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Interview Questions and Answers

Real-time data warehousing involves loading data into the data warehouse in near real-time, allowing for up-to-date reporting and analysis. This requires specialized tools and techniques.

OLTP (Online Transaction Processing) is for transactional data processing with a focus on quick transactions and current data. OLAP (Online Analytical Processing) is for analytical data processing with a focus on historical data and complex queries for business intelligence.

Data governance is the process of establishing and enforcing policies and procedures to manage the quality, security, and accessibility of data within the data warehouse.

Challenges include: Data quality issues, scalability, performance tuning, security concerns, and managing complex data integration.

Metadata is data about data. It provides information about the data warehouse structure, data sources, ETL processes, and data quality. Its essential for understanding and managing the data warehouse.

Data security measures include: Access control, encryption, data masking, auditing, and compliance with relevant regulations.

A fact table contains numerical data (facts) that can be aggregated, as well as foreign keys referencing dimension tables. It represents the events or measurements of interest.

A dimension table contains descriptive attributes that provide context to the facts in the fact table. Examples include time, location, product, and customer.

Common tools include: Amazon Redshift, Google BigQuery, Snowflake, Microsoft Azure Synapse Analytics, Oracle Autonomous Data Warehouse, and IBM Db2 Warehouse.

Data modeling is the process of designing the structure of the data warehouse, including defining tables, columns, relationships, and constraints. It ensures data consistency and efficient querying.

SCDs are dimensions whose attributes change over time. There are different types of SCDs (Type 0, Type 1, Type 2, Type 3, Type 4, Type 6) to handle these changes in different ways, balancing historical accuracy with storage requirements.

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in the data. Its crucial for ensuring data quality and reliable analysis.

Benefits include improved decision-making, enhanced business intelligence, increased efficiency, and a competitive advantage.

A star schema is a data warehouse schema with a central fact table surrounded by dimension tables. Its called a star schema because the diagram resembles a star.

A snowflake schema is a variation of the star schema where dimension tables are further normalized into multiple related tables. This can reduce data redundancy but increase query complexity.

Data warehousing is the process of collecting and managing data from various sources to provide meaningful business insights. Its a central repository of integrated data used for reporting and analysis.

Key characteristics include: Subject-oriented, Integrated, Time-variant, and Non-volatile.

A database is designed for transactional processing (OLTP), while a data warehouse is designed for analytical processing (OLAP). Databases focus on current data and quick transactions, while data warehouses focus on historical data and complex queries.

There are three main types: Enterprise Data Warehouse (EDW), Data Mart, and Operational Data Store (ODS). EDWs are centralized repositories, Data Marts are subject-specific, and ODSs are used for real-time operational reporting.

ETL stands for Extract, Transform, and Load. Its the process of extracting data from various sources, transforming it into a consistent format, and loading it into the data warehouse.

A data warehouse is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources.

Types of Data Warehouse:

- Enterprise Data Warehouse (EDW).

- Operational Data Store.

- Data Mart.

- Offline Operational Database.

- Offline Data Warehouse.

- Real time Data Warehouse.

- Integrated Data Wa

Data warehouse has four main components: a central database, ETL (extract, transform, load) tools, metadata, and access tools.

Fact tables and dimension tables hold the columns that store the data for the model: Fact tables contain measures, which are columns that have aggregations built into their definitions.

Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis.

- A surrogate key is an artificial or synthetic key that is used as a substitute for a natural key. It is a

In the top-down approach, the data warehouse is designed first and then data mart are built on top of data warehouse.

One dimension is selected for the slice operation.

No. OLTP database tables are normalized and will be adding extra time for queries to return results.

Star schema is the type of multidimensional model which is used for data warehouse.

- In a star schema, only a single join creates the relationship between the fact table and any dimension tables. Design is simple and has high data redundancy.
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ETL process encompasses data extraction, transformation, and loading. ETL systems take large volumes of raw data from multiple sources, convert it for analysis, and loads that data into your warehouse.

