Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 90

Data Warehouse Cloud Government Metadata 90

Cloudera

SEPTEMBER 24, 2020

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

Data Warehouse 70

Data Warehouse SQL Engineering Metadata 70

Uber Engineering

AUGUST 3, 2018

Data powers Uber’s global marketplace, enabling more reliable and seamless user experiences across our products for riders, … The post Databook: Turning Big Data into Knowledge with Metadata at Uber appeared first on Uber Engineering Blog.

Metadata 110

Metadata Big Data Transportation Data 110

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Modern data warehousing for the cloud. Using Cloudera Altus for your cloud data warehouse.

Data Warehouse 40

Data Warehouse Metadata Cloud Storage Cloud 40

Cloudera

NOVEMBER 15, 2024

A Better Way Forward: Cloudera’s Open Data Lakehouse Cloudera offers a solution to these challenges with its open data lakehouse, which combines the flexibility and scalability of data lake storage with data warehouse functionality to unify and simplify the management of cyber log data.

Metadata 76

Metadata Unstructured Data Data Lake Government 76

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. Starting from the CDW Public Cloud DWX-1.6.1

Metadata 89

Metadata Data Warehouse BI AWS 89

Data Engineering Weekly

JULY 7, 2024

The blog highlights the advantages of GNN over traditional machine learning models, which struggle to discern relationships between various entities, such as users and restaurants, and edges, such as order. The author highlights Paimon’s consistency model by examining the metadata model.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

Cloudera

OCTOBER 10, 2024

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

IT 83

IT Data Lake Metadata Data Warehouse 83

phData: Data Engineering

NOVEMBER 8, 2024

Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms. In this blog, we will discuss: What is the Open Table format (OTF)? First, we create an Iceberg table in Snowflake and then insert some data.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Data Engineering Weekly

OCTOBER 6, 2024

link] Medium: Learnings from optimising 22 of our most expensive Snowflake pipelines A blog about real-world learning is always a delight to read. Though the blog talks about Superset, every team should strive to adopt a similar framework to manage the lifecycle of their dashboards. “text-to-SQL” and “text-to-insight.”

Data Engineering 62

Data Engineering Data Engineer Engineering Data Warehouse 62

Data Science Blog: Data Engineering

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Data Engineering Weekly

AUGUST 25, 2024

[link] FourSquare: Modern Data Platform: An Unbundling of a Traditional Data Warehouse When building their data platform, companies face a critical decision: adopt an all-in-one solution from vendors like Databricks, Snowflake, or AWS or compose a custom platform using tools from different providers.

Data Engineering 70

Data Engineering Data Engineer Engineering Database-centric 70

Data Engineering Podcast

NOVEMBER 20, 2022

Summary The majority of blog posts and presentations about data engineering and analytics assume that the consumers of those efforts are internal business users accessing an environment controlled by the business. Atlan is the metadata hub for your data ecosystem.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Cloudera

NOVEMBER 15, 2024

A Better Way Forward: Cloudera’s Open Data Lakehouse Cloudera offers a solution to these challenges with its open data lakehouse, which combines the flexibility and scalability of data lake storage with data warehouse functionality to unify and simplify the management of cyber log data.

Metadata 52

Metadata Unstructured Data Data Lake Government 52

Airbnb Tech

NOVEMBER 28, 2023

However, for all of our uncertified data, which remained the majority of our offline data, we lacked visibility into its quality and didn’t have clear mechanisms for up-leveling it. How could we scale the hard-fought wins and best practices of Midas across our entire data warehouse?

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. My advice on this point is to learn from others.

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Cloudera

JULY 13, 2023

A range of Iceberg table analysis such as listing table’s data file, selecting table snapshot, partition filtering, and predicate filtering can be delegated through Iceberg Java API instead, obviating the need for each query engine to implement it themself. The data files and metadata files in Iceberg format are immutable.

Java 69

Java Metadata PostgreSQL Data Warehouse 69

phData: Data Engineering

SEPTEMBER 19, 2023

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Workfall

JUNE 12, 2023

So, embrace the power of Change Data Capture, and embark on a captivating journey where the magic of real-time data awaits. In this blog, we will cover: What Is CDC and Its Benefits? CDC also plays a crucial role in data integration and ETL processes. Where Is CDC Used and Who Uses It?

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Lyft Engineering

OCTOBER 3, 2023

In this post we will define data quality at a high-level and explore our motivation to achieve better data quality. We will then introduce our in-house product, Verity, and showcase how it serves as a central platform for ensuring data quality in our Hive Data Warehouse. What and Where is Data Quality?

Big Data 85

Big Data Metadata Data Warehouse Data 85

Snowflake

NOVEMBER 30, 2023

At TCS , we help companies shift their enterprise data warehouse (EDW) platforms to the cloud as well as offering IT services. We’re extremely familiar with just how tricky a cloud migration can be, especially when it involves moving historical business data. Use separate data warehouses for cost-effective data loading.

Data Warehouse 104

Data Warehouse Banking Data Cloud 104

Data Engineering Podcast

MARCH 22, 2021

Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Metadata Hadoop Data Lake 100

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Metadata management .

Cloud 78

Cloud Metadata Google Cloud Data Warehouse 78

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Cloud Storage Metadata Data 98

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Forrester ).

Data Architecture 78

Data Architecture Architecture Data Lake NoSQL 78

Netflix Tech

DECEMBER 3, 2022

The most commonly used one is dataflow project , which helps folks in managing their data pipeline repositories through creation, testing, deployment and few other activities. It lets you create YAML formatted mock data files based on selected tables, columns and a few rows of data from the Netflix data warehouse.

Data Pipeline 144

Data Pipeline Scala Metadata Food 144

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 93

Data Lake Data Warehouse BI SQL 93

Cloudera

NOVEMBER 5, 2020

Many organizations struggle to meet growing and variable data warehouse demands. This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse. CDP is a data platform that is optimized for both business units and central IT. . Cloudera Data Warehouse Security.

Cloud 74

Cloud Data Lake Data Warehouse Metadata 74

Cloudera

JULY 14, 2023

Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration. In this blog, I will describe a few strategies one could undertake for various use cases. This will be discussed in a later blog. Relatively fast as the underlying data files are kept in place.

Metadata 69

Metadata Data Warehouse Big Data Ecosystem Java 69

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 117

Data Pipeline Building Manufacturing Data Warehouse 117

Cloudera

MARCH 17, 2023

I took the free version of ChatGPT on a test drive (in March 2023) and asked some simple questions on data lakehouse and its components. Hopefully this blog will give ChatGPT an opportunity to learn and correct itself while counting towards my 2023 contribution to social good. I thought this was a fairly comprehensive list.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

Cloudera

SEPTEMBER 29, 2022

This team or domain expert will be responsible for the data produced by the team. The data itself is then treated as a product. The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. What is a data mesh contract?

Architecture 73

Architecture Data Architecture Metadata Data Warehouse 73

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Architecture 101

Architecture Metadata Machine Learning Unstructured Data 101

Edureka

AUGUST 14, 2024

It is the open-source software that increased the Paraquet data assignments. This is a scalable metadata system because it handles transaction performance and fills the files with it. Updating and modifying Delta Lake tables The Delta Lake atomic transactions enhance many options for upgrading and updating metadata.

Data Lake 40

Data Lake Metadata SQL Data Pipeline 40

Databand.ai

JULY 19, 2023

Learn more in our detailed guide to data lineage visualization (coming soon) Integration with Multiple Data Sources Data lineage tools are designed to integrate with a wide range of data sources, including databases, data warehouses, and cloud-based data platforms.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52