Tweag

APRIL 26, 2023

Moreover, these steps can be combined in different ways, perhaps omitting some or changing the order of others, producing different data processing pipelines tailored to a particular task at hand.

Data Process 98

Data Process Process Programming Data 98

Netflix Tech

NOVEMBER 14, 2023

Understanding the nature of the late-arriving data and processing requirements will help decide which pattern is most appropriate for a use case. Stateful Data Processing : This pattern is useful when the output depends on a sequence of events across one or more input streams.

Data Process 94

Data Process Process Metadata Finance 94

LinkedIn Engineering

JANUARY 19, 2024

Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. With our new data processing framework, we were able to observe a multitude of benefits, including 99.9%

Recruitment 88

Recruitment Data Process Process Kafka 88

databricks

MARCH 4, 2024

StreamNative, a leading Apache Pulsar-based real-time data platform solutions provider, and Databricks, the Data Intelligence Platform, are thrilled to announce the enhanced Pulsar-Spark.

Data Process 126

Data Process Process Data 126

databricks

JUNE 15, 2023

We are excited to announce the official launch of the Google Pub/Sub connector for the Databricks Lakehouse Platform. This new connector adds to.

Google Cloud 119

Google Cloud Data Process Process Cloud 119

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities. The following figure shows a snapshot of VDK UI.

Data Process 73

Data Process Process Raw Data Data 73

Towards Data Science

FEBRUARY 12, 2024

Let’s learn what… Continue reading on Towards Data Science » In this first article, we’re exploring Apache Beam, from a simple pipeline to a more complicated one, using GCP Dataflow.

Data Pipeline 91

Data Pipeline Data Process Process Data Science 91

KDnuggets

AUGUST 21, 2023

A comprehensive comparison between OLAP and OLTP systems, exploring their features, data models, performance needs, and use cases in data engineering.

Systems 99

Systems Data Process Process Data 99

Analytics Vidhya

FEBRUARY 28, 2023

A collaborative and interactive workspace allows users to perform big data processing and machine learning tasks easily. Introduction Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform that is built on top of the Microsoft Azure cloud.

Big Data 310

Big Data Machine Learning Cloud Data Process 310

Data Engineering Podcast

NOVEMBER 27, 2022

Summary The data ecosystem has been growing rapidly, with new communities joining and bringing their preferred programming languages to the mix. This has led to inefficiencies in how data is stored, accessed, and shared across process and system boundaries.

Data Process 100

Data Process Process Metadata Business Intelligence 100

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Use DuckDB 4.4.

Data Pipeline 219

Data Pipeline Python Building Data 219

Analytics Vidhya

FEBRUARY 7, 2023

Introduction Data engineering is the field of study that deals with the design, construction, deployment, and maintenance of data processing systems. The goal of this domain is to collect, store, and process data efficiently and efficiently so that it can be used to support business decisions and power data-driven applications.

Data Engineering 240

Data Engineering Data Engineer Engineering Data 240

Analytics Vidhya

FEBRUARY 13, 2023

Introduction Every data scientist demands an efficient and reliable tool to process this big unstoppable data. Today we discuss one such tool called Delta Lake, which data enthusiasts use to make their data processing pipelines more efficient and reliable.

Data Process 235

Data Process Process Data Data Warehouse 235

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Big Data is a large and complex dataset generated by various sources and grows exponentially. It is so extensive and diverse that traditional data processing methods cannot handle it. The volume, velocity, and variety of Big Data can make it difficult to process and analyze.

Big Data Tools 234

Big Data Tools Big Data Datasets Data 234

Analytics Vidhya

FEBRUARY 2, 2023

Introduction Big data processing is crucial today. Big data analytics and learning help corporations foresee client demands, provide useful recommendations, and more. Hadoop, the Open-Source Software Framework for scalable and scattered computation of massive data sets, makes it easy.

Hadoop 230

Hadoop Big Data Data Analytics Data Process 230

Analytics Vidhya

APRIL 28, 2023

It is a famous Scala-coded data processing tool that offers low latency, extensive throughput, and a unified platform to handle the data in real-time. Introduction Apache Kafka is an open-source publish-subscribe messaging application initially developed by LinkedIn in early 2011.

Kafka 201

Kafka Scala Coding Data Process 201

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Data pipelines play a critical role in the processing and management of data in modern organizations. A well-designed data pipeline can help organizations extract valuable insights from their data, automate tedious manual processes, and ensure the accuracy of data processing.

Data Pipeline 197

Data Pipeline Data Designing Data Process 197

Snowflake

JUNE 5, 2024

With Snowpark’s existing DataFrame API , users have access to a robust framework for lazily evaluated, relational operations on data, closely resembling Spark’s conventions. pandas is the go-to data processing library for millions worldwide, including countless Snowflake users. Why introduce a distributed pandas API?

Python 113

Python Programming Language Government SQL 113

KDnuggets

JULY 13, 2022

Learn various techniques to reduce data processing time by using multiprocessing, joblib, and tqdm concurrent.

Process 159

Process Python Data Process Data 159

KDnuggets

JANUARY 18, 2022

TLDR; process it with a new Python Data Processing Engine in the Cloud.

