUE
Explain in detail about type 1, type 2(SCD), type 3 ?
Type-1 Most Recent Value
Type-2 (full History)
i) Version Number
ii) Flag
iii) Date
Type-3 Current and one Perivies value
What is snapshot?
You can disconnect the report from the catalog to which it is attached by saving the report with a snapshot of the data. However, you must reconnect to the catalog if you want to refresh the data.
What is the difference between datawarehouse and BI?
Simply speaking, BI is the capability of analyzing the data of a datawarehouse in advantage of that business. A BI tool analyzes the data of a datawarehouse and to come into some business decision depending on the result of the analysis.
What are non-additive facts in detail?
A fact may be measure, metric or a dollar value. Measure and metric are non additive facts.
Dollar value is additive fact. If we want to find out the amount for a particular place for a particular period of time, we can add the dollar amounts and come up with the total amount.
A non additive fact, for eg measure height(s) for 'citizens by geographical location' , when we rollup 'city' data to 'state' level data we should not add heights of the citizens rather we may want to use it to derive 'count'
What is the Difference between OLTP and OLAP?
Main Differences between OLTP and OLAP are:-
1. User and System Orientation
OLTP: customer-oriented, used for data analysis and querying by clerks, clients and IT professionals.
OLAP: market-oriented, used for data analysis by knowledge workers( managers, executives, analysis).
2. Data Contents
OLTP: manages current data, very detail-oriented.
OLAP: manages large amounts of historical data, provides facilities for summarization and aggregation, stores information at different levels of granularity to support decision making process.
3. Database Design
OLTP: adopts an entity relationship(ER) model and an application-oriented database design.
OLAP: adopts star, snowflake or fact constellation model and a subject-oriented database design.
4. View
OLTP: focuses on the current data within an enterprise or department.
OLAP: spans multiple versions of a database schema due to the evolutionary process of an organization; integrates information from many organizational locations and data stores
What is SCD1 , SCD2 , SCD3?
SCD Stands for Slowly changing dimensions.
SCD1: only maintained updated values.
Ex: a customer address modified we update existing record with new address.
SCD2: maintaining historical information and current information by using
A) Effective Date
B) Versions
C) Flags
or combination of these
SCD3: by adding new columns to target table we maintain historical information and current information.
Why are OLTP database designs not generally a good idea for a Data Warehouse?
Since in OLTP,tables are normalised and hence query response will be slow for end user and OLTP doesnot contain years of data and hence cannot be analysed.
What is BUS Schema?
BUS Schema is composed of a master suite of confirmed dimension and standardized definition if facts.
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