Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 90

Data Lake Data Warehouse BI SQL 90

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 61

Education Unstructured Data Data Lake Data Warehouse 61

Workfall

JUNE 12, 2023

In this dynamic realm of data engineering, a monumental challenge takes centre stage: efficiently managing the ever-changing tides of real-time data. Data, the lifeblood of organisations, holds the key to unlocking untapped potential and propelling businesses forward. Where Is CDC Used and Who Uses It?

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Knowledge Hut

SEPTEMBER 29, 2023

This growth is creating a strong demand for data experts, especially Azure data engineers. But who are Azure data engineers, and what do they do? Moreover, what benefits can you expect from a career in Azure Data Engineering? Why Should You Get an Azure Data Engineer Certification?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Expiring snapshots is a relatively cheap operation and uses metadata to determine newly unreachable files.

Bytes 57

Bytes Metadata Data Lake SQL 57

Data Engineering Podcast

MARCH 22, 2021

In this episode Raghu Murthy, founder and CEO of Datacoral, does a deep dive on how he and his team manage change data capture pipelines in production. e.g. APIs and third party data sources How can we integrage CDC into metadata/lineage tooling? S3/Parquet or Trino/Drill/etc.) How do you handle observability of CDC flows?

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. Data professionals are not perfectly interchangeable.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

ProjectPro

JANUARY 24, 2023

It is a popular ETL tool well-suited for big data environments and extensively used by data engineers today to build and maintain data pipelines with minimal effort. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS Data Lake Scala ETL Tools 52

Databand.ai

AUGUST 30, 2023

This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management. These practices help ensure that the data being ingested is accurate, complete, and consistent across all sources.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

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

Advancing Analytics: Data Engineering

SEPTEMBER 7, 2021

1 SCD Type 1 in SQL and Python Introduction With the move to cloud based Data Lake platforms there has often been criticism from the more traditional Data Warehousing community. By its definition, a data lake accepts any data, without oversight or governance. From Warehouse to Lakehouse Pt.1

Data Lake 52

Data Lake Datasets Data Warehouse SQL 52

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., …. DataOps Composability.

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

Cloudera

JANUARY 15, 2021

Cloudera Data Warehouse is a highly scalable service that marries the SQL engine technologies of Apache Impala and Apache Hive with cloud-native features to deliver best-in-class price-performance for users running data warehousing workloads in the cloud. The benchmark run by McKnight Consulting Group used the Impala engine.

Data Warehouse 92

Data Warehouse Cloud Consulting SQL 92

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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 91

Data Lake Data Warehouse Cloud Unstructured Data 91

Cloudera

NOVEMBER 12, 2020

Inability to maintain context – This is the worst of them all because every time a data set or workload is re-used, you must recreate its context including security, metadata, and governance. Alternatively, you can also spin up a different compute cluster and access the data by using CDP’s Shared Data Experience.

Cloud 102

Cloud Data Warehouse Banking Data 102

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Data Engineering Weekly

JANUARY 15, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. 2023 predictions from the panel are; Unified metadata becomes kingmaker.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

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. These tables are created as Iceberg tables.

Metadata 88

Metadata Data Warehouse BI AWS 88

Data Engineering Weekly

DECEMBER 4, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. link] Barr Moses: What’s Next for Data Engineering in 2023?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

Snowflake

AUGUST 31, 2023

Catalog Integration: Our newly developed Catalog Integration feature allows you to seamlessly plug Snowflake into other Iceberg catalogs tracking table metadata. In this blog post, we’ll dive into the details of these features and the benefits for customers. In addition to Iceberg External Tables, we introduced Native Iceberg Tables.

Metadata 85

Metadata AWS Data Lake Datasets 85

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

Cloudera

DECEMBER 15, 2022

Compute engines in these CDP data services can access and process data sets in the Iceberg tables concurrently, with shared security and governance provided by our unique Cloudera Shared Data Experience ( SDX ). Only metadata will be regenerated. Data quality using table rollback. Metadata management .

Cloud 76

Cloud Metadata Google Cloud Data Warehouse 76

Big Data Tools

SEPTEMBER 6, 2021

But data engineering never stops. News A lot of engineering is about learning new things and keeping a finger on the pulse of new technologies. News A lot of engineering is about learning new things and keeping a finger on the pulse of new technologies. Here’s what’s happening in data engineering right now.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

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. Towards Data Science ). Forrester ).

Data Architecture 76

Data Architecture Architecture Data Lake NoSQL 76

Cloudera

MARCH 23, 2022

Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. By being a truly open table format, Apache Iceberg fits well within the vision of the Cloudera Data Platform (CDP). What is Apache Iceberg? 2: Open formats.

Metadata 88

Metadata Data Architecture BI Machine Learning 88

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

ProjectPro

JULY 23, 2021

AWS (Amazon Web Services) is the world’s leading and widely used cloud platform, with over 200 fully featured services available from data centers worldwide. This blog presents some of the most unique and innovative AWS projects from beginner to advanced levels. Serverless Image Recognition Engine 13.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

DataKitchen

OCTOBER 11, 2021

First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. She applies some calculations and forwards the file to a data engineer who loads the data into a database and runs a Talend job that performs ETL to dimensionalize the data and produce a Data Mart.

Engineering 60

Engineering BI Business Analyst Metadata 60

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Business Intelligence Metadata Data Warehouse 84

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. This library is integrated by execution engines such as Impala, Hive and Spark.

Data Warehouse 79

Data Warehouse Metadata Java Data 79

Big Data Tools

SEPTEMBER 6, 2021

But data engineering never stops. News A lot of engineering is about learning new things and keeping a finger on the pulse of new technologies. News A lot of engineering is about learning new things and keeping a finger on the pulse of new technologies. Here’s what’s happening in data engineering right now.

Data Engineering 40

Data Engineering Data Engineer Engineering Big Data Tools 40

Databand.ai

JULY 28, 2022

All of these are essential at a time when data plays such an integral role in business outcomes and decision-making. In this very simplified example, we can see an ELT: Some pipeline tasks, probably running by Airflow , are scraping external data sources and collecting data from there.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 52