AWS Big Data

DECEMBER 20, 2024

Your generated jobs can use a variety of data transformations, including filters, projections, unions, joins, and aggregations, giving you the flexibility to handle complex data processing requirements. The following video provides a full demonstration of the experience with AWS Glue Studio.

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Data Integration Visualization Data Processing Big Data 94

CIO Business Intelligence

APRIL 8, 2025

These issues dont just hinder next-gen analytics and AI; they erode trust, delay transformation and diminish business value. Data quality is no longer a back-office concern. In this article, I am drawing from firsthand experience working with CIOs, CDOs, CTOs and transformation leaders across industries.

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Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud. Our infrastructure was defined as code using the AWS CDK.

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Data Warehouse Data Architecture Machine Learning Data Transformation 52

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. The result is a lower total cost of ownership and trusted data and analytics.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 101

IoT Machine Learning Metadata Data-driven 101

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. Using a native AWS Glue connector increases agility, simplifies data movement, and improves data quality. Choose Save to save your job, and choose Run to run the job.

Analytics 108

Analytics IT Data Lake Visualization 108

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

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Wayne Yaddow

MARCH 12, 2025

The framework ensures that your data transformations comply with rigorous specifications from the moment they are created through every iteration of your pipeline. Great Expectations can enable a wide range of data transformations and conversion operations.

Data Transformation 52

Data Transformation Data Quality Testing Data Warehouse 52

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever.

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Data Warehouse Digital Transformation Data-driven Reporting 142

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. Can it also help write SQL queries? The answer is yes. Choose Notebook instances.

Metadata 89

Metadata Data Lake Modeling Data Warehouse 89

Smart Data Collective

APRIL 29, 2020

What is data management? Data management can be defined in many ways. The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Data analytics and visualisation. Custom applications can also be integrated.

Management 97

Management Data Warehouse Digital Transformation Dashboards 97

datapine

SEPTEMBER 29, 2022

What Is Data Quality Management (DQM)? Data quality management is a set of practices that aim at maintaining a high quality of information. It goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data.

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Data Quality Metrics Data-driven Management 241

AWS Big Data

NOVEMBER 9, 2023

Building a data platform involves various approaches, each with its unique blend of complexities and solutions. In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform.

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Data Warehouse Testing Data Quality Reporting 119

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.

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Data Warehouse KPI Optimization Cost-Benefit 100

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. It uses massively parallel processing (MPP) architecture in Amazon Redshift to read and load large amounts of data in parallel from files or data from supported data sources.

IoT 107

IoT Data Warehouse Cost-Benefit Reporting 107

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. New Services.

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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.

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Data Lake Management Metrics Data Warehouse 117

DataKitchen

JULY 27, 2023

While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure. You can use it for big data analytics and machine learning workloads.

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Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. For example, imaging data can be used to show patients how an aligner will change their appearance over time. “It

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Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

SEPTEMBER 6, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. You can also schedule stored procedures to automate data processing on Amazon Redshift.

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Data Warehouse Insurance Statistics Software 109

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

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AWS Big Data

AUGUST 9, 2024

Dafiti’s data infrastructure relies heavily on ETL and ELT processes, with approximately 2,500 unique processes run daily. Amazon Redshift at Dafiti Amazon Redshift is a fully managed data warehouse service, and was adopted by Dafiti in 2017. We started with 115 dc2.large We removed the DC2 cluster and completed the migration.

Data Lake 107

Data Lake Analytics Data Warehouse Data-driven 107

AWS Big Data

APRIL 30, 2024

This reduces the time and effort you need to learn, build, and run data integration jobs using AWS Glue data integration engines. For example, you can ask Amazon Q Developer to generate a complete extract, transform, and load (ETL) script or code snippet for individual ETL operations.

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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.

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Data Warehouse Analytics Data Lake Data Science 104

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

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Data Warehouse Data Lake Optimization Data-driven 86

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

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. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

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Data Warehouse Data Transformation Machine Learning Data Lake 81

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

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Dashboards Analytics Metadata Data Warehouse 107

AWS Big Data

DECEMBER 4, 2024

In today’s rapidly evolving financial landscape, data is the bedrock of innovation, enhancing customer and employee experiences and securing a competitive edge. Like many large financial institutions, ANZ Institutional Division operated with siloed data practices and centralized data management teams.

Metadata 94

Metadata Data Governance Data Quality Data-driven 94

AWS Big Data

DECEMBER 21, 2023

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.

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Data Lake Data Warehouse Data-driven B2B 104

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

CDW Research Hub

OCTOBER 20, 2020

Snowflake is a modern cloud data platform that boasts instant elasticity, secure data sharing and per-second pricing across multiple clouds. Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering. Have questions? Contact us.

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Dashboards Reporting Data Warehouse Structured Data 72

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 130

Analytics Machine Learning Data mining Software 130

AWS Big Data

JUNE 19, 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. All columns should masked for them.

Data Warehouse 102

Data Warehouse Testing Sales Structured Data 102

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Data is made queryable in real time. Apache Hive.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97