ProjectPro

FEBRUARY 8, 2023

This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

JUNE 6, 2025

If your company relies heavily on spreadsheets for data. What would you suggest using - multidimensional OLAP or relational OLAP? Relational OLAP stores data in a relational database, whereas multidimensional OLAP stores data in a cube that is compatible with standard spreadsheet tools.

Data Warehouse 40

Data Warehouse Data Mining Recruitment Database 40

Striim

SEPTEMBER 11, 2024

It typically includes large data repositories designed to handle varying types of data efficiently. Data Warehouses: These are optimized for storing structured data, often organized in relational databases.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Data Ingestion 52

Booking.com Engineering

DECEMBER 2, 2022

BigQuery also offers native support for nested and repeated data schema[4][5]. We take advantage of this feature in our ad bidding systems, maintaining consistent data views from our Account Specialists’ spreadsheets, to our Data Scientists’ notebooks, to our bidding system’s in-memory data.

Systems 52

Systems Cloud MySQL Relational Database 52

AltexSoft

OCTOBER 3, 2022

They allow for representing various types of data and content (data schema, taxonomies, vocabularies, and metadata) and making them understandable for computing systems. So, in terms of a “graph of data”, a dataset is arranged as a network of nodes, edges, and labels rather than tables of rows and columns.

Relational Database 52

Relational Database Banking Pharmaceutical Media 52

Ascend.io

MAY 24, 2023

Let’s take a look at some of the datasets that we receive from hospitals. Biome Analytics receives two types of datasets from hospitals: financial and clinical datasets. The clinical dataset consists of all characteristics, treatments, and outcomes of cardiac disease patients. billion financial records and 8.3

Healthcare 52

Healthcare Data Pipeline Hospitality MySQL 52

Cloud Academy

JANUARY 27, 2022

For example, it’s good to be familiar with the different data types in the field, including: variables varchar int char prime numbers int numbers Also, named pairs and their storage in SQL structures are important concepts. These fundamentals will give you a solid foundation in data and datasets.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

NOVEMBER 22, 2021

What's the difference between an RDD, a DataFrame, and a DataSet? RDDs contain all datasets and dataframes. If a similar arrangement of data needs to be calculated again, RDDs can be efficiently reserved. It's useful when you need to do low-level transformations, operations, and control on a dataset. count())) df2.show(truncate=False)

Hadoop 52

Hadoop Metadata Java Python 52

Edureka

MAY 27, 2025

In the field of data engineering, DynamicFrame boosts Glue’s capability to manage complex and diverse datasets. AWS Data Engineer Interview Questions for Experienced 17. RDS is appropriate for transactional databases, while Redshift is tailored for performing analytical queries on extensive datasets.

AWS 40

AWS Data Engineering Data Engineer Engineering 40

Knowledge Hut

DECEMBER 28, 2023

Toad for SQL Server Toad for SQL Server is a database management tool specifically developed by Quest Software to help database administrators and developers manage all versions of Microsoft SQL Server databases. Key Features: Ability to navigate and manage specific database objects like tables and views.

SQL 52

SQL MySQL PostgreSQL Database 52