Data Engineering Podcast

OCTOBER 30, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. RudderStack helps you build a customer data platform on your warehouse or data lake.

Engineering 100

Engineering MongoDB Scala MySQL 100

Christophe Blefari

OCTOBER 14, 2023

He also demo a event-based DAG parsing that instantaneously display DAGs in the UI. That's why we should probably move to event-based DAG parsing — In the presentation Bas explains the 4 steps in the DAG parser and what configuration you can change to have better performance.

Python 130

Python Datasets Data Banking 130

Towards Data Science

FEBRUARY 16, 2024

As we are pulling data with discrepancies together from different operational systems, the data ingestion process can be more time-consuming than originally thought! Your program might get confused too when records come in with different names even though it means the same thing.

Food 62

Food Data Ingestion Python Data Science 62

Data Engineering Podcast

NOVEMBER 6, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. Data teams are increasingly under pressure to deliver. Data teams are increasingly under pressure to deliver.

MongoDB 130

MongoDB Scala MySQL Machine Learning 130

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Striim

JULY 11, 2024

Real-Time Data Ingestion Striim seamlessly ingests data from various sources and streams it directly into Snowflake in real time. This continuous data flow guarantees that the most up-to-date, accurate information is always available for immediate analysis. Here’s how.

Data Ingestion 52

Data Ingestion Datasets PostgreSQL Data Integration 52

Ascend.io

DECEMBER 21, 2022

21, 2022 – Ascend.io , The Data Automation Cloud, today announced they have partnered with Snowflake , the Data Cloud company, to launch Free Ingest , a new feature that will reduce an enterprise’s data ingest cost and deliver data products up to 7x faster by ingesting data from all sources into the Snowflake Data Cloud quickly and easily.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 52

Cloudera

MAY 3, 2024

The workflow—from data ingestion and model training to model deployment—is meticulously defined within a YAML configuration file. Like AMPs, Spaces are ML demo applications that are self-contained and instantly ready to deliver value upon deployment.

Data Security 70

Data Security Machine Learning Data Ingestion Professional Services 70

Data Engineering Podcast

NOVEMBER 13, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. RudderStack helps you build a customer data platform on your warehouse or data lake.

MongoDB 100

MongoDB Google Cloud Scala MySQL 100

Data Engineering Podcast

JUNE 5, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. Data teams are increasingly under pressure to deliver. Data teams are increasingly under pressure to deliver.

Data Security 100

Data Security Metadata MongoDB Scala 100

Cloudera

OCTOBER 15, 2020

Provide a collection Name under Destination (in this example, we named it ‘solr-nifi-demo’). nifi-solr-demo. nifi-solr-demo. solr-nifi-demo-collection. In this post, we demonstrated how Cloudera Data Platform components can collaborate with each other, while still being resource isolated and managed separately.

AWS 117

AWS Data Cloud Cloud Storage 117

Cloudera

MAY 3, 2024

The workflow—from data ingestion and model training to model deployment—is meticulously defined within a YAML configuration file. Like AMPs, Spaces are ML demo applications that are self-contained and instantly ready to deliver value upon deployment.

Project 52

Project Machine Learning Data Ingestion Professional Services 52

Snowflake

APRIL 24, 2023

Data management becomes increasingly manual, creating elongated data pipelines, delayed analytics, and greater potential for error. Snowflake is helping transform the asset servicing workflow with its modernizing technology and data management capabilities, streamlining data ingestion and data sharing.

Management 52

Management Portfolio Data Ingestion Data Warehouse 52

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive. In addition, join us for industry 4.0- challenges.

Manufacturing 108

Manufacturing Machine Learning Data Ingestion Electronics 108

Databand.ai

JUNE 28, 2023

Data observability works with your data pipeline by providing insights into how your data flows and is processed from start to end. Here is a more detailed explanation of how data observability works within the data pipeline: Data ingestion : Observability begins from the point where data is ingested into the pipeline.

Data Pipeline 98

Data Pipeline Data Engineer Data Engineering Engineering 98

Monte Carlo

JUNE 14, 2022

Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Apache Spark, Trino, Flink, Presto, and Hive to safely work with the same tables, at the same time. Snowflake is going to be your unified platform for developing data applications from code to monetization. That story?

Cloud 52

Cloud Data Ingestion Python Government 52

Towards Data Science

JULY 8, 2024

I have used Colab for this demo, as it is much easier (and faster) to configure the environment. ML Pipeline operations begins with data ingestion and validation, followed by transformation. The transformed data is trained and deployed. . Have a look at this article to gain better understanding of this article.

Data Preparation 46

Data Preparation Datasets Metadata Data Ingestion 46

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. More Data Collection Resources. Conclusion.

Manufacturing 109

Manufacturing Data Warehouse Kafka Retail 109

The Modern Data Company

MAY 8, 2023

Data Operating System: Orchestrating a Unified Data Ecosystem A data operating system is an advanced data management platform that unifies data storage, integration, processing, and analytics. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Operating System: Orchestrating a Unified Data Ecosystem A data operating system is an advanced data management platform that unifies data storage, integration, processing, and analytics. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Operating System: Orchestrating a Unified Data Ecosystem A data operating system is an advanced data management platform that unifies data storage, integration, processing, and analytics. It provides a flexible, scalable, and secure data infrastructure that can adapt to evolving business needs.

