Rockset

OCTOBER 11, 2022

As Rockset is purpose-built for real-time analytics, it has also been designed for field-level mutability , decreasing the CPU required to process inserts, updates and deletes. Logstash is an event processing pipeline that ingests and transforms data before sending it to Elasticsearch.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. This blog will be published in two parts.

Process 85

Process Kafka SQL Machine Learning 85

Snowflake

JUNE 13, 2024

But at Snowflake, we’re committed to making the first step the easiest — with seamless, cost-effective data ingestion to help bring your workloads into the AI Data Cloud with ease. Like any first step, data ingestion is a critical foundational block. Ingestion with Snowflake should feel like a breeze.

Data Ingestion 90

Data Ingestion MySQL PostgreSQL Data Pipeline 90

Snowflake

NOVEMBER 19, 2024

On a day-to-day basis, Snowflake teams identify opportunities and help customers implement recommended best practices that ease the migration process from on-premises to the cloud. They also monitor potential challenges and advise on proven patterns to help ensure a successful data migration.

Cloud 52

Cloud Data Ingestion Data Validation Data Security 52

phData: Data Engineering

SEPTEMBER 19, 2023

Data lakes have emerged as a popular solution, offering the flexibility to store and analyze diverse data types in their raw format. However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Snowflake

MARCH 2, 2023

This solution is both scalable and reliable, as we have been able to effortlessly ingest upwards of 1GB/s throughput.” Rather than streaming data from source into cloud object stores then copying it to Snowflake, data is ingested directly into a Snowflake table to reduce architectural complexity and reduce end-to-end latency.

Kafka 125

Kafka Data Ingestion Data Pipeline Cloud Storage 125

Rockset

MARCH 27, 2023

In part 1 , we covered the technology landscape for real-time analytics on streaming data. In this post, we’ll explore the differences between real-time analytics databases and stream processing frameworks. Differing Paradigms Stream processing systems and real-time analytics (RTA) databases are both exploding in popularity.

Database 52

Database Process Scala SQL 52

Snowflake

OCTOBER 16, 2024

For organizations who are considering moving from a legacy data warehouse to Snowflake, are looking to learn more about how the AI Data Cloud can support legacy Hadoop use cases, or are struggling with a cloud data warehouse that just isn’t scaling anymore, it often helps to see how others have done it.

Digital Media 81

Digital Media Media Data Lake Data Warehouse 81

Rockset

MARCH 1, 2023

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

Data Ingestion 144

Data Ingestion Database Architecture SQL 144

DataKitchen

MAY 10, 2024

Harnessing Data Observability Across Five Key Use Cases The ability to monitor, validate, and ensure data accuracy across its lifecycle is not just a luxury—it’s a necessity. Data Evaluation Before new data sets are introduced into production environments, they must be thoroughly evaluated and cleaned.

Data Ingestion 57

Data Ingestion Datasets Data Coding 57

Data Engineering Weekly

JULY 7, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Hudi seems to be a de facto choice for CDC data lake features. Notion migrated the insert heavy workload from Snowflake to Hudi.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring (#2) Introduction Ensuring the accuracy and timeliness of data ingestion is a cornerstone for maintaining the integrity of data systems. This process is critical as it ensures data quality from the onset.

Data Ingestion 53

Data Ingestion Transportation High Quality Data Data Schemas 53

Cloudyard

JULY 31, 2024

Read Time: 2 Minute, 5 Second In the modern data landscape, the common challenge is efficiently handling and integrating new data from various files into data warehouses. Consider a company that receives daily CSV files containing customer transaction data. Load data into these tables.

Data Ingestion 52

Data Ingestion Data Warehouse Coding Designing 52

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. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear. I'll use Python and Spark because they are the top 2 requested skills in Toronto.

Data Pipeline 130

Data Pipeline Data Ingestion AWS Kafka 130

Striim

SEPTEMBER 11, 2024

With data volumes and sources rapidly increasing, optimizing how you collect, transform, and extract data is more crucial to stay competitive. That’s where real-time data, and stream processing can help. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

DataKitchen

NOVEMBER 5, 2024

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. By systematically moving data through these layers, the Medallion architecture enhances the data structure in a data lakehouse environment.

Architecture 79

Architecture Raw Data Pipeline-centric Data Ingestion 79

Snowflake

APRIL 18, 2024

This blog post explores how Snowflake can help with this challenge. Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. These rules need computing power to analyze data and spot attacks.

Data Lake 82

Data Lake Data Ingestion Bytes Cloud Computing 82

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. This growing demand has found a natural synergy with the rise of the data lake. What is the Difference Between Data Testing and Data Observability?

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Pinterest Engineering

OCTOBER 23, 2024

Yongjun Zhang; Staff Software Engineer | William Tom; Staff Software Engineer | Sandeep Kumar; Software Engineer | Monarch, Pinterest’s Batch Processing Platform, was initially designed to support Pinterest’s ever-growing number of Apache Spark and MapReduce workloads at scale. This minor version upgrade process took approximately one year.

