Cloudera

DECEMBER 4, 2024

introduces features to enhance developer productivity and streamline data pipeline development: Parameter Groups: Simplify flow management and promote reusability by grouping parameters and applying them across multiple flows. empowers data engineers to build and deploy data pipelines faster, accelerating time-to-value for the business.

Data Pipeline 93

Data Pipeline Data Ingestion Data Preparation Architecture 93

Precisely

DECEMBER 18, 2023

By connecting with customers when, where and how they desire, using personalized and data-driven insights, businesses are creating the game-changing experiences that customers demand. Join us as we count down the Top 5 Customer Engagement blog posts of 2023. #5.

Management 64

Management Data Integration IT Data 64

Databand.ai

AUGUST 30, 2023

Data Consistency vs Data Integrity: Similarities and Differences Joseph Arnold August 30, 2023 What Is Data Consistency? Data consistency refers to the state of data in which all copies or instances are the same across all systems and databases. What Is Data Integrity?

Data Integration 52

Data Integration Data Cleanse Data Validation High Quality Data 52

Databand.ai

AUGUST 30, 2023

Data Accuracy vs Data Integrity: Similarities and Differences Eric Jones August 30, 2023 What Is Data Accuracy? Data accuracy refers to the degree to which data is correct, precise, and free from errors. In other words, it measures the closeness of a piece of data to its true value.

Data Integration 52

Data Integration Data Cleanse Data Validation Data Governance 52

Hevo

AUGUST 23, 2024

Choosing the right data integration tool is crucial for managing workflows and ensuring your data pipelines are efficient and reliable. In this blog, we’ll explore what each tool offers, compare Talend vs Airflow, and explore whether an even better option, […]

Data Integration 52

Data Integration Data Pipeline Data Management 52

Pinterest Engineering

NOVEMBER 18, 2024

Liang Mou; Staff Software Engineer, Logging Platform | Elizabeth (Vi) Nguyen; Software Engineer I, Logging Platform | In today’s data-driven world, businesses need to process and analyze data in real-time to make informed decisions. What is Change Data Capture? Why is CDC Important? or its affiliates.

Kafka 50

Kafka MySQL Database Software Engineering 50

Ascend.io

NOVEMBER 14, 2024

By focusing on these attributes, data engineers can build pipelines that not only meet current demands but are also prepared for future challenges. In this blog post, we’ll explore key strategies for future-proofing your data pipelines. We’ll explore scalability, integration, security, and cost management.

Data Pipeline 52

Data Pipeline Amazon Web Services Data Integration Data 52

Data Engineering Podcast

FEBRUARY 26, 2023

TimeXtender takes a holistic approach to data integration that focuses on agility rather than fragmentation. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. When is a data mesh the wrong choice?

Building 147

Building Machine Learning Metadata Data Integration 147

Striim

JUNE 6, 2024

For your organization’s data integration and streaming initiatives to succeed, meeting latency requirements is crucial. Low latency, defined by the rapid transmission of data with minimal delay, is essential for maximizing the effectiveness of your data strategy.

Data Integration 52

Data Integration Data Ingestion Healthcare Data Pipeline 52

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

Data Integration 52

Data Integration Process Data Validation Data Governance 52

Monte Carlo

JUNE 16, 2023

Data integrity and quality may seem similar at first glance, and they are sometimes used interchangeably in everyday life, but they play unique roles in successful data management. You can have data quality, without data integrity.

Data Integration 52

Data Integration Hospitality Banking Healthcare 52

Wayne Yaddow

MARCH 28, 2025

Unleashing GenAIEnsuring Data Quality at Scale (Part1) Transitioning from isolated repository systems to consolidated AI LLM pipelines Photo by Joshua Sortino on Unsplash Introduction This blog is based on insights from articles in Database Trends and Applications, Feb/Mar 2025 ( DBTA Journal ).

Government 52

Government Data Governance Data Data Integration 52

Edureka

APRIL 22, 2025

Data engineering can help with it. It is the force behind seamless data flow, enabling everything from AI-driven automation to real-time analytics. To stay competitive, businesses need to adapt to new trends and find new ways to deal with ongoing problems by taking advantage of new possibilities in data engineering.

