AWS Big Data

NOVEMBER 22, 2024

Testing these upgrades involves running the application and addressing issues as they arise. Each test run may reveal new problems, resulting in multiple iterations of changes. They then need to modify their Spark scripts and configurations, updating features, connectors, and library dependencies as needed. Python 3.7) to Spark 3.3.0

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

erwin

SEPTEMBER 26, 2019

The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell.

Data Warehouse 108

Data Warehouse Cost-Benefit Data Integration Consulting 108

CIO Business Intelligence

OCTOBER 7, 2022

BI analysts, with an average salary of $71,493 according to PayScale , provide application analysis and data modeling design for centralized data warehouses and extract data from databases and data warehouses for reporting, among other tasks. BI encompasses numerous roles.

Business Intelligence 145

Business Intelligence Data Warehouse Visualization Dashboards 145

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

datapine

FEBRUARY 10, 2021

Your Chance: Want to test a social media dashboard software for free? A social media dashboard is an invaluable management tool that is used by professionals, managers, and companies to gather, optimize, and visualize important metrics and data from social channels such as Facebook, Twitter, LinkedIn, Instagram, YouTube, etc.

Dashboards 193

Dashboards Scorecard KPI Metrics 193

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 130

Data Warehouse Analytics Data Lake Machine Learning 130

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

AWS Big Data

JULY 2, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. For Name , enter a name (for example, dms-test ).

Data Warehouse 118

Data Warehouse Sales Testing Big Data 118

AWS Big Data

JANUARY 30, 2025

Our approach The migration initiative consisted of two main parts: building the new architecture and migrating data pipelines from the existing tool to the new architecture. Often, we would work on both in parallel, testing one component of the architecture while developing another at the same time.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

erwin

FEBRUARY 7, 2019

For example, manually managing data mappings for the enterprise data warehouse via MS Excel spreadsheets had become cumbersome and unsustainable for one BSFI company. It recognized the need for a solution to standardize the pre-ETL data mapping process to make data integration more efficient and cost-effective.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

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 122

Data Lake Cost-Benefit Data-driven Data Warehouse 122

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. connection testing, metadata retrieval, and data preview.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

Cloudera

MARCH 11, 2021

Data flows are an integral part of every modern enterprise. At Cloudera, we’re helping our customers implement data flows on-premises and in the public cloud using Apache NiFi , a core component of Cloudera DataFlow.

Data Integration 119

Data Integration Data Warehouse Testing Enterprise 119

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

datapine

NOVEMBER 11, 2021

This data is usually saved in different databases, external applications, or in an indefinite number of Excel sheets which makes it almost impossible to combine different data sets and update every source promptly. BI tools aim to make data integration a simple task by providing the following features: a) Data Connectors.

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. We observed that our TPC-DS tests on Amazon S3 had a total job runtime on AWS Glue 4.0

Testing 105

Testing Data Lake Cost-Benefit Data Integration 105

AWS Big Data

JUNE 10, 2024

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using Athena queries in the consumer account.

Data Lake 116

Data Lake Metadata Data Warehouse Data Processing 116

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 93

Snapshot Data Warehouse Data Processing Strategy 93

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 119

Data Analytics Analytics Data Warehouse Data Lake 119

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. SQL Server Integration Services (SSIS): You know it; your father used it.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

FEBRUARY 13, 2024

Monitoring data pipelines in real time is critical for catching issues early and minimizing disruptions. AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. Choose Add new data source.

Metrics 126

Metrics Dashboards Visualization Key Performance Indicator 126

AWS Big Data

JUNE 10, 2024

Many of the tests to check performance and volumes of data scanned have used Athena because it provides a simple to use, fully serverless, cost effective, interface without the need to setup infrastructure. 12xl) cluster The test included four types of queries that represent different production workloads that Cloudinary is running.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111

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 111

Data Architecture Optimization Data Warehouse Metadata 111

AWS Big Data

FEBRUARY 8, 2023

Vyaire developed a custom data integration platform, iDataHub, powered by AWS services such as AWS Glue , AWS Lambda , and Amazon API Gateway. In this post, we share how we extracted data from SAP ERP using AWS Glue and the SAP SDK. Test the connection with SAP using the wheel file. Create the PyRFC wheel file.

Testing 105

Testing Data Integration Data Lake Enterprise 105

AWS Big Data

JUNE 28, 2023

Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.

Analytics 96

Analytics Data Warehouse Data Lake Data-driven 96

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 116

Data Warehouse Snapshot Data Processing Internet of Things 116

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

CIO Business Intelligence

JUNE 7, 2022

You don’t understand how long you should test your feature and what exactly you should measure,” he says. Data scientists may build the ML models, but its ML engineers who implement them. An ML engineer is also involved with validation of models, A/B testing, and monitoring in production.”. Data steward. ML engineer.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

erwin

FEBRUARY 19, 2021

Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Occam's Razor

OCTOBER 19, 2010

If after rigorous analysis you have determined that you have evolved to a stage that you need a data warehouse then you are out of luck with Yahoo! If you can show ROI on a DW it would be a good use of your money to go with Omniture Discover, WebTrends Data Mart, Coremetrics Explore. Five Reasons And Awesome Testing Ideas.

Analytics 136

Analytics Testing Measurement Optimization 136

Cloudera

JUNE 2, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.). bridging protocols, data formats, routing, filtering, error handling, retries).

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

AWS Big Data

OCTOBER 20, 2023

Regarding the Azure Data Lake Storage Gen2 Connector, we highlight any major differences in this post. AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. Learn more in README.

Data Lake 111

Data Lake Big Data Consulting Data Warehouse 111

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

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 104

Data Warehouse Data-driven Snapshot Testing 104