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. let the user document, test, and share the model. let the user document, test, and share the model. or higher 5.x

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

AWS Big Data

JULY 27, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Amazon Redshift RA3 with managed storage is the newest instance type for Provisioned clusters.

Testing 65

Testing Data Warehouse Data Processing Snapshot 65

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 76

Data Warehouse Data-driven Snapshot Testing 76

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 94

Data Warehouse Snapshot Testing Management 94

Cloudera

FEBRUARY 8, 2024

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. Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables.

Snapshot 91

Snapshot Metadata Cost-Benefit Data Warehouse 91

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. You can get faster insights without spending valuable time managing your data warehouse.

Analytics 96

Analytics Data Warehouse Testing Dashboards 96

IBM Big Data Hub

APRIL 8, 2024

Can Amazon RDS for Db2 be used for running data warehousing workloads? Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS At what level are snapshot-based backups taken?  Also, you can take manual snapshots as needed. 

Snapshot 68

Snapshot Data Warehouse Data Processing Management 68

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 67

Snapshot Data Warehouse Testing Analytics 67

AWS Big Data

MARCH 18, 2024

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

Data Warehouse 80

Data Warehouse Visualization Snapshot Data-driven 80

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. We begin with a Data lake reference architecture followed by an overview of operational data processing framework. This concludes the demo.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

AWS Big Data

MAY 24, 2023

Some of the important non-functional use cases for an S3 data lake that organizations are focusing on include storage cost optimizations, capabilities for disaster recovery and business continuity, cross-account and multi-Region access to the data lake, and handling increased Amazon S3 request rates. write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 84

Data Lake Snapshot Metadata Optimization 84

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool. Ashish Agrawal is a Sr.

Metrics 80

Metrics Data Warehouse Dashboards Snapshot 80

AWS Big Data

OCTOBER 20, 2023

You can have multiple internal applications such as databases, data warehouses, or other systems where DNS names are not publicly resolvable. You can now use MSK Connect to privately connect with databases, data warehouses, and other resources in your VPC to comply with your security needs.

Data Processing 86

Data Processing Snapshot Data Warehouse Management 86

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Test SCD Type 2 implementation With the infrastructure in place, you’re ready to test out the overall solution design and query historical records from the employee dataset.

Data Lake 70

Data Lake Testing Snapshot Sales 70

AWS Big Data

APRIL 27, 2023

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance.

Data Lake 73

Data Lake Snapshot Optimization Data Transformation 73

AWS Big Data

FEBRUARY 1, 2023

We chose DynamoDB as our metadata store, which provides the latest details to the consumers to query the data effectively. Every dataset in our system is uniquely identified by snapshot ID, which we can search from our metadata store. Clients access this data store with an API’s.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. Clustering data for better data colocation using z-ordering.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

AUGUST 16, 2023

On the Code tab, choose Test , then Configure test event. Configure a test event with the default hello-world template event JSON. Configure a test event with the default hello-world template event JSON. Provide an event name without any changes to the template and save the test event.

Data Lake 71

Data Lake Metadata Testing Snapshot 71

AWS Big Data

MAY 30, 2023

Under Instance configuration , for High Availability , choose Dev or test workload (Single-AZ). Before joining AWS, Manish’s experience includes helping customers implement data warehouse, BI, data integration, and data lake projects. Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team.

Data Lake 80

Data Lake Data Analytics Analytics Data Processing 80

AWS Big Data

JUNE 10, 2024

Apache Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for processing engines such as Apache Spark, Trino, Apache Flink, Presto, Apache Hive, and Impala to safely work with the same tables at the same time. SparkActions.get().expireSnapshots(iceTable).expireOlderThan(TimeUnit.DAYS.toMillis(7)).execute()

Data Lake 108

Data Lake Metadata Snapshot Analytics 108

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

IBM Big Data Hub

SEPTEMBER 25, 2023

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. There may be inaccuracy because of sampling, but it allows users to discover new viewpoints within the data.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87