Data Engineer 52

Data Engineer Data Engineering Engineering Consulting 52

Databand.ai

JUNE 20, 2023

Niv Sluzki June 20, 2023 What Is Data Integrity? Data integrity refers to the overall accuracy, consistency, and reliability of data stored in a database, data warehouse, or any other information storage system.

Data Integration 52

Data Integration Data Validation Pharmaceutical Data Cleanse 52

Databand.ai

JUNE 22, 2023

Ryan Yackel June 22, 2023 What Is Data Integrity? Data integrity is concerned with the accuracy, consistency, and reliability of data stored in databases or other data storage systems. Entity integrity: Ensures each row in a database table is uniquely identifiable.

Data Integration 52

Data Integration Medical Healthcare Education 52

Striim

MARCH 21, 2025

This blog post describes the advantages of real-time ETL and how it increases the value gained from Snowflake implementations. With instant elasticity, high-performance, and secure data sharing across multiple clouds , Snowflake has become highly in-demand for its cloud-based data warehouse offering.

Data Warehouse 52

Data Warehouse MongoDB MySQL Hadoop 52

Ascend.io

OCTOBER 28, 2024

Data transformation helps make sense of the chaos, acting as the bridge between unprocessed data and actionable intelligence. You might even think of effective data transformation like a powerful magnet that draws the needle from the stack, leaving the hay behind. This is crucial for maintaining data integrity and quality.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Cloudera

MARCH 11, 2021

While Apache NiFi is used successfully by hundreds of our customers to power mission critical and large-scale data flows, the expectations for enterprise data flow solutions are constantly evolving. In this blog post, I want to share the top three requirements for data flows in 2021 that we hear from our customers.

Cloud 119

Cloud Data Data Warehouse Data Integration 119

Hevo

SEPTEMBER 29, 2024

The same, however triggers a sound ETL solution to handle the data correctly. This blog REST API ETL Tools will talk about the various tools that will help you fetch data from Public APIs and […] Today most organizations are of the opinion that public APIs should be tapped into and useful information extracted there from.

ETL Tools 52

ETL Tools Data Integration Data 52

Snowflake

APRIL 16, 2025

Enterprises need to rapidly transform raw data into actionable applications, but this often requires expensive infrastructure, coding, custom data analysis and complex integrations. Whats the coolest thing youre doing with data?

Building 59

Building Raw Data Data Analysis Data Security 59

Data Engineering Weekly

JULY 14, 2024

[link] Discord: How Discord Uses Open-Source Tools for Scalable Data Orchestration & Transformation Discord writes about its migration journey from a homegrown orchestration engine to Dagster. Techniques for turning text data and documents into vector embeddings and structured data.

Data Engineer 98

Data Engineer Data Engineering Engineering Unstructured Data 98

Databand.ai

JUNE 21, 2023

Eric Jones June 21, 2023 What Are Data Integrity Tools? Data integrity tools are software applications or systems designed to ensure the accuracy, consistency, and reliability of data stored in databases, spreadsheets, or other data storage systems. In this article: Why Are Data Integrity Tools Important?

Data Integration 52

Data Integration Data Cleanse Data Validation Telecommunication 52

Ascend.io

DECEMBER 4, 2024

Automation, AI, DataOps, and strategic alignment are no longer optional —they are essential components of a successful data strategy. As we look towards 2025, it’s clear that data teams must evolve to meet the demands of evolving technology and opportunities. Data Quality Management: Ensure data quality as data volumes grow.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

DataKitchen

FEBRUARY 17, 2025

Manually writing tests limits the scope of what gets tested and can introduce biases, making it difficult to get a complete picture of data quality. Organizations that fail to prioritize data quality testing risk compromising their data integrity, affecting their ability to make informed business decisions.

SQL 73

SQL Python Government Data Engineering 73

Workfall

SEPTEMBER 18, 2023

Reading Time: 9 minutes Imagine your data as pieces of a complex puzzle scattered across different platforms and formats. This is where the power of data integration comes into play. Meet Airbyte, the data magician that turns integration complexities into child’s play.

