Top 10 best informatica absolutely new questions for freshers

top-10-best-iformatica-questions
#top-10-best-iformatica-questions:

What is data mart?
A data mart can contain one fact table to address one subject. In such a case,when a number of data marts are integrated to create a data warehouse, it is important that the facts in each table mean the same thing. Such facts (i.e., measures or metrics) that have the same meaning in different data marts are called conformed facts.

What are the different types of datasmarts?
– Stand–alone Data Marts : Data marts that do not interact with other data marts are called stand–alone data marts. On the other hand, data marts can be integrated to create a data warehouse.
– Multi–source Data Mart : A data mart for which the input data is obtained from multiple sources is called a multi–source data mart.
– Personal Data Mart : A data mart for use by individuals such as Chief Executive Officer (CEO), Chief Technology Officer (CTO) or Chief Financial Officer (CFO) is called Personal Data Mart.
– Operational Data Store : ODS is a database system that obtains data from different sources, consolidates it and keeps it at a single location. However, it does not have the sophistication of a data mart or a data warehouse for analytical processing. ODS is generally developed as a pre-cursor for ERP systems.

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What is fact table?
A fact table is the central table that contains the measures or facts of a business process.

What is the mapplet?
Mapplet is a set of transformations that you build in the mapplet designer and you can use in multiple mappings.

What is meant by grain?
Granularity of data is a very important factor in the design of fact table. In fact table, we can represent data at different atomic levels, called grains.

What is difference between view and materialized view?
Views contains query whenever execute views it has read from base table. A view which is physically stored in a database. Materialized views allow query performance to be enhanced by precalculating costly operations.

What is surrogate key?
A system generated artificial primary key that is not derived from any data in the database. It is similar to the object identifier in an object oriented system.

What is a folder?
Folder contains repository objects such as sources, targets, mappings, transformation which are helps logically organize our data warehouse.

What is pivot?
The pivot (or rotate) operation rotates the axes of a cube to provide an alternative presentation of the data.

What is the difference between mapping and session?
Maping : It is a set of source and target definitions linked by transformation objects that define the rules for transformation. Session : It is a set of instructions that describe how and when to move data from source to targets.

The in and out of Group By clause in SQL

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#group-by-clause:

GROUP BY Clause – The GROUP BY clause is based on simple partitions. A  partition of a set divides the set into subsets such that the union of the subsets returns the original set, and the intersection of the subsets is empty. Think of it as cutting up a pizza pie—each piece of pepperonion belongs to one and only one slice of pizza.

The GROUP BY clause takes the result of the FROM and WHERE clauses, then puts the rows into groups defined as having the same values for the columns listed in the GROUP BY clause.

  • Each group is reduced to a single row in the result table. This result table is called a grouped table, and all operations are now defined on groups rather than on rows.
  • By convention, the NULLs are treated as one group. The order of the grouping columns in the GROUP BY clause does not matter, but since all or some of the column names have to appear in the SELECT list, you should probably use the same order in both lists for readability.
  • Please note the SELECT column names might be a subset of the GROUP BY clause column names, but never the other way around. Let us construct a sample table called Villes to explain in detail how this works. The table is declared as:
CREATE TABLE Villes
(state_code CHAR(2) NOT NULL, -- usps codes
city_name CHAR(25) NOT NULL,
PRIMARY KEY (city_name, state_code));

We populate it with the names of cities that end in “-ville” in each state. The first problem is to find a count of the number of such cities by state_code. The immediate naïve query might be:

SELECT state_code, city_name, COUNT(*)
FROM Villes
GROUP BY state_code;

The groups for Tennessee would have the rows (‘TN’, ‘Nashville’) and (‘TN’, ‘Knoxville’). The first position in the result is the grouping column, which has to be constant within the group. The third column in the SELECT clause is the COUNT(*) for the group, which is clearly two. The city_name column is a problem.

Since the table is grouped by states, there can be at most 50 groups, one for each state_code. The COUNT(*) is clearly a single value, and it applies to the group as a whole.

But what possible single value could I output for a city_name in each group? Pick a typical city_name and use it? If all the cities have the same name, use that name; otherwise, output a NULL.

The worst possible choice would be to output both rows with the COUNT(*) of 2, since each row would imply that there are two cities named Nashville and two cities named Knoxville in Tennessee.

Each row represents a single group, so anything in it must be a characteristic of the group, not of a single row in the group.

This is why there is a rule that the SELECT list must be made up only of grouping columns with optional aggregate function expressions.