Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

AWS Big Data

JUNE 21, 2023

Amazon DynamoDB is a fully managed NoSQL service that delivers single-digit millisecond performance at any scale. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse. It’s used by thousands of customers for mission-critical workloads.

Data Warehouse 91

Data Warehouse Data Lake OLAP Cost-Benefit 91

Sisense

JANUARY 6, 2020

Best practice blends the application of advanced data models with the experience, intuition and knowledge of sales management, to deeply understand the sales pipeline. This process helps sales managers manage and invest in their team and anticipate opportunities that lead to exceeding revenue goals.

Sales 91

Sales Forecasting Snapshot Management 91

AWS Big Data

JUNE 27, 2024

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. Document the entire disaster recovery process.

Snapshot 81

Snapshot Data Warehouse Data Processing Strategy 81

AWS Big Data

FEBRUARY 12, 2024

About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. Moreover, no separate effort is required to process historical data versus live streaming data.

Analytics 114

Analytics Data Warehouse Snapshot Cost-Benefit 114

AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. All the connection profiles are configured within the dbt profiles.yml file.

Snapshot 104

Snapshot Data Processing Testing Data Warehouse 104

AWS Big Data

SEPTEMBER 10, 2024

With the launch of Amazon Redshift Serverless and the various provisioned instance deployment options , customers are looking for tools that help them determine the most optimal data warehouse configuration to support their Amazon Redshift workloads. Enable audit logging following the guidance in Amazon Redshift Management Guide.

Testing 108

Testing Snapshot Data Warehouse Metrics 108

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 98

Data Integration Data Lake Statistics Data-driven 98

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 97

Enterprise Data Warehouse Snapshot Cost-Benefit 97

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 117

Data Lake Management Metrics Data Warehouse 117

AWS Big Data

JUNE 10, 2024

The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data. A solution based on Apache Iceberg encompasses complete data management, featuring simple built-in table optimization capabilities within an existing storage solution.

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

AWS Big Data

JANUARY 24, 2024

These formats enable ACID (atomicity, consistency, isolation, durability) transactions, upserts, and deletes, and advanced features such as time travel and snapshots that were previously only available in data warehouses. For more information, refer to Amazon S3: Allows read and write access to objects in an S3 Bucket.

Snapshot 115

Snapshot Data Lake Metadata Optimization 115

Cloudera

AUGUST 8, 2022

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). SDX Integration (Ranger): Manage access to Iceberg tables through Apache Ranger. group by year.

Snapshot 94

Snapshot Data Warehouse Machine Learning Cost-Benefit 94

AWS Big Data

APRIL 3, 2024

Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more. By adding a metadata layer to data lakes, you get a better user experience, simplified management, and improved performance and reliability on very large datasets.

Data Lake 106

Data Lake Snapshot Metadata Data Architecture 106

AWS Big Data

APRIL 10, 2024

Within seconds of transactional data being written into supported AWS databases, zero-ETL seamlessly makes the data available in Amazon Redshift, removing the need to build and maintain complex data pipelines that perform extract, transform, and load (ETL) operations. For this post, set this to 8 RPUs. Choose Next.

Data Warehouse 107

Data Warehouse Analytics Metrics Snapshot 107

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

AWS Big Data

MARCH 10, 2023

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data.

Data Lake 116

Data Lake Sales Data Warehouse Snapshot 116

Cloudera

MAY 13, 2021

Since my last blog, What you need to know to begin your journey to CDP , we received many requests for a tool from Cloudera to analyze the workloads and help upgrade or migrate to Cloudera Data Platform (CDP). The good news is Cloudera has a tried and tested tool, Workload Manager (WM) that meets your needs.

Management 73

Management Data Warehouse Interactive Reporting 73

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 111

Data Warehouse Snapshot Data Processing Internet of Things 111

AWS Big Data

AUGUST 9, 2024

This trend is no exception for Dafiti , an ecommerce company that recognizes the importance of using data to drive strategic decision-making processes. Amazon Redshift is widely used for Dafiti’s data analytics, supporting approximately 100,000 daily queries from over 400 users across three countries. TB of data.

