ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It can be set up as a security policy on all SQL Databases in an Azure subscription. One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

DECEMBER 29, 2023

The highlight feature of this platform is its potential to integrate semi-structured and structured data without using any third-party tools. Apache Hive It is a Hadoop-based data management and storage tool that allows data analytics through an SQL-like framework.

Data Engineering 40

Data Engineering Data Engineer Engineering BI 40

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. It offers a fault-tolerant storage engine that prioritizes data security.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc. Structured data usually consists of only text.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 45

Big Data NoSQL Data Lake Hadoop 45

AltexSoft

NOVEMBER 10, 2021

The data in this case is checked against the pre-defined schema (internal database format) when being uploaded, which is known as the schema-on-write approach. Purpose-built, data warehouses allow for making complex queries on structured data via SQL (Structured Query Language) and getting results fast for business intelligence.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

JANUARY 24, 2023

Furthermore, BigQuery supports machine learning and artificial intelligence, allowing users to use machine learning models to analyze their data. BigQuery Storage BigQuery leverages a columnar storage format to efficiently store and query large amounts of data. The equality operators equal (=), not equal (!=

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

JANUARY 31, 2022

Snowflake provides data warehousing, processing, and analytical solutions that are significantly quicker, simpler to use, and more adaptable than traditional systems. Snowflake is not based on existing database systems or big data software platforms like Hadoop. Let us now understand the Snowflake data storage layer in detail.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

DECEMBER 13, 2023

Micro Focus has rapidly amassed a robust portfolio of Big Data products in just a short amount of time. The Vertica Analytics Platform provides the fastest query processing on SQL Analytics, and Hadoop is built to manage a huge volume of structured data. This tool can process up to 80 terabytes of data.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52