Ascend.io

SEPTEMBER 14, 2023

Data-Centric Libraries: Python has purpose-built libraries like Pandas, NumPy, and Scikit-learn, tailored for data manipulation, analysis, and machine learning, streamlining data engineers’ workflows. PySpark allows Python to interface with Apache Spark, making distributed data tasks more approachable.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 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. 7 Be Intentional About the Batching Model in Your Data Pipelines Different batching models. Test system with A/A test.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Maxime Beauchemin

JANUARY 20, 2017

This discipline also integrates specialization around the operation of so called “big data” distributed systems, along with concepts around the extended Hadoop ecosystem, stream processing, and in computation at scale. This includes tasks like setting up and operating platforms like Hadoop/Hive/HBase, Spark, and the like.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Knowledge Hut

JANUARY 30, 2024

Customer Interaction Data: In customer-centric industries, extracting data from customer interactions (e.g., Apache Sqoop: Efficiently transfers bulk data between Hadoop and structured data stores like relational databases, simplifying the process of importing and exporting data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

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. Data Engineers are engineers responsible for uncovering trends in data sets and building algorithms and data pipelines to make raw data beneficial for the organization.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

NOVEMBER 15, 2023

Looking for a position to test my skills in implementing data-centric solutions for complicated business challenges. Example 6: A well-qualified Cloud Engineer is looking for a position responsible for developing and maintaining automated CI/CD and deploying pipelines to support platform automation.

Finance 98

Finance Business Intelligence Database-centric Certification 98

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. To come to the right decision, we need to divide this big question into several smaller ones — namely: What is Hadoop? To come to the right decision, we need to divide this big question into several smaller ones — namely: What is Hadoop? scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

U-Next

AUGUST 17, 2022

Hadoop Apache Data Engineers utilize the open-source Hadoop platform to store and process enormous volumes of data. Hadoop is a collection of tools that allow data integration rather than a single platform. Data Engineers focused on pipelines require a solid understanding of decentralized technology and computer engineering.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

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. While Spark’s speed is often cited as being “100 times faster than Hadoop,” it’s crucial to understand the specifics of this claim.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

SEPTEMBER 26, 2023

This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads. The development experience is more SQL-centric, making it well-suited for traditional data warehousing tasks. This cohesive experience promotes productivity and accelerates the development of data solutions.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Cloudera

APRIL 22, 2021

Look at details of volumes/buckets/keys/containers/pipelines/datanodes. Given a file, find out what nodes/pipeline is it part of. Seamlessly scale the architecture to thousands of nodes with a single pane of glass management using Cisco Application Centric Infrastructure (ACI).

Pipeline-centric 98

Pipeline-centric Data Lake Hadoop Metadata 98

Monte Carlo

NOVEMBER 14, 2023

Data orchestration tools minimize manual intervention by automating the movement of data within data pipelines. Or are there other data orchestration tools that could be a better fit for your pipeline needs? Each block of code in your pipeline produces data that can be versioned, partitioned, and cataloged for future reference.

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

Cloudera

SEPTEMBER 17, 2020

For modern data engineers using Apache Spark, DE offers an all-inclusive toolset that enables data pipeline orchestration, automation, advanced monitoring, visual troubleshooting, and a comprehensive management toolset for streamlining ETL processes and making complex data actionable across your analytic teams. Managed, Serverless Spark.

Data Pipeline 101

Data Pipeline Data Engineering Data Engineer Engineering 101

Dataquest

JANUARY 25, 2017

This is where data engineers come in — they build pipelines that transform that data into formats that data scientists can use. Roughly, the operations in a data pipeline consist of the following phases: Ingestion — this involves gathering in the needed data. A data scientist is only as good as the data they have access to.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

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. Here, the bank loan business division has essentially become software.

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

Databand.ai

DECEMBER 20, 2022

He specializes in distributed systems and data processing at scale, regularly working on data pipelines and taking complex analyses authored by data scientists/analysts and keeping them running in production. He is also a member of The Apache Software Foundation. You can also watch both episodes with Maxime (episodes #18 and #19).

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52