Data Pipeline 93

Data Pipeline Raw Data Data Schemas Healthcare 93

Data Engineering Podcast

MARCH 25, 2023

TimeXtender takes a holistic approach to data integration that focuses on agility rather than fragmentation. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. But don't worry, there is a better way.

MySQL 130

MySQL Python Architecture Machine Learning 130

Ascend.io

DECEMBER 4, 2024

Automation, AI, DataOps, and strategic alignment are no longer optional —they are essential components of a successful data strategy. As we look towards 2025, it’s clear that data teams must evolve to meet the demands of evolving technology and opportunities. Data Quality Management: Ensure data quality as data volumes grow.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Striim

DECEMBER 18, 2024

Elevating Fuel Efficiency with Real-Time Data For airlines, fuel efficiency isn’t just about cutting costsit’s a pivotal factor in reducing environmental impact and maintaining competitive operations. This centralized approach empowers teams with immediate insights across all facets of aviation operations.

Aggregated Data 52

Aggregated Data Machine Learning Data Integration Data 52

Data Engineering Weekly

AUGUST 6, 2024

Integration and Extendability A CDC tool's ability to integrate with existing systems and extend its functionalities is crucial. Considerations include: - APIs and SDKs for custom integrations. Compatibility with data integration and orchestration tools. I’m a data engineer; how can I contribute?

Data Lake 126

Data Lake Data Warehouse Database Data Architecture 126

Cloudera

JUNE 2, 2022

CDF-PC is a cloud native universal data distribution service powered by Apache NiFi on Kubernetes, ??allowing allowing developers to connect to any data source anywhere with any structure, process it, and deliver to any destination. This blog aims to answer two questions: What is a universal data distribution service?

Systems 104

Systems Data Lake Google Cloud Data Collection 104

Netflix Tech

FEBRUARY 14, 2025

This nuanced integration of data and technology empowers us to offer bespoke content recommendations. In this multi-part blog series, we take you behind the scenes of our system that processes billions of impressions daily.

Kafka 66

Kafka Datasets Metadata Utilities 66

Cloudyard

JANUARY 21, 2025

Schema evolution refers to the ability of a system to adapt to changes in the structure of incoming data without breaking existing workflows. In this blog, we’ll explore the significance of schema evolution using real-world examples with CSV, Parquet, and JSON data formats. Technical Implementation: 1.

Data Schemas 59

Data Schemas Data Pipeline Data Warehouse Data Storage 59

Christophe Blefari

JUNE 3, 2023

The camera is using location data to feed context to a generative algorithm. A dynamic prompt — (Paragraphica camera) Fast News ⚡️ Meltano announced their Cloud — Meltano is an open-source data integration project that has been started at Gitlab.

Data Pipeline 130

Data Pipeline Data SQL Algorithm 130

Snowflake

JULY 22, 2024

At first, you may use your modern data platform as a single source of truth to realize operational gains — but you can realize far greater benefits by adding additional use cases. In this blog, we offer guidance for leveraging Snowflake’s capabilities around data and AI to build apps and unlock innovation.

Government 119

Government Data Cloud Hadoop 119

Edureka

APRIL 22, 2025

We’ll explain everything in this blog post in the most straightforward manner possible—no complicated terms, just the features, advantages, and reasons why moving to Lightning might revolutionize your company. Salesforce Lightning is likely familiar to anyone who works with or plans to use Salesforce.

Designing 52

Designing Accessibility Accessible Coding 52

phData: Data Engineering

MARCH 8, 2023

With so many data integration tools available in the market, it can be difficult to determine which one is the best fit for your organization. Fivetran, a cloud-based automated data integration platform, has emerged as a leading choice among businesses looking for an easy and cost-effective way to unify their data from various sources.

IT 96

IT Data Warehouse Data Ingestion Data Integration 96

Cloudera

JULY 11, 2022

The need for data fabric. As Cloudera CMO David Moxey outlined in his blog , we live in a hybrid data world. Data is growing and continues to accelerate its growth. Cloudera data fabric and analyst acclaim. We look forward to speaking with you and helping you make the most of your data.

Data Architecture 107

Data Architecture Architecture Data Government 107