AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Data store – The data store used a custom data model that had been highly optimized to meet low-latency query response requirements.

Data Warehouse 100

Data Warehouse Data Lake Cost-Benefit Structured Data 100

AWS Big Data

OCTOBER 30, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze your data using standard SQL and your existing business intelligence (BI) tools. Data ingestion is the process of getting data to Amazon Redshift.

Data Warehouse 89

Data Warehouse Sales Data Lake Recreation/Entertainment 89

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. Refer to the Amazon Redshift Database Developer Guide for more details.

Analytics 94

Analytics Data Warehouse Big Data Metrics 94

AWS Big Data

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. or a later version) database.

Data Warehouse 94

Data Warehouse Analytics Testing Modeling 94

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g., Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

OCTOBER 23, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that lets you analyze your data at scale. Amazon Redshift Serverless lets you access and analyze data without the usual configurations of a provisioned data warehouse. For more information, refer to Amazon Redshift clusters.

Data Warehouse 89

Data Warehouse Metrics Broadcasting Dashboards 89

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

O'Reilly on Data

OCTOBER 19, 2021

but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern. Along the way, we’ll provide illustrative examples.

IT 364

IT Testing Experimentation Software 364

AWS Big Data

FEBRUARY 20, 2024

Managed AWS Analytics and Database services allow for each component of the solution, from ingestion to analysis, to be optimized for speed, with little management overhead. Transactional data storage In this solution, we use Amazon DynamoDB as our transactional data store.

Visualization 114

Visualization Cost-Benefit Optimization B2B 114

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 91

Data Warehouse Data Lake OLAP Cost-Benefit 91

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Here, data modeling uses dbt on Amazon Redshift.

Snapshot 79

Snapshot Recreation/Entertainment Experimentation Data Lake 79

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 99

Data Warehouse Data Processing Data Lake Management 99

datapine

SEPTEMBER 27, 2022

Amongst the various topics that it covers, ”SQL Performance Explained” offers knowledge into: Correctly applying SQL functions Using indexes correctly How to use LIKE queries efficiently How to optimize join operations Data clustering Database scalability. The all-encompassing nature of this book makes it a must for a data bookshelf.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

AWS Big Data

FEBRUARY 1, 2024

Trade quality and optimization – In order to monitor and optimize trade quality, you need to continually evaluate market characteristics such as volume, direction, market depth, fill rate, and other benchmarks related to the completion of trades. This will be your OLTP data store for transactional data. version cluster.

Data Warehouse 132

Data Warehouse Dashboards Risk Management Risk 132

Smart Data Collective

JUNE 6, 2021

If your company deals with hundreds or thousands of customers, optimal productivity, budgeting and customer satisfaction should be at the top of your priority list. Achieving your company’s target goals can, however, be difficult if you’re unable to access all the relevant and useful data your business has. References.

Big Data 137

Big Data Data Analytics Analytics Cost-Benefit 137

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on.

Metadata 89

Metadata Data Lake Modeling Data Warehouse 89

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. OLTP databases are best at queries where we are doing point scans or short scans of the data, think “return the number of deposits by X user this week.”.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 72

Data Warehouse Cost-Benefit Metadata Management 72

Cloudera

MARCH 24, 2021

Hive users can check how probedecode optimization applies for their MapJoin queries using their standard query explain plans. For more details about the optimization feel free to check the Hive and ORC tickets listed below and watch our ApacheCon talk! References. Probedecode support for MapJoin with row-level filtering.

Data Warehouse 78

Data Warehouse Broadcasting Statistics Cost-Benefit 78

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

MAY 16, 2024

Traditionally, spatial data is represented through a geography or geometry in which features are geolocated on the earth by a long reference string describing the coordinates of every vertex. Indexed data can be quickly joined across different datasets and aggregated at different levels of precision.

Data Warehouse 118

Data Warehouse Visualization Cost-Benefit Data-driven 118

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

Data Warehouse 109

Data Warehouse Machine Learning Data-driven Data Lake 109

AWS Big Data

SEPTEMBER 11, 2024

Source systems Aruba’s source repository includes data from three different operating regions in AMER, EMEA, and APJ, along with one worldwide (WW) data pipeline from varied sources like SAP S/4 HANA, Salesforce, Enterprise Data Warehouse (EDW), Enterprise Analytics Platform (EAP) SharePoint, and more.

Data Architecture 97

Data Architecture Optimization Data Warehouse Metadata 97

AWS Big Data

MAY 20, 2024

Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS.

Data Lake 109

Data Lake Big Data Cost-Benefit Data Warehouse 109

Cloudera

DECEMBER 20, 2022

Effective use of data can have a direct impact on the cash flow of wind and solar generation companies in areas such as real-time decision making. With the right insights, energy production from renewable assets can be optimized and better predict the future of supply and demand. Towards a better customer experience.

Optimization 81

Optimization Data Analytics Analytics Cost-Benefit 81

AWS Big Data

OCTOBER 26, 2023

times better price-performance than other cloud data warehouses on real-world workloads using advanced techniques like concurrency scaling to support hundreds of concurrent users, enhanced string encoding for faster query performance, and Amazon Redshift Serverless performance enhancements. Amazon Redshift delivers up to 4.9

Data Warehouse 110

Data Warehouse Cost-Benefit Dashboards Optimization 110

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. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 100

Data Warehouse KPI Optimization Cost-Benefit 100

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 113

Data Warehouse Analytics Data Lake Machine Learning 113

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 98

Enterprise Data Warehouse Data Lake Optimization 98

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 108

Data Lake Data Warehouse Metadata Data Architecture 108

AWS Big Data

OCTOBER 1, 2024

The external data catalog can be AWS Glue Data Catalog, the data catalog that comes with Amazon Athena, or your own Apache Hive metastore. To get the best performance on data lake queries with Redshift, you can use AWS Glue Data Catalog’s column statistics feature to collect statistics on Data Lake tables.

Data Lake 105

Data Lake Statistics Broadcasting Optimization 105

BizAcuity

SEPTEMBER 22, 2022

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. Not being an agile cloud data warehouse.

Optimization 52

Optimization Data Warehouse Management Modeling 52

AWS Big Data

NOVEMBER 17, 2023

In this post, we look into an optimal and cost-effective way of incorporating dbt within Amazon Redshift. In an optimal environment, we store the credentials in AWS Secrets Manager and retrieve them. For more information, refer SQL models. For more information, refer to Redshift set up. A Redshift cluster.

Snapshot 104

Snapshot Data Processing Testing Data Warehouse 104

AWS Big Data

APRIL 10, 2024

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics. Choose a suitable instance size (the default is db.r5.2xlarge ).

Data Warehouse 107

Data Warehouse Analytics Metrics Snapshot 107

BizAcuity

APRIL 1, 2023

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. The BYNET interconnect supports up to 512 nodes.

Optimization 52

Optimization Data Warehouse Management Modeling 52

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. Refer to Zero-ETL integration costs (Preview) for further details.

Data Warehouse 101

Data Warehouse Metrics Statistics Optimization 101

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 112

Data Lake Cost-Benefit Data-driven Data Warehouse 112