Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

FEBRUARY 8, 2023

ETL developer is a software developer who uses various tools and technologies to design and implement data integration processes across an organization. The role of an ETL developer is to extract data from multiple sources, transform it into a usable format and load it into a data warehouse or any other destination database.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Knowledge Hut

NOVEMBER 17, 2023

Data Architecture and Design: These experts excel in creating effective data structures that meet scalability requirements, ensure optimal data storage, processing, and retrieval, and correspond with business demands. Azure Data Factory stands at the forefront, orchestrating data workflows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques. What Should You Choose Between Big Data and Small Data?

Big Data 52

Big Data Datasets Data Analysis Media 52

Ascend.io

JANUARY 2, 2024

Actions: Establish connections to your data sources like CRM systems or social media platforms. Implement processes to validate and clean incoming data, such as verifying data formats or removing duplicates 3. Objective: Refine the data through specific transformations to make it suitable for analysis.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Data Lake A storage repository where data is stored in its raw format.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

JUNE 20, 2023

From blockchain-based database systems to real-time data processing with in-memory databases, these topics offer a glimpse into the exciting future of database research. This is particularly useful in situations where data integrity is critical, such as in financial transactions or supply chain management.

Database 52

Database Java Education Data Collection 52

Databand.ai

JULY 19, 2023

A Beginner’s Guide [SQ] Niv Sluzki July 19, 2023 ELT is a data processing method that involves extracting data from its source, loading it into a database or data warehouse, and then later transforming it into a format that suits business needs. The extraction process requires careful planning to ensure data integrity.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

AltexSoft

MARCH 2, 2023

Data usability ensures that data is available in a structured format that is compatible with traditional business tools and software. Data integrity is about maintaining the quality of data as it is stored, converted, transmitted, and displayed. Learn more about data integrity in our dedicated article.

Data Governance 52

Data Governance Government Healthcare Programming 52

U-Next

AUGUST 17, 2022

Data Engineer roles and responsibilities have certain important components, such as: Refining the software development process using industry standards. Identifying and fixing data security flaws to shield the company from intrusions. Employing data integration technologies to get data from a single domain.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 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. It is intended to process enormous amounts of data, including tables with hundreds of millions of rows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

NOVEMBER 15, 2021

Companies like Yandex, CloudFare, Uber , eBay, Spotify have preferred Clickhouse owing to its performance, scalability, reliability, and security. With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 31, 2022

Snowflake puts all data on a single high-performance platform by bringing data in from many locations, reducing the complexity and delay imposed by standard ETL processes. Snowflake allows data to be examined and cleaned immediately, assuring data integrity.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

NOVEMBER 10, 2021

Inability to handle unstructured data such as audio, video, text documents, and social media posts. The DW nature isn’t the best fit for complex data processing such as machine learning as warehouses normally store task-specific data, while machine learning and data science tasks thrive on the availability of all collected data.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. You can’t just keep it in SQL databases, unlike structured data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

phData: Data Engineering

JULY 18, 2023

First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse. Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52