Edureka

APRIL 22, 2025

Snowflake is completely managed, but its main focus is on the data warehouse layer, and users need to integrate with other tools for BI, ML, or ETL. Ideal for: Business-centric workflows involving fabric Snowflake = environments with a lot of developers and data engineers 2.

BI 52

BI Pipeline-centric Data Lake Google Cloud 52

ThoughtSpot

OCTOBER 18, 2024

In the fast-paced world of software development, the efficiency of build processes plays a crucial role in maintaining productivity and code quality. At ThoughtSpot , while Gradle has been effective, the growing complexity of our projects demanded a more sophisticated approach to understanding and optimizing our builds.

Building 52

Building Process Pipeline-centric Database-centric 52

Monte Carlo

JANUARY 21, 2025

Who Attends Expect to meet a diverse crowd: top-level executives, seasoned data scientists, technology vendors, and rising innovators. Key Themes Data-Driven Decision-Making : Learn how to build a data-centric culture that drives better outcomes. Build trust across domains : Set and uphold data SLAs.

Data Analytics 52

Data Analytics Pipeline-centric Food Data Lake 52

Maxime Beauchemin

JANUARY 20, 2017

They’re highly analytical, and are interested in data visualization. Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Confluent

SEPTEMBER 25, 2019

Of course, this is not to imply that companies will become only software (there are still plenty of people in even the most software-centric companies), just that the full scope of the business is captured in an integrated software defined process. Event streams as the central nervous system.

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is the role of a Data Engineer? They are required to have deep knowledge of distributed systems and computer science.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

AltexSoft

JULY 18, 2023

With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Big data processing.

Big Data 52

Big Data Data Process Process Hadoop 52

Dataquest

JANUARY 25, 2017

A data scientist is only as good as the data they have access to. Most companies store their data in variety of formats across databases and text files. This is where data engineers come in — they build pipelines that transform that data into formats that data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

U-Next

AUGUST 17, 2022

Data must be comprehensive and cohesive, and Data Engineers are best at this task with their set of skills. Skills Required To Be A Data Engineer. SQL – A database may be used to build data warehousing, combine it with other technologies, and analyze the data for commercial reasons with the help of strong SQL abilities.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Ascend.io

JUNE 8, 2023

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

NOVEMBER 2, 2023

For those aspiring to build a career within the Azure ecosystem, navigating the choices between Azure Data Engineers and Azure DevOps Engineers can be quite challenging. Azure Data Engineers and Azure DevOps Engineers are two critical components of the Azure ecosystem for different but interconnected reasons.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

FEBRUARY 27, 2023

A data engineer is a key member of an enterprise data analytics team and is responsible for handling, leading, optimizing, evaluating, and monitoring the acquisition, storage, and distribution of data across the enterprise. Data Engineers indulge in the whole data process, from data management to analysis.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Edureka

JULY 3, 2024

ADF connects to various data sources, including on-premises systems, cloud services, and SaaS applications. It then gathers and relocates information to a centralized hub in the cloud using the Copy Activity within data pipelines. Transform and Enhance the Data: Once centralized, data undergoes transformation and enrichment.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Ripple Engineering

JANUARY 29, 2024

  A lack of a centralized system makes building a single source of high-quality data difficult. The key aspect of any business-centric team in delivering products and features is to make critical decisions on ensuring low latency, high throughput, cost-effective storage, and highly efficient infrastructure.

Database-centric 52

Database-centric Pipeline-centric NoSQL High Quality Data 52

Snowflake

JUNE 28, 2023

Snowpark is our secure deployment and processing of non-SQL code, consisting of two layers: Familiar Client Side Libraries – Snowpark brings deeply integrated, DataFrame-style programming and OSS compatible APIs to the languages data practitioners like to use. Previously, tasks could be executed as quickly as 1-minute.

Python 52

Python Accessible Accessibility Pipeline-centric 52

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. Open question: how to seed data in a staging environment? Test system with A/A test. Be adaptable.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Knowledge Hut

JULY 3, 2023

Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. This process consists of feeding data from various sources and building it to be available for analysis, storage, or next processing.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

Data Engineering Weekly

JANUARY 8, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Pipelines for data in motion can quickly turn into DAG hell.

Data Engineering 40

Data Engineering Data Engineer Engineering Pipeline-centric 40

Monte Carlo

NOVEMBER 14, 2023

This is the world that data orchestration tools aim to create. Data orchestration tools minimize manual intervention by automating the movement of data within data pipelines. According to one Redditor on r/dataengineering, “Seems like 99/100 data engineering jobs mention Airflow.”

Pipeline-centric 40

Pipeline-centric Google Cloud Python Data Workflow 40

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. The combination of these technologies has become collectively known as the Modern Data Stack.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Edureka

JULY 4, 2024

Databricks runs on an optimized Spark version and gives you the option to select GPU-enabled clusters, making it more suitable for complex data processing. The platform’s massive parallel processing (MPP) architecture empowers you with high-performance querying of even massive datasets. But it doesn’t stop there.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

Knowledge Hut

JUNE 26, 2023

Top Azure Skills to Master Microsoft Azure is a leading cloud platform that offers a wide range of services to help businesses build scalable & robust cloud applications. Application Management Application management expertise is crucial in an Azure-centric ecosystem.

Cloud Computing 52

Cloud Computing Certification Cloud Pipeline-centric 52

Databand.ai

DECEMBER 20, 2022

Read on for the top 25 data analytics and science connections on LinkedIn so you can easily find the information you’re looking for and fill your homepage with meaningful content. Sarah has a growing newsletter read by 4k+ people covering the topics of data, tech, and product.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52

Databand.ai

DECEMBER 29, 2022

Chad writes on data management, contracts, and products on his Substack blog and serves as an advisor and investor to several startups. He recently joined Databand’s MAD Data Podcast to talk about how his team is building one of the most advanced experimentation and machine learning platforms in the world from the ground up.

BI 52

BI Consulting Data Science Data Governance 52

Confluent

MAY 9, 2019

Event-first thinking enables us to build a new atomic unit: the event. This model is completely free form, we can build anything provided that we apply mechanical sympathy with the underlying system behavior. Building the KPay payment system. Pillar 1 – Business function: Payment processing pipeline.

Kafka 94

Kafka Pipeline-centric Architecture Database-centric 94

Precisely

JANUARY 6, 2025

Organizations leveraging real-time data can make faster, data-driven decisions, optimize processes, and accelerate time-to-market. Your ability to deliver seamless, personalized, and timely experiences is key to success in our modern customer-centric landscape.

Data Architecture 59

Data Architecture Architecture Pipeline-centric Banking 59