AWS 52

AWS Hadoop Management Algorithm 52

Data Engineering Weekly

APRIL 21, 2024

The blog narrates how Chronon fits into Stripe’s online and offline requirements. link] GoodData: Building a Modern Data Service Layer with Apache Arrow GoodData writes about using Apache Arrow to build an efficient service layer. The result is to adopt data contract solutions with type standardization and auto-generate schemas.

Data Engineer 52

Data Engineer Data Engineering Engineering Medical 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Rockset

JANUARY 30, 2024

Microbatching : An option to microbatch ingestion based on the latency requirements of the use case. In this blog, we delve into each of these features and how they are giving users more cost controls for their search and AI applications. This is not a hands-free operation and also involves the transfer of data across nodes.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Fast, Safe Development and Deployment (#4) Introduction The integrity and functionality of new code, tools, and configurations during the development and deployment stages are crucial. This process is critical as it ensures data quality from the onset.

Data Ingestion 50

Data Ingestion Datasets Coding Data 50

Cloudera

FEBRUARY 15, 2024

Data integration and ingestion: With robust data integration capabilities, a modern data architecture makes real-time data ingestion from various sources—including structured, unstructured, and streaming data, as well as external data feeds—a reality.

Insurance 88

Insurance Banking Data Architecture Data Ingestion 88

Striim

JUNE 6, 2024

Conversely, high latency can hinder your organization’s data integration and streaming efforts. As data-driven decision-making becomes increasingly vital, the importance of minimizing latency has never been clearer. Inefficient data transfer protocols or high data volumes can exacerbate latency during the loading phase.

Data Integration 52

Data Integration Data Ingestion Healthcare Data Pipeline 52

Cloudera

NOVEMBER 1, 2023

This AMP is built on the foundation of one of our previous AMP s, with the additional enhancement of enabling customers to create a knowledge base from data on their own website using Cloudera DataFlow (CDF) and then augment questions to the chatbot from that same knowledge base in Pinecone.

Machine Learning 110

Machine Learning Data Ingestion Database Architecture 110

Snowflake

APRIL 9, 2024

However, that data must be ingested into our Snowflake instance before it can be used to measure engagement or help SDR managers coach their reps — and the existing ingestion process had some pain points when it came to data transformation and API calls. Outcome data goes back into the system to train the model.

BI 77

BI Data Ingestion Data Aggregated Data 77

Lyft Engineering

NOVEMBER 29, 2023

In this particular blog post, we explain how Druid has been used at Lyft and what led us to adopt ClickHouse for our sub-second analytic system. Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Pinterest Engineering

NOVEMBER 7, 2023

Jeff Xiang | Software Engineer, Logging Platform Vahid Hashemian | Software Engineer, Logging Platform Jesus Zuniga | Software Engineer, Logging Platform At Pinterest, data is ingested and transported at petabyte scale every day, bringing inspiration for our users to create a life they love.

Kafka 110

Kafka Java Software Engineering Software Engineer 110

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Contents: What is the role of an Azure Data Engineer? Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

Cloudyard

MAY 7, 2024

Read Time: 1 Minute, 39 Second Many organizations leverage Snowflake stages for temporary data storage. However, with ongoing data ingestion and processing, it’s easy to lose track of stages containing old, potentially unnecessary data. This can lead to wasted storage costs.

Data Ingestion 52

Data Ingestion Data Storage Utilities Coding 52

ProjectPro

JANUARY 25, 2022

Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things. Finally, you'll find a list of PySpark projects to help you gain hands-on experience and land an ideal job in Data Science or Big Data.

Big Data 52

Big Data Data Process Process Kafka 52

Snowflake

JUNE 4, 2024

Supporting open storage architectures The AI Data Cloud is a single platform for processing and collaborating on data in a variety of formats, structures and storage locations, including data stored in open file and table formats. Getting data ingested now only takes a few clicks, and the data is encrypted.

Government 84

Government Data Ingestion Data PostgreSQL 84

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. Did I Ensure That Data Does Not Conflict With Itself?

Raw Data 50

Raw Data Data Ingestion Datasets Data 50

Edureka

AUGUST 23, 2024

These analytic models can work on processed data sets. The accuracy of decisions improves dramatically once you can use live data in real-time. The AWS training will prepare you to become a master of the cloud, storing, processing, and developing applications for the cloud data. How Amazon Kinesis Works?

AWS 52

AWS Kafka Amazon Web Services Medical 52

phData: Data Engineering

MARCH 8, 2023

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 allows organizations to easily connect their disparate data sources without having to manage any infrastructure. Why Use Fivetran?

IT 96

IT Data Warehouse Data Ingestion Data Integration 96