Interview Questions.

Top 100+ Data Architect Interview Questions And Answers

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Top 100+ Data Architect Interview Questions And Answers

Question 1. Who Is A Data Architect, Please Explain?

Answer :

The man or woman who is into data architect position is someone who can be taken into consideration as a records architecture practitioner.

So in terms of information architecture it consists of the subsequent tiers:

Designing
Creating
Deploying
Managing
All of those sports are performed with the business enterprise's records architecture.

With their help and talent set, the organization can take a optimistic decision of the way the data is saved, how the facts is ate up and the way the records is included into exclusive IT structures. In a feel, this method is carefully aligned with business structure, due to the fact they should be aware of this procedure in order that the security guidelines are also considered.

Question 2. What Are The Fundamental Skills Of A Data Architect?

Answer :

The fundamental abilties of a Data Architect are as follows:

The character need to possess knowledge about records modeling in element.
Physical statistics modeling ideas.
Should be familiar with ETL process.
Should be acquainted with Data warehousing ideas.
Hands-on revel in with statistics warehouse tools and special software.
Should have enjoy in terms of growing records strategies.
Build data guidelines and plans for executions.
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Question 3. What Is A Data Block And What Is A Data File? Please Explain Briefly?

Answer :

A statistics block is not anything but a logical space where the Oracle database data is saved.

A facts report is not anything but a record where all the data is to be had. For each Oracle database, we are able to be having one or more statistics documents associated.

Question 4. What Is Cluster Analysis? What Is The Purpose Of Cluster Analysis?

Answer :

A cluster analysis is defined as a system wherein an item is described without giving any label to it. It makes use of statistical information analysis method and approaches the facts mining process. Using cluster analysis, an iterative method of knowledge discovery is processed in the shape of trails.

The cause of cluster evaluation:

It is scalable
It can deal with distinct set of attributes
High dimensionality
Interpretability
Data Warehousing Tutorial
Question five. What Is Virtual Data Warehousing?

Answer :

A virtual facts warehouse provides a view of completed statistics. Within Virtual statistics warehousing, it doesn’t have any ancient information and it can be considered as a logical records version which has the metadata. A virtual information warehouse is a really perfect facts device where it acts as the perfect analytical decision-making gadget.

It is one of the great approaches of portraying raw records within the form of significant facts for government customers which makes commercial enterprise experience and at the same time it presents hints at the time of choice making.

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Question 6. What Is Snapshot With Reference To Data Warehouse?

Answer :

As the name itself implies, the photograph is not anything however a fixed of complete data visualization when a information extraction is achieved. The exceptional component is that it uses less area and it may be without difficulty used to take backup and also the records can be restored fast from a photo.

Question 7. What Is Xmla?

Answer :

XMLA is not anything but XML for analysis functions.This is taken into consideration as a general for get admission to of facts in OLAP. XMLA surely makes use of discover and execute techniques. So Discover approach clearly is used to fetch the data from the internet and execute method is used for the packages to execute in opposition to all the statistics resources that are available.

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Question 8. What Is The Main Difference Between View And Materialized View?

Answer :

The most important difference between view and materialized view is as follows:

View:

Data illustration is furnished by view in which the information is accessed from its desk.
View has a logical structure which does not occupy space
All the changes are affected in corresponding tables.
Materialized View:

Within materialized view, pre-calculated records is to be had
The materialized view has a physical shape which does occupy space
All the adjustments aren't reflected inside the corresponding tables.
Question nine. What Is Junk Dimension?

Answer :

A junk measurement is not anything however a measurement where a sure kind of facts is saved which isn't appropriate to keep in the schema. The nature of the junk size is usually a Boolean has flag values.

A single size is formed with the aid of a set of small dimensions got collectively. This may be taken into consideration as junk dimension.

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Question 10. What Is Data Warehouse Architecture?

Answer :

The records warehouse structure is a 3-tier architecture.

The following is the 3-tier structure:

Bottom Tier
Middle Tier
Upper Tier
It is nothing however a repository of integrating information that is extracted from exclusive records sources.

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Question 11. What Is An Integrity Constraints? What Are Different Types Of Integrity Constraints?