Process 158

Process Python Cloud Data Process 158

KDnuggets

JANUARY 20, 2023

Is ChatGPT useful for Python programmers, specifically those of us who use Python for data processing, data cleaning, and building machine learning models? Let's give it a try and find out.

Python 160

Python Programming Machine Learning Data Process 160

Seattle Data Guy

APRIL 25, 2024

As data increased in volume, velocity, and variety, so, in turn, did the need for tools that could help process and manage those larger data sets coming at us at ever faster speeds.

Big Data 147

Big Data Data Process Process Management 147

Waitingforcode

APRIL 18, 2024

Streaming jobs are supposed to run continuously but it applies to the data processing logic. After all, sometimes you may need to release a new job package with upgraded dependencies or improved business logic. What happens then?

Data Process 130

Data Process Process IT Data 130

Start Data Engineering

SEPTEMBER 4, 2024

Key parts of data systems: 2.1. Data flow design 2.3. Data processing design 2.5. Data storage design 2.7. Introduction If you are trying to break into (or land a new) data engineering job, you will inevitably encounter a slew of data engineering tools. Introduction 2. Requirements 2.2. Conclusion 1.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Storage 130

Start Data Engineering

OCTOBER 14, 2024

Using nested data types effectively 3.1. Using nested data types in data processing 3.3.1. STRUCT enables more straightforward data schema and data access 3.3.2. Nested data types can be sorted 3.3.3. Use STRUCT for one-to-one & hierarchical relationships 3.2.

SQL 130

SQL Data Schemas Data Coding 130

KDnuggets

JANUARY 5, 2023

Data merge is a common data processing activity. Learn how Pandas provide various ways to merge our data.

Data Process 137

Data Process Process Data Data Science 137

Start Data Engineering

OCTOBER 17, 2024

Handy functions for common data processing scenarios 1.1. STRUCT data types are sorted based on their keys from left to right 1.4. Introduction Setup SQL tips 1. Need to filter on WINDOW function without CTE/Subquery use QUALIFY 1.2. Need the first/last row in a partition, use DISTINCT ON 1.3.

SQL 130

SQL Data Engineering Data Engineer Engineering 130

Data Engineering Weekly

MAY 16, 2023

Architectural Patterns for Data Quality Now we understand the trade-off between speed & correctness and the difference between data testing and observability. Let’s talk about the data processing types. Two-Phase WAP The Two-Phase WAP, as the name suggests, follows two copy processes.

Engineering 112

Engineering Kafka Data Pipeline Data Warehouse 112

Confluent

FEBRUARY 6, 2024

Streamline data processing and unlock analytics to boost productivity and time to market while lowering infrastructure costs. Confluent enables real-time, reliable, scalable, and secure communication between IoT devices, applications, and backend systems.

Building 119

Building Data Data Process Systems 119

Waitingforcode

DECEMBER 19, 2023

Even though nowadays data processing frameworks and data stores have smart query planners, they don't take our responsibility to correctly design the job logic.

Designing 130

Designing Data Process Process Data 130

The Pragmatic Engineer

MARCH 19, 2024

A 1959 survey had found that in any data processing installation, the programming cost US$800,000 on average and that translating programs to run on new hardware would cost $600,000. From Wikipedia : “In the late 1950s, computer users and manufacturers were becoming concerned about the rising cost of programming.

Software Engineer 276

Software Engineer Software Engineering Programming Language Media 276

Waitingforcode

FEBRUARY 16, 2023

I like writing code and each time there is a data processing job to write with some business logic I'm very happy. However, with time I've learned to appreciate the Open Source contributions enhancing my daily work. Mack library, the topic of this blog post, is one of those projects discovered recently.

Coding 130

Coding Data Process Project Process 130

Waitingforcode

FEBRUARY 3, 2023

However, it's not the single Python-based framework for distributed data processing and people talk more and more often about the alternatives like Dask or Ray. PySpark has been getting interesting improvements making it more Python and user-friendly in each release.

Python 130

Python Data Process Process IT 130

Simon Späti

MARCH 8, 2023

Pandas has established itself as the standard tool for in-memory data processing in Python, and it offers an extensive range of data manipulation capabilities. As such, it is unsurprising that data engineers or those just starting with data have come across it at some point in their work.

IT 130

IT Python Datasets Data Engineering 130

Snowflake

JUNE 20, 2024

In the age of AI, enterprises are increasingly looking to extract value from their data at scale but often find it difficult to establish a scalable data engineering foundation that can process the large amounts of data required to build or improve models.

Data Engineering 96

Data Engineering Data Engineer Scala Engineering 96

Netflix Tech

NOVEMBER 14, 2023

In this context, managing the data, especially when it arrives late, can present a substantial challenge! In this three-part blog post series, we introduce you to Psyberg , our incremental data processing framework designed to tackle such challenges! Let’s dive in! To solve these problems, we came up with Psyberg!

Data Engineering 109

Data Engineering Data Engineer Engineering Metadata 109

Team Data Science

DECEMBER 17, 2020

It’s not a must for data scientist to have skill in data engineering before they can analyze data processed by data engineer or before they can move uniformly with other group (involving data engineer) for the progress of the company. Data scientists should acquire some basic SQL functionality.

Data Engineering 130

Data Engineering Data Engineer Engineering Cloud Computing 130