Snowflake

OCTOBER 3, 2023

We are excited to announce the availability of data pipelines replication, which is now in public preview. In the event of an outage, this powerful new capability lets you easily replicate and failover your entire data ingestion and transformations pipelines in Snowflake with minimal downtime.

Data Pipeline 83

Data Pipeline Management Data Ingestion Data 83

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Raw Data 49

Raw Data Data Ingestion Datasets Data 49

Ascend.io

AUGUST 15, 2023

While terms like “Fivetran ETL” or “Fivetran data pipeline” are echoing in the corridors of data professionals, the truth is, Fivetran is primarily an expert on data ingestion — just the first step in a much broader and nuanced data management process.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Precisely

SEPTEMBER 11, 2023

At Precisely, we recognize the value and potential of AI to help our customers work faster and smarter, and make more powerful, confident decisions grounded in trusted data – supporting our overall mission of unlocking data integrity for organizations of all kinds.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Striim

NOVEMBER 13, 2023

Introduction In the fast-evolving world of data integration, Striim’s collaboration with Snowflake stands as a beacon of innovation and efficiency. Handling Peak Loads : During times of peak data load, it might be beneficial to temporarily adjust the batch policy to handle the increased load more efficiently.

Data Ingestion 59

Data Ingestion Utilities Data Integration Data 59

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. In fact, while only 3.5% That’s where our friends at Ascend.io

Food 100

Food MongoDB Scala MySQL 100

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Knowledge Hut

APRIL 23, 2024

Big Data Training online courses will help you build a robust skill-set working with the most powerful big data tools and technologies. Big Data vs Small Data: Velocity Big Data is often characterized by high data velocity, requiring real-time or near real-time data ingestion and processing.

Big Data 52

Big Data Datasets Data Analysis Media 52

DataKitchen

OCTOBER 20, 2023

Example 2: The Data Engineering Team Has Many Small, Valuable Files Where They Need Individual Source File Tracking In a typical data processing workflow, tracking individual files as they progress through various stages—from file delivery to data ingestion—is crucial.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

Ascend.io

MARCH 1, 2023

Ascend does not compete with those solutions – instead, it provides the missing “last yard” to act on the data directly in your data pipelines.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

Ascend.io

FEBRUARY 20, 2023

Ascend does not compete with those solutions – instead, it provides the missing “last yard” to act on the data directly in your data pipelines.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

Ascend.io

FEBRUARY 20, 2023

Ascend does not compete with those solutions – instead, it provides the missing “last yard” to act on the data directly in your data pipelines.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Experience with Azure services for big data processing and analytics.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

FreshBI

SEPTEMBER 11, 2023

It can fetch the data, apply it to the template, and create a new report. Key Principles to Understand Automated Data Ingestion Consider the scenario where you regularly receive data updates in the form of Excel files or CSVs. Example: Develop a Power Automate flow connecting to a stock market API.

BI 59

BI Consulting Datasets Data Ingestion 59

Knowledge Hut

APRIL 23, 2024

The Era of Big Data In the era of big data, some of the most serious problems facing us are maintaining data quality and setting up contemporary infrastructure for data ingestion from various sources. Some of the technological changes have positively impacted data integrity and service delivery quality.

Big Data 52

Big Data Amazon Web Services Media Cloud Computing 52

Ascend.io

JANUARY 2, 2024

The sources of data can be incredibly diverse, ranging from data warehouses, relational databases, and web analytics to CRM platforms, social media tools, and IoT device sensors. Regardless of the source, data ingestion, which usually occurs in batches or as streams, is the critical first step in any data pipeline.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. The metadata layer also allows for the implementation of features like ACID transactions, caching, indexing, zero-copy cloning, and data versioning.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. The metadata layer also allows for the implementation of features like ACID transactions, caching, indexing, zero-copy cloning, and data versioning.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

DareData

JULY 5, 2023

Typically, it is advisable to retain the data in its original, unaltered format when transferring it from any source to the data lake layer. The Data Warehouse(s) facilitates data ingestion and enables easy access for end-users.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

MARCH 20, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

phData: Data Engineering

SEPTEMBER 19, 2023

Data modeling methodologies are systematic approaches used to design and define the structure and relationships of data within a system. They provide a framework for organizing and representing data elements, attributes, and relationships.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

MARCH 15, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Cloudera

JULY 18, 2018

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

Machine Learning 50

Machine Learning Healthcare Medical Electronics 50

Striim

JULY 10, 2023

Additionally, Striim is a robust real-time data integration platform, which complements Databricks Unity Catalog by facilitating continuous data ingestion and synchronization.

Python 40

Python Database Programming Language Coding 40

Edureka

FEBRUARY 7, 2023

It teaches you how to design and implement data storage solutions, design and implement data processing solutions, design and implement data security and compliance solutions, design and implement data integration solutions, and design and implement data analytics solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Any option can pair well with Apache Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Silectis

JANUARY 3, 2021

Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling. Data Integration Combining data from various, disparate sources into one unified view. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

JULY 10, 2023

Data can go missing for nearly endless reasons, but here are a few of the most common challenges around data completeness: Inadequate data collection processes Data collection and data ingestion can cause data completion issues when collection procedures aren’t standardized, requirements aren’t clearly defined, and fields are incomplete or missing.

Data Collection 40

Data Collection Data Governance Government Data 40

ProjectPro

DECEMBER 7, 2021

However, you can also pull data from centralized data sources like data warehouses to transform data further and build ETL pipelines for training and evaluating AI agents. Processing: It is a data pipeline component that decides the data flow implementation. ADF does not store any data on its own.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

MAY 9, 2019

Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data. It is meant for you to assess if you have thought through processes such as continuous data ingestion, enterprise data integration and data governance.

Manufacturing 53

Manufacturing Data Ingestion Architecture Data Governance 53

Cloudera

AUGUST 31, 2021

Due to the high storage cost in the legacy EDW solution, 100% source data capture proved cost-prohibitive – this led to continuing and costly change cycles to load incremental source updates as business requirements changed. Value Achieved.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Maxime Beauchemin

JANUARY 20, 2017

It’s definitely in the interest of the data engineer to build [on] infrastructure that scales with the company, and to be resource conscious at all times. Data Integration Data integration, the practice behind integrating businesses and systems through the exchange of data, is as important and as challenging as its ever been.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130