Data Lake 107

Data Lake Analytics Data Warehouse Data-driven 107

AWS Big Data

MARCH 2, 2023

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. Carry out performance tuning.

Data Lake 128

Data Lake Data Processing Metadata Snapshot 128

erwin

JULY 2, 2020

a senior business process management architect at a pharma/biotech company with more than 5,000 employees, erwin Evolve was useful for enterprise architecture reference. As he put it, “We are describing our business process and we are trying to describe our data catalog. Data Modeling with erwin Data Modeler. George H.,

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.

Data Warehouse 101

Data Warehouse Metrics Statistics Optimization 101

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities.

Data Warehouse 100

Data Warehouse KPI Optimization Cost-Benefit 100

IBM Big Data Hub

APRIL 8, 2024

The new Amazon Relational Database Service (Amazon RDS) for Db2 offering allows customers to migrate their existing, self-managed Db2 databases to the cloud and accelerate strategic modernization initiatives. Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS

Snapshot 68

Snapshot Data Warehouse Data Processing Management 68

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. You can get faster insights without spending valuable time managing your data warehouse. Fault tolerance is built in.

Analytics 107

Analytics Data Warehouse Dashboards Testing 107

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. ETL pipelines can be expensive to build and complex to manage. ETL pipelines can be expensive to build and complex to manage.

Data Warehouse 96

Data Warehouse Analytics Metrics Dashboards 96

AWS Big Data

MAY 24, 2023

To learn more about how to create an EMR cluster with Iceberg and use Amazon EMR Studio, refer to Use an Iceberg cluster with Spark and the Amazon EMR Studio Management Guide , respectively. In that case, we have to query the table with the snapshot-id corresponding to the deleted row. parquet") df.sortWithinPartitions("review_date").writeTo("dev.db.amazon_reviews_iceberg").append()

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

AWS Big Data

FEBRUARY 13, 2023

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. 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.

Snapshot 73

Snapshot Data Warehouse Analytics Testing 73

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

Data Lake 107

Data Lake Snapshot Metadata Optimization 107

AWS Big Data

APRIL 27, 2023

Apache Iceberg is an open table format for data lakes that manages large collections of files as tables. It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. However, this requires knowledge of a table’s current snapshots.

Data Lake 81

Data Lake Snapshot Optimization Data Transformation 81

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 105

Data Processing Data Lake Data Warehouse Optimization 105

Domino Data Lab

JANUARY 11, 2021

Data Science works best with a high degree of data granularity when the data offers the closest possible representation of what happened during actual events – as in financial transactions, medical consultations or marketing campaign results. Domino Data Lab is the system-of-record for enterprise data science teams.

Data Science 103

Data Science Recreation/Entertainment Data Warehouse Publishing 103

CIO Business Intelligence

MAY 16, 2022

The advent of distributed workforces, smart devices, and internet-of-things (IoT) applications is creating a deluge of data generated and consumed outside of traditional centralized data warehouses. How edge refines data strategy. From there, other best practices emerge: Heighten the focus on security and governance.

IoT 98

IoT Internet of Things Data Warehouse Machine Learning 98

Cloudera

OCTOBER 11, 2022

The takeaway – businesses need control over all their data in order to achieve AI at scale and digital business transformation. The challenge for AI is how to do data in all its complexity – volume, variety, velocity. And that data is likely in clouds, in data centers and at the edge.

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tags provide metadata about resources at a glance.

Snapshot 91

Snapshot Metadata Measurement Data Warehouse 91

AWS Big Data

OCTOBER 20, 2023

Amazon MSK Connect is a feature of Amazon Managed Streaming for Apache Kafka (Amazon MSK) that offers a fully managed Apache Kafka Connect environment on AWS. You can have multiple internal applications such as databases, data warehouses, or other systems where DNS names are not publicly resolvable.

Data Processing 101

Data Processing Snapshot Data Warehouse Management 101