Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. Query engines (Impala, Hive, Spark) might mitigate some of these problems by using Iceberg’s metadata files.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

Jet Global

FEBRUARY 23, 2024

This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Cloudera

JANUARY 19, 2024

Please refer to the product documentation for more information about specific releases. Cloudera has been testing with GPT running in both Azure and OpenAI, but the following service-model combinations are also supported: Note: Cloudera recommends using the Hue AI assistant with the Azure OpenAI service. or higher on the public cloud.

Data Warehouse 71

Data Warehouse Data Processing Optimization Modeling 71

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Having good data is crucial to creating golden records. MDM Model Objects. MDM Build Objects. The MDM tool should help with this.

Management 52

Management Data Quality Metadata Testing 52

AWS Big Data

NOVEMBER 30, 2023

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

Data Warehouse 80

Data Warehouse Finance Sales Management 80

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In addition, erwin DM users have the ability to: Visualize any data, from anywhere.

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 67

Analytics Data Warehouse Optimization Metrics 67

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

FEBRUARY 24, 2023

An AWS Glue streaming job is connected to Kinesis Data Streams to process the data using the Iceberg connector. Athena uses the AWS Glue Data Catalog to store and retrieve table metadata for the Amazon S3 data in Iceberg format. When the testing is correct, choose Send data. Choose Add database.

Data Lake 80

Data Lake Metadata Testing Data Warehouse 80

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. This post is not intended to provide detailed technical guidance (e.g.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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. Simplified user administration.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Alation

OCTOBER 18, 2022

In the modern data stack, dbt is a key tool to make data ready for analysis. Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Conclusion.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Increasingly, these were simply web servers.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. dbt used in transformation pipelines on data warehouses (Image source: [link].

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Supports the ability to interact with the actual data and perform analysis on it.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

Alation

SEPTEMBER 6, 2022

Ten years ago, there was no modern data catalog. So I was excited to sit down recently with Michael Ting, Senior Software Engineer on the Logical Metadata Infrastructure Team. I worked with biological databases, pulling information and running experiments to synthesize something, test it, and see if you can build a tool.

Data-driven 52

Data-driven Software Testing Metadata 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52