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.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Data Science 52

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

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Rockset

MAY 3, 2023

lower latency than Elasticsearch for streaming data ingestion. In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Pinterest Engineering

SEPTEMBER 12, 2023

transformers) became standardized, ML engineers started to show a growing appetite to iterate on datasets. While such dataset iterations can yield significant gains, we observed that only a handful of such experiments were conducted and productionized in the last six months. As model architecture building blocks (e.g.

Data Process 105

Data Process Process Datasets Software Engineering 105

Striim

APRIL 18, 2025

Siloed storage : Critical business data is often locked away in disconnected databases, preventing a unified view. Incomplete records : Missing values or partial datasets lead to inaccurate AI predictions and poor business decisions. Delayed data ingestion : Batch processing delays insights, making real-time decision-making impossible.

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Data Pipeline 52

Cloudera

DECEMBER 14, 2021

So to improve the speed of data analysis, the IRS worked with the combined technology integrating Cloudera Data Platform (CDP) and NVIDIA’s RAPIDS Accelerator for Apache Spark 3.0. The Roads and Transport Authority (RTA) operating in Dubai wanted to apply big data capabilities to transportation and enhance travel efficiency.

Transportation 111

Transportation Telecommunication Banking Data Lake 111

Cloudera

OCTOBER 11, 2021

Modak’s Nabu is a born in the cloud, cloud-neutral integrated data engineering platform designed to accelerate the journey of enterprises to the cloud. The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata.

Data Engineering 95

Data Engineering Data Engineer Cloud Engineering 95

Cloudera

JANUARY 20, 2021

The missing chapter is not about point solutions or the maturity journey of use cases, the missing chapter is about the data, it’s always been about the data, and most importantly the journey data weaves from edge to artificial intelligence insight. . Conclusion.

Manufacturing 110

Manufacturing Data Warehouse Kafka Retail 110

Cloudera

AUGUST 17, 2022

Only data platform with built-in capability to ingest data from on-prem to the cloud. Readily Accessible Data Ingestion and Analytics. Sophisticated data practitioners and business analysts want access to new datasets that can help optimize their work and transform whole business functions.

Cloud Computing 116

Cloud Computing Cloud Storage Data Science Machine Learning 116

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 109

Kafka Data Ingestion Architecture Datasets 109

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. Security teams can also reduce their costs by loading certain datasets in batches instead of continuously.

Data Lake 105

Data Lake Data Ingestion Bytes Cloud Computing 105

Cloudera

NOVEMBER 17, 2020

Once the prototype has been completely deployed, you will have an application that is able to make predictions to classify transactions as fraudulent or not: The data for this is the widely used credit card fraud dataset. Data analysis – create a plan to build the model.

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Data Engineering Weekly

SEPTEMBER 18, 2024

Data testing checks for rule-based validations, while observability ensures overall pipeline health, tracking aspects like latency, freshness, and lineage. How to Evaluate a Data Observability Tool When selecting a data observability tool, assessing both functionality and how well it integrates into your existing data stack is important.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines.

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

Confluent

JULY 3, 2019

From a data perspective, the World Cup represents an interesting source of information. The idea in this blog post is to mix information coming from two distinct channels: the RSS feeds of sport-related newspapers and Twitter feeds of the FIFA Women’s World Cup. Ingesting Twitter data.

Data Analysis 21

Data Analysis Kafka Datasets Java 21

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. ® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). Joining with other datasets.

Kafka 21

Kafka SQL BI Hadoop 21

Cloudera

FEBRUARY 16, 2021

In the previous blog post , we looked at some of the application development concepts for the Cloudera Operational Database (COD). In this blog post, we’ll see how you can use other CDP services with COD. Integrated across the Enterprise Data Lifecycle . Conclusion.

Database 83

Database Machine Learning Kafka Data Lake 83

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” As a result, a single consolidated and centralized source of truth does not exist that can be leveraged to derive data lineage truth. push or pull.

Building 92

Building Metadata Transportation Data Ingestion 92

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

Cloudera

SEPTEMBER 9, 2022

With this in mind, it’s clear that no “one size fits all” architecture will work here; we need a diverse set of data services, fit for each workload and purpose, backed by optimized compute engines and tools. . Data changes in numerous ways: the shape and form of the data changes; the volume, variety, and velocity changes.

Architecture 102

Architecture Metadata Machine Learning Unstructured Data 102

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 56

Data Ingestion Data Datasets Coding 56

Cloudera

AUGUST 8, 2024

And through this partnership, we can offer clients cost-effective AI models and well-governed datasets as this industry charges into the future.” Through this partnership, our customers will benefit from more democratized data reducing risk to all downstream projects while significantly cutting their variable IT spend.”

Pharmaceutical 72

Pharmaceutical Unstructured Data Government Data Ingestion 72

LinkedIn Engineering

DECEMBER 20, 2023

This blog post delves into the AutoML framework for LinkedIn’s content abuse detection platform and its role in improving and fortifying content moderation systems at LinkedIn. Most of these steps are automated using the AutoML framework, saving data scientists’ time and reducing the risk of errors.

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

FreshBI

SEPTEMBER 11, 2023

. ” In the continuously evolving field of data-driven insights, maintaining competitiveness relies not only on in-depth analysis but also on the rapid and precise development of reports. Power BI, Microsoft's cutting-edge business analytics solution, empowers users to visualize data and seamlessly distribute insights.

BI 59

BI Consulting Datasets Data Ingestion 59

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 52

Data Ingestion Transportation Data High Quality Data 52

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. Faster data ingestion: streaming ingestion pipelines. These data products can be web applications, dashboards, alerting systems, or even data science notebooks. . Conclusion. Not in the manufacturing space?

Kafka 88

Kafka Manufacturing Data Lake SQL 88

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

Towards Data Science

JANUARY 26, 2023

Another good practice, especially when working with large files, is to choose a format that supports partial file reads — that is, a format that does not require ingesting the entire file in order to process any part of it. Check out this informative blog for more details on how S5cmd works and its significant performance advantages.

Cloud Storage 98

Cloud Storage Big Data Cloud AWS 98

Netflix Tech

OCTOBER 19, 2020

In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. An additional implication of a lenient sampling policy is the need for scalable stream processing and storage infrastructure fleets to handle increased data volume. —?which is difficult when troubleshooting distributed systems.

Building 96

Building Transportation Java Metadata 96

Data Engineering Weekly

NOVEMBER 20, 2022

Google AI: The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation Google published Data Cards , a dataset documentation framework aimed at increasing transparency across dataset lifecycles. link] The short YouTube video gives a nice overview of the Data Cards.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Data Engineering Weekly

OCTOBER 30, 2022

I found the blog helpful in understanding the generative model’s historical development and the path forward. link] Sponsored- [New eBook] The Ultimate Data Observability Platform Evaluation Guide Considering investing in a data quality solution? The author explains how to dump the history of blockchains into S3.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Confluent

MAY 22, 2019

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. A version of this blog post was originally published on the Scylla blog. Try it yourself.

Kafka 98

Kafka Google Cloud NoSQL Entertainment 98