Knowledge Hut

APRIL 19, 2023

It can be any system that creates data, including databases, files, APIs, and cloud services. Transformation Engine: Where the ETL pipeline processes the data. This type of ETL pipeline is useful when you need to process data quickly, but you want to ensure that all data is processed in a timely manner.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

ProjectPro

JANUARY 27, 2023

Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange. This indicates the growing use of the ETL process and various ETL tools and techniques across multiple industries.

BI 52

BI ETL Tools Retail Healthcare 52

Towards Data Science

NOVEMBER 4, 2023

Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Indeed, why would we build a data connector from scratch if it already exists and is being managed in the cloud? I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). What is it?

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

JANUARY 30, 2024

Its flexibility allows organizations to leverage data value, regardless of its format or source, and can reside in various storage environments, from on-premises solutions to cloud-based platforms or a hybrid approach, tailored to the organization's specific needs and strategies.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

MARCH 30, 2023

Source: Databricks Delta Lake is an open-source, file-based storage layer that adds reliability and functionality to existing data lakes built on Amazon S3, Google Cloud Storage, Azure Data Lake Storage, Alibaba Cloud, HDFS ( Hadoop distributed file system), and others. Delta Lake integrations.

Scala 64

Scala Data Lake BI Google Cloud 64

Monte Carlo

APRIL 4, 2023

With today’s announcement, Monte Carlo becomes the first data company to bring data observability to the entire orchestration layer, this coming after integrations with Airflow, dbt Core and dbt Cloud were announced in 2022.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

Monte Carlo

APRIL 4, 2023

With today’s announcement, Monte Carlo becomes the first data company to bring data observability to the entire orchestration layer, this coming after integrations with Airflow, dbt Core and dbt Cloud were announced in 2022.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

AltexSoft

AUGUST 4, 2021

Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit. Modern cloud warehouses make it possible to store data in its raw formats similarly to data lakes. Hybrid data marts.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

Monte Carlo

SEPTEMBER 8, 2021

If traditional ETL and ELT solutions like Fivetran and Stitch enable companies to ingest data into their modern data warehouse for transformation and modeling, Reverse ETL does just the opposite: it enables companies to move transformed data from their cloud data warehouse out into operational business tools.

ETL Tools 52

ETL Tools Data Warehouse BI Data Pipeline 52

Silectis

MARCH 9, 2021

The position requires knowledge of cloud services, analytics databases, ETL tools, big data platforms, DevOps, and the fundamentals of the business, all of which make it tough to know where to start. Nowadays established companies aim to deploy across clouds for several reasons.

Data Engineering 52

Data Engineering Data Engineer Engineering ETL Tools 52

AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

OCTOBER 21, 2022

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. A single cluster can span across multiple data centers and cloud facilities.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Cloudera

JUNE 16, 2022

Once Laila started using SSB, she quickly utilized her SQL skills to parse and process complex streams of telemetry metadata from Kafka with contextual information from their manufacturing data lakes in their data center and in the cloud to create a hybrid streaming pipeline. Better yet, it works in any cloud environment.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

AltexSoft

OCTOBER 30, 2021

Such visualizations as graphs and charts are typically prepared by data analysts or business analysts, though not every project has those people employed. Then, a data scientist uses complex business intelligence tools to present business insights to executives. Providing data access tools. Data warehousing.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

phData: Data Engineering

MAY 11, 2023

Practices centered on software engineering principles can create a barrier to entry for teams with skilled data wranglers looking to take their infrastructure to the next level with cloud-native tools like Matillion for the Snowflake Data Cloud. What is Zero-Code Development Life Cycle (ZDLC)?

Coding 52

Coding Software Engineer Software Engineering Government 52

AltexSoft

OCTOBER 8, 2021

Usually, data integration software is divided into on-premise, cloud-based, and open-source types. On-premise data integration tools. As the name suggests, these tools aim at integrating data from different on-premise source systems. Cloud-based data integration tools. Cloud-based tools make up another category.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

JANUARY 26, 2022

The development of new tools and the improvement of old ones has led to the transformation of the traditional data roles, simplifying some job aspects and complicating other ones. Such specialists can use SaaS platforms to continuously extract the underlying data from existing databases and centralize it in cloud data warehouses.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

ProjectPro

NOVEMBER 30, 2021

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

FEBRUARY 18, 2022

ETL is a must-have for data-driven businesses. The transition to cloud-based software services and enhanced ETL pipelines can ease data processing for businesses. ETL pipelines help data scientists to prepare data for analytics and business intelligence.

Project 52

Project AWS Kafka Healthcare 52

AltexSoft

SEPTEMBER 10, 2021

Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications. These systems can be hosted on-premises, in the cloud, and on IoT devices, etc.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

SEPTEMBER 26, 2021

Google Trends shows the large-scale demand and popularity of Big Data Engineer compared with other similar roles, such as IoT Engineer, AI Programmer, and Cloud Computing Engineer. Big Data Engineer identifies the internal and external data sources to gather valid data sets and deals with multiple cloud computing environments.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Modern cloud-based data pipelines are agile and elastic to automatically scale compute and storage resources. Data Pipeline Example Suppose you are running an eCommerce business and want to use data for quick insights or offer personalizations effectively. It not only consumes more memory but also slackens data transfer.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. What are the various types of storage available in Azure?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40