Answer :

An integrity constraint is not anything but a selected requirement that the facts within the database has to satisfy. It is not anything but a commercial enterprise rule for a selected column in a table. In the records warehouse idea, they're five integrity constraints.

The following are the integrity constraints:

Null
Unique key
Primary key
Foreign key
Check
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Question 12. Why Is That Data Architect Actually Monitor And Enforce Compliance Data Standards? What Is The Need?

Answer :

The number one idea of keeping the requirements high on compliance for data standards is because it will help to lessen the data redundancy and helps the crew to have a satisfactory statistics. As this data is definitely achieved or used for the duration of the corporation.

Data Warehousing Interview Questions
Question thirteen. Explain The Different Data Models That Are Available In Detail?

Answer :

There are 3 exceptional sorts of information fashions which might be available and they are as follows:

Conceptual
Logical
Physical
Conceptual facts model:

As the name itself implies that this information model depicts the high-degree layout of the available physical data.

Logical information version:

Within the logical model, the entity names, entity relationships, attributes, number one keys and overseas keys will show up.

Physical records model:

Based on this records version, the view will supply out greater information and showcases how the version is implemented in the database. All the number one keys, overseas keys, tables names and column names could be displaying up.

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Question 14. Differentiate Between Dimension And Attribute?

Answer :

In quick, dimensions are not anything but which represents qualitative records. For instance information like a plan, product, magnificence are all taken into consideration as dimensions.

The characteristic is not anything however a subset of a measurement. Within a measurement table, we will have attributes. The attributes may be textual or descriptive. For instance, product name and product category are not anything but an characteristic of product dimensions.

Question 15. Differentiate Between Oltp And Olap?

Answer :

OLTP stands for Online Transaction Process System
OLTP is known for maintaining transactional level statistics of the employer and usually, they may be fairly normalized. If it is OLTP direction then it is going to be a celeb schema design.
OLAP stands for Online Analytical system system.
OLAP is thought for numerous evaluation and fulfills reporting purposes. It is de-normalized shape.
If it's far an OLAP route then it's far going to be a snowflake schema design.
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Question sixteen. How To Become A Data Architect?

Answer :

The following are the stipulations for an character to start his career in Data Architect.

A bachelor's degree is critical and preferably in laptop technological know-how background
No predefined certifications are essential, but it is constantly accurate to have few certifications related to the sector because few of the businesses might expect. It is advisable to go through CDMA (Certified )
Data Management Professional)
Should have at the least 3-8 years of IT revel in.
Should be creative, revolutionary and desirable at hassle-fixing.
Has right programming information and statistics modeling ideas
Should be well versed with the equipment like SOA, ETL, ERP, XML etc
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Question 17. The Responsibilities Of A Data Architect And Data Administrator Are The Same?

Answer :

No, under no circumstances. The duties of records architect are absolutely exceptional from that of information administrator.

For instance:

Data architect works on with facts modeling and designs the database layout in a strong manner wherein the customers might be able to extract the facts without difficulty. When it comes to facts directors, they are responsible for having the databases run successfully and correctly.

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Question 18. Is Data Architect And Data Scientist Roles Are Similar?

Answer :

No, information architect and facts scientist roles are two special roles in an agency.

The following are few sports that facts architect is involved :

Data warehousing answers
ETL activities
Data Architecture development sports
Data modelling
The following are few activities that information scientist is concerned in:

Data cleansing and processing
Predictive modelling
Machine studying
Statistical analysis implemented
Data visualization
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Question 19. What Are The Different Types Of Measures Available?

Answer :

The three one-of-a-kind forms of measures are to be had, they're as follows:

Non-additive measures
Semi-additive measures
Additive measures
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Question 20. What Are The Common Mistakes That Encounter During Data Modeling Activity, List Them Out?

Answer :

The common errors that are encountered at some point of facts modeling sports are listed underneath:

First and most important is making an attempt to construct big facts fashions. The hassle with big massive statistics models is that they have got greater design faults. The best case eventualities is to have a records model construct that is under 200 desk restriction.
Misunderstanding of the enterprise trouble, if that is the case then the data model that is built will now not suffice the cause.
Inappropriate manner of surrogate key utilization.
Carrying out unnecessary de-normalization.
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