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

Data Engineering Weekly

MARCH 10, 2024

Pradheep Arjunan - Shared insights on AZ's journey from on-prem to the cloud data warehouses. Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

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

Cloudera

JANUARY 19, 2022

Cloudera Data Platform (CDP) scored among the top 10 vendors on all four Analytical Use Cases — Data Warehouse, Logical Data Warehouse, Data Lake and Operational Intelligence in the Critical Capabilities for Cloud Database Management Systems for Analytics Use Cases.

Database 87

Database Cloud Data Warehouse Data Lake 87

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

NOVEMBER 12, 2020

Your sunk costs are minimal and if a workload or project you are supporting becomes irrelevant, you can quickly spin down your cloud data warehouses and not be “stuck” with unused infrastructure. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs.

Cloud 102

Cloud Data Warehouse Banking Data 102

Maxime Beauchemin

JANUARY 20, 2017

The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Secure and permissioned – data is protected from unauthorized users.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

phData: Data Engineering

OCTOBER 12, 2022

In this blog post, we’ll dive into six of the most powerful dbt Cloud features and many others that you probably don’t know about. Even if there is a failure, or if your data is stale, dbt Cloud provides a link to see the details of the tests and the sources that might be stale. Our team of data experts are happy to assist.

Cloud 52

Cloud Metadata SQL Data Warehouse 52

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Unstructured Data 80

Unstructured Data Data Warehouse Pharmaceutical MySQL 80

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

Monte Carlo

MARCH 3, 2021

We designed our product without having to store or access individual records, PII, or any other sensitive information. Instead, we only extract query logs, metadata, and aggregated statistics about data usage to ensure that your most critical data assets are as trustworthy and reliable as possible. What’s next?

Metadata 52

Metadata Data Lake Business Intelligence Certification 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

NOVEMBER 23, 2020

Upgrading components of Cloudera Data Warehouse (CDW) is as easy as one decision and a few clicks. While the Database (DB) Catalog and Virtual Warehouses (VWs) need to be compatible, the CDW upgrade framework understands the interoperability constraints between them. . contains new API for faster metadata.

Metadata 65

Metadata Data Warehouse Database Accessible 65

Hepta Analytics

FEBRUARY 14, 2022

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Workfall

AUGUST 14, 2023

Two powerful tools that have emerged to simplify the management of data pipelines are DBT (Data Build Tool) and Airflow. These tools, when combined, form a dynamic duo that streamlines and scales data engineering workflows. So, let’s dive into the world of DBT and Airflow and discover how they revolutionize data pipelines.

Data Pipeline 62

Data Pipeline Raw Data Data Database 62

Monte Carlo

SEPTEMBER 12, 2022

But with the rise of tools such as Segment, Fivetran, Meltano, and Airbyte, it’s become relatively easy for teams to bring all of their data from external sources into a centralized place like a data warehouse. Overall, data literacy is on the rise—and new specializations are starting to emerge. Maxime says.

BI 52

BI Data Governance ETL Tools Data Warehouse 52

Data Engineering Weekly

NOVEMBER 6, 2022

A data contract is a continuous and collaborative system because the business context and requirements won’t be static. I plan to write a series of blogs on Schemata and Data Contract in the coming weeks. Martin kindly stepped in for me to give the update for my promised blog posts.

Data Engineering 40

Data Engineering Data Engineer Engineering Machine Learning 40

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Databand.ai

JUNE 28, 2023

This might include processes like data extraction from different sources, data cleansing, data transformation (like aggregation), and loading the data into a database or a data warehouse. Having a bigger and more specialized data team can help, but it can hurt if those team members don’t coordinate.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

FEBRUARY 16, 2022

Within the CML data service, model lineage is managed and tracked at a project level by the SDX. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets. Figure 03: lineage.yaml.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

ProjectPro

JANUARY 24, 2023

If you are preparing for your ETL developer or data engineer interview , you must possess a solid fundamental knowledge of AWS Glue, as you’re likely to get asked questions that test your ability to handle complex big data ETL tasks. Furthermore, AWS Glue DataBrew allows you to visually clean and normalize data without any code.

AWS 52

AWS Data Lake ETL Tools Scala 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. Industry Transformation: Telkomsel — Ingesting 25TB of data daily to provide advanced customer analytics in real-time . SECURITY AND GOVERNANCE LEADERSHIP.

Food 66

Food Healthcare Government Medical 66

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success. How do I get to the next level in the data-driven journey fast enough? appeared first on Cloudera Blog.

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 89

Data Lake Data Warehouse Cloud Unstructured Data 89

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. save the built model container, along with metadata like who built or deployed it. appeared first on Cloudera Blog.

Data Science 41

Data Science Machine Learning Metadata Big Data 41

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 88

Data Warehouse Cloud Government Metadata 88

Cloudera

SEPTEMBER 28, 2021

Cloudera Data platform ( CDP ) provides a Shared Data Experience ( SDX ) for centralized data access control and audit in the Enterprise Data Cloud. The Ranger Authorization Service (RAZ) is a new service added to help provide fine-grained access control (FGAC) for cloud storage.

Accessible 61

Accessible Accessibility Cloud Cloud Storage 61

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

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.

Metadata 69

Metadata Java PostgreSQL Data Warehouse 69

Cloudera

DECEMBER 15, 2022

With CDP, customers can deploy storage, compute, and access, all with the freedom offered by the cloud, avoiding vendor lock-in and taking advantage of best-of-breed solutions. 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.

Cloud 76

Cloud Metadata Google Cloud Data Warehouse 76

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. A simple example from a recent article in StateTech makes this case.

Data Architecture 76

Data Architecture Architecture Data Lake NoSQL 76

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

dbt Developer Hub

JANUARY 8, 2024

Each node is assigned a unique_id (like model.my_project.my_model ) and the manifest stores all the metadata about that model in a dictionary associated to that id. This includes the data warehouse location that gets returned when you write {{ ref('my_model') }} in SQL. That’s exactly what defer does!

Coding 59

Coding Metadata Cloud Healthcare 59

Databand.ai

AUGUST 30, 2023

Data Cataloging Data cataloging is the process of organizing and categorizing data assets to make them easily discoverable and understandable for data teams. This enables data teams to quickly and easily find the data they need for their analytics projects. In this article: Why Are DataOps Tools Important?

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

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 143

Data Pipeline Scala Metadata Food 143