ProjectPro

JUNE 23, 2016

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

Booking.com Engineering

DECEMBER 2, 2022

BigQuery saves us substantial time — instead of waiting for hours in Hive/Hadoop, our median query run time is 20 seconds for batch, and 2 seconds for interactive queries[3]. A Unified View for Operational Data We kept most of our operational data in relational databases, like MySQL.

Systems 52

Systems Cloud MySQL Relational Database 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed with SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. What is HDFS?

Data Engineer 52

Data Engineer Data Engineering Engineering NoSQL 52

Knowledge Hut

JANUARY 24, 2024

Supports numerous data sources It connects to and fetches data from a variety of data sources using Tableau and supports a wide range of data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and on-cloud data.

BI 98

BI Business Intelligence Non-relational Database Machine Learning 98

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Cassandra A database built by the Apache Foundation. Hadoop / HDFS Apache’s open-source software framework for processing big data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Knowledge Hut

JANUARY 9, 2024

5 Programming Models Students study data-parallel analytics along with Hadoop MapReduce (YARN), distributed programming for the cloud, graph parallel analytics (with GraphLab 2.0), and iterative data-parallel analytics (with Apache Spark). Using Apache Hadoop, they can write their own MapReduce code and provision instances on Amazon EC2.

Cloud Computing 52

Cloud Computing Cloud Amazon Web Services Cloud Storage 52

AltexSoft

OCTOBER 8, 2021

ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats. They include NoSQL databases (e.g., MongoDB), SQL databases (e.g., MySQL), file stores (e.g.,

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

MAY 12, 2023

It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

FEBRUARY 16, 2023

Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies. Data engineers can extract data from a table in a relational database using SQL queries like the "SELECT" statement with the "FROM" and "WHERE" clauses.

Data Engineer 52

Data Engineer Data Engineering SQL Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing. Database Management : knowing how to work with databases - both relational(like Postgres) and non-relational - is important for efficient storing and retrieval of data.

Big Data 52

Big Data Certification Hadoop Kafka 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JANUARY 19, 2022

Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Depending on the type of database a data engineer is working with, they will use specific software. Below, we mention a few popular databases and the different softwares used for them. and their implementation on the cloud is a must for data engineers.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

AltexSoft

NOVEMBER 23, 2021

It maps metadata and semantically similar data assets from different autonomous databases to a common virtual data model or schema of the abstraction layer. To join data together from non-relational databases and other unstructured sources, TIBCO has the built-in transformation engine doing all the jobs.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

AUGUST 31, 2018

Azure and AWS both provide database services, regardless of whether you need a relational database or a NoSQL offering. Amazon’s RDS (Relational Database Service ) and Microsoft’s equivalent SQL Server database both are highly available and durable and provide automatic replication.

AWS 45

AWS Cloud Amazon Web Services Big Data 45

Knowledge Hut

MARCH 20, 2024

Average Salary: $126,245 Required skills: Familiarity with Linux-based infrastructure Exceptional command of Java, Perl, Python, and Ruby Setting up and maintaining databases like MySQL and Mongo Roles and responsibilities: Simplifies the procedures used in software development and deployment.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

AltexSoft

JUNE 26, 2023

Relational vs non-relational databases As we mentioned above, relational or SQL databases are designed for structured or tabular data. According to the 2023 Stack Overflow survey , the most popular SQL solutions so far are PostgreSQL, MySQL, SQLite, and Microsoft SQL Server.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

AUGUST 29, 2023

These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Common structured data sources include SQL databases like MySQL, Oracle, and Microsoft SQL Server. Data sources can be broadly classified into three categories. Transformation section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

NOVEMBER 2, 2023

For data management Through its Amazon Relational Database service, AWS is able to provide managed database services. In this, there are options for SQL Server, Oracle, MariaDB, MySQL, PostgreSQL, and Amazon Aurora. It also offers NoSQL databases with the help of Amazon DynamoDB.

Amazon Web Services 52

Amazon Web Services AWS IT Transportation 52

ProjectPro

JULY 30, 2021

Map-reduce - Map-reduce enables users to use resizable Hadoop clusters within Amazon infrastructure. Amazon’s counterpart of this is called Amazon EMR ( Elastic Map-Reduce) Hadoop - Hadoop allows clustering of hardware to analyse large sets of data in parallel. What are the platforms that use Cloud Computing?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

DECEMBER 7, 2021

Data sources may include relational databases or data from SaaS (software-as-a-service) tools like Salesforce and HubSpot. You must first create a connection to the MySQL database to use Talend to extract data. In most cases, data is synchronized in real-time at scheduled intervals.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 9, 2018

No impact Database Engine MySQL, Oracle DB, SQL Server, Amazon Aurora, Postgre SQL Redshift NoSQL Primary Usage Feature Conventional Databases Data warehouse Database for dynamically modified data Multi A-Z Replication Additional Service Manual In-built 7. The log files may also be queried from a specific database table.

AWS 40

AWS Amazon Web Services Cloud Computing Database 40

ProjectPro

SEPTEMBER 11, 2021

Please point out the difference between SQL and MySQL. SQL MySQL SQL stands for Structured Query Language. It is a query language that is used to fetch data from a database. MySQL is a relational database management software that is open source and relies on SQL for querying a database.

Business Analyst 52

Business Analyst Database-centric MySQL SQL 52

U-Next

AUGUST 3, 2022

Now that well-known technologies like Hadoop and others have resolved the storage issue, the emphasis is on information processing. They demand good knowledge of non-relational databases, including MongoDB, DynamoDB, Casandra, Redis, and Oracle, as well as MySQL, SQL Server, PostgreSQL, Oracle, and others.

Data Science 52

Data Science Computer Science Retail Entertainment 52