Data Management 52

Data Management Management Data Lake Data Governance 52

Rockset

APRIL 18, 2023

To highlight these new capabilities, we built a search demo using OpenAI to create embeddings for Amazon product descriptions and Rockset to generate relevant search results. In the demo, you’ll see how Rockset delivers search results in 15 milliseconds over thousands of documents.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Cloudera

JANUARY 11, 2021

Over the last few weeks, I delivered four live NiFi demo sessions, showing how to use NiFi connectors and processors to connect to various systems, with 1000 attendees in different geographic regions. Interactive demo sessions and live Q&A are what we all need these days when working remotely from home is now a norm.

Kafka 62

Kafka Java Data Cleanse Datasets 62

Confluent

MAY 22, 2019

We’ll also provide demo code so you can try it out for yourself. Since MQTT is designed for low-power and coin-cell-operated devices, it cannot handle the ingestion of massive datasets. On the other hand, Apache Kafka may deal with high-velocity data ingestion but not M2M. Demo of Scylla and Confluent integration.

Kafka 98

Kafka Google Cloud NoSQL Entertainment 98

Cloudera

MARCH 27, 2019

Cloudera Flow Management (CFM) is a no-code data ingestion and management solution powered by Apache NiFi. With a slick user interface, 300+ processors and the NiFi Registry, CFM delivers highly scalable data management and DevOps capabilities to the enterprise. NiFi can handle all types of data across any type of data source.

Management 72

Management Data Ingestion Machine Learning Java 72

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.

Machine Learning 107

Machine Learning Python Kafka Java 107

Rockset

DECEMBER 20, 2018

In this blog, I will show how Rockset can serve a live dashboard, which surfaces analytics on real-time Twitter data ingested into Rockset from a Kinesis stream. We obtain data points for the number of incoming tweets every 2 seconds and plot them in a chart. This can also be achieved through the AWS Console or the AWS CLI.

AWS 52

AWS Kafka Data Ingestion Data 52

Ascend.io

OCTOBER 28, 2024

Tools like Python’s requests library or ETL/ELT tools can facilitate data enrichment by automating the retrieval and merging of external data. Read More: Discover how to build a data pipeline in 6 steps Data Integration Data integration involves combining data from different sources into a single, unified view.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Striim

JULY 10, 2024

UPS Capital integrated Striim’s real-time data streaming with Google BigQuery’s analytics to enhance delivery security through immediate data ingestion and real-time risk assessments. Book a demo with us today to see for yourself the difference Striim can make for your team. That’s where Striim came into play.

Management 52

Management Transportation Machine Learning High Quality Data 52

Striim

OCTOBER 11, 2024

This interconnected approach enables teams to create, manage, and automate data pipelines with ease and minimal intervention. In contrast, traditional data pipelines often require significant manual effort to integrate various external tools for data ingestion , transfer, and analysis.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Cloudera

APRIL 9, 2021

Second, CML seamlessly integrates with the rest of the Cloudera Data Platform to provide end-to-end ML workflows. CML can leverage experiences in the earlier stages, such as data ingestion and data engineering, to fully automate data collection, cleansing and transformation before the prediction (ML) stage begins. .

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

Monte Carlo

MAY 26, 2023

Data freshness best practices Once you have talked with your key data consumers and determined your data freshness goals or SLAs, there are a few best practices you can leverage to provide the best service or data product possible. Fill out the form below to schedule a demo!

Data Pipeline 98

Data Pipeline Data Data Warehouse Machine Learning 98

Rockset

MARCH 1, 2023

The default virtual instance will be dedicated to streaming ingestion in this example. In this example, I used ingest transformations to cast a date as a timestamp, parse a field and extract nested fields. Ingest transformations The default virtual instance is responsible for streaming data ingestion and ingest transformations.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Rockset

JUNE 21, 2022

Rockset, in contrast, is a real-time analytics platform that was built to serve sub-second queries on real-time data. Rockset efficiently organizes data in a Converged Index ™, which is optimized for real-time data ingestion and low-latency analytical queries. We invite you to start using the Snowflake connector today!

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Cloudera

DECEMBER 28, 2017

With this in mind, Nordea implemented a modern data architecture based on Cloudera that allowed them to improve data quality, cut data ingest times by 87%, shorten DevOps cycle times, and simplify data management processes.

Banking 40

Banking Data Ingestion Big Data Machine Learning 40

Ascend.io

FEBRUARY 12, 2023

That means data engineers consider functionality (usability, accessibility, relevance) and format (dashboards, reports, datasets) of the required data products before they start building. They gather requirements, demo early versions of data products, and iterate on them over time — just like a conventional product squad would.

Business Analyst 52

Business Analyst Data Lake Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

That means data engineers consider functionality (usability, accessibility, relevance) and format (dashboards, reports, datasets) of the required data products before they start building. They gather requirements, demo early versions of data products, and iterate on them over time — just like a conventional product squad would.

Business Analyst 52

Business Analyst Data Lake Data Pipeline Data 52