Data Engineering Weekly

APRIL 16, 2023

The blog narrates the difference between deterministic and non-deterministic system design and the challenges of building LLM applications in production. Meta shares its ever-changing landscape of data engineering. Analytical Engineering is the role often quoted for data engineers who do Accessible Analytics.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

MARCH 22, 2024

You maintain the data integrity, security, and performance by monitoring, optimizing, and troubleshooting database operations. Proficiency in MongoDB query language and database design principles. Familiarity with application development frameworks and tools. Developing database architecture strategies.

MongoDB 52

MongoDB Amazon Web Services Computer Science Education 52

Knowledge Hut

NOVEMBER 3, 2023

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. Quickly pull (fetch), filter, and reduce data.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

MARCH 26, 2024

Growing Technology Landscape: With the rapid advancements in technology, there's an increasing demand for professionals who can design and implement complex IT solutions. Role Level: Typically a senior-level position requiring extensive experience in architecture design and implementation across various domains and industries.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. This is part of a series of articles about data quality.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. There are not many sources to pull the metadata.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Knowledge Hut

NOVEMBER 17, 2023

In the post, we will investigate how to become an Azure data engineer, the skills required, the roles and responsibilities of an Azure data engineer, and much more. Who is an Azure Data Engineer? Data Modeling The process of creating a logical and physical data model for a system is known as data modeling.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Databand.ai

JULY 19, 2023

By loading the data before transforming it, ELT takes full advantage of the computational power of these systems. This approach allows for faster data processing and more flexible data management compared to traditional methods. The extraction process requires careful planning to ensure data integrity.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Databand.ai

JULY 5, 2023

They help organizations understand the dependencies between data sources, processes, and systems, enabling better data governance and impact analysis. They provide insights into the health of data integration processes, detect issues in real-time, and enable teams to optimize data flows.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Towards Data Science

NOVEMBER 4, 2023

How to Become a Data Engineer As a data engineer, I am tasked to design efficient data processes almost every day. Introduction to Apache Iceberg Tables Simplified data integrations Managed solutions like Fivetran and Stitch were built to manage third-party API integrations with ease.

Data Engineering 87

Data Engineering Data Engineer Engineering BI 87

ProjectPro

SEPTEMBER 26, 2021

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. It will also assist you in building more effective data pipelines.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

What is a Big Data Pipeline? Data pipelines have evolved to manage big data, just like many other elements of data architecture. Big data pipelines are data pipelines designed to support one or more of the three characteristics of big data (volume, variety, and velocity).

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

OCTOBER 8, 2021

The good news is, businesses can choose the path of data integration to make the most out of the available information. The bad news is, integrating data can become a tedious task, especially when done manually. Data integration in a nutshell. Data integration process. That’s a lot of work.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

NOVEMBER 30, 2021

Transform Data Once the data is validated, we apply transformations to remove duplicates, perform cleansing, standardization, business rule application, perform data integrity checks, data governance, use aggregations, and many more. Stage Data Data that has been transformed is stored in this layer.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

OCTOBER 30, 2021

Data scientists need to have precise domain knowledge to extract the most relevant features for a model to use. Feature engineering is one of the most important and time consuming parts of a data scientist’s job. Data scientists are well versed in algorithms and data-related problems to be able to make a solid choice.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64