Denormalized

Databases store transactional data effectively, making it accessible to end users and other systems. Data warehouses aggregate data from databases and other sources to create a unified repository that can serve as the basis for advanced reporting and ana

This methodology focuses on a bottom-up approach, emphasizing the value of the data warehouse to the users as quickly as possible.

Top Data Warehouse Software:

- Amazon Redshift.

- IBM Db2.

- Snowflake.

- BigQuery.

- Vertica.

Defining Business Requirements.

- Setting up Physical Environments.

- Introducing Data Modeling.

- Choosing Extract, Transfer, Load (ETL) solution.

- Online Analytic Processing (OLAP) Cube.

- Creating the Front End.

Explain with examples that sync with the job description. or Answer appropriately.

Yes we can, but is not advised because Fact tables tend to have several keys (FK), and each join scenario will require the use of different keys.

Dimensional Data Modeling includes of one or more dimension tables and fact tables. Good examples of dimensions are location, product, time, promotion, organization etc.

Metadata in a data warehouse defines the warehouse objects and acts like a directory. This directory helps locate the contents of a data warehouse.

Entity Relationship Model (ER Modeling) is a graphical approach to database design.

Active Data Warehousing is the technical ability to capture transactions when they change, and integrate them into the warehouse.

Real-time Data Warehousing describes a system that reflects the state of the warehouse in real time.

Conformed dimensions make it possible to get facts and measures to be categorized and described in the same way across multiple facts and/or data marts, ensuring consistent reporting across the enterprise.

One fact table.

Cubes are data processing units composed of fact tables and dimensions from the data warehouse.

Time dimensions are usually loaded by a program that loops through all possible dates that appear in the data. Time dimension are used to represent the data over a certain period of time.

Model–view–controller(MVC) is a software design pattern used for developing user interfaces that separate the related program logic into three interconnected elements. Each of these components is built to handle specific development aspects of an applicat

Explain specific instances with respect to the job JD.

NA

(1) Choose the Right Technology when picking up a programming language, Database, Communication Channel.

(2) The ability to run multiple servers and databases as a distributed application over multiple time zones.

(3)Database backup, correcti

Object-oriented programming is a programming paradigm based on the concept of \"objects\", which can contain data, in the form of fields, and code, in the form of procedures. A feature of objects is that objects' own procedures can access and often modify

Explain specific instances with respect to the job JD.

The most common software sizing methodology has been counting the lines of code written in the application source. Another approach is to do Functional Size Measurement, to express the functionality size as a number by performing Function point analysis.

The major parts to project estimation are effort estimation, cost estimation, resource estimate. In estimation, there are many methods used as best practices in project management such as-Analogous estimation, Parametric estimation, Delphi process, 3 Poin

software configuration management (SCM) is the task of tracking and controlling changes in the software code, part of the larger cross-disciplinary field of configuration management. Whereas change management deals with identification, impact analysis, d

Basecamp, Teamwork Projects, ProofHub, Zoho Projects, Nifty, Trello, JIRA, Asana, Podio, etc.

A feasibility study is a study that takes into account all of the related factors of a project — including economic, technological, legal, and scheduling considerations — to assess the probability of completing the project.

Functional requirements are the specifications explicitly requested by the end-user as essential facilities the system should provide. Non-functional requirements are the quality constraints that the system must satisfy according to the project contract,

Validation is the process of checking whether the specification captures the user's needs, while verification is the process of checking that the software meets the specification.

Different Types Of Software Testing - Unit Testing, Integration Testing, System Testing, Sanity Testing, Smoke Testing, Interface Testing, Regression Testing, Beta/Acceptance Testing.

Quality control can be defined as a \"part of quality management concentrating on maintaining quality requirements.\" While quality assurance relates to how a process is carried out or how a product is produced, quality control is more the quality managem