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. The following Diagram 2 shows this workflow.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 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

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. When did you begin a technology partnership with Snowflake and why?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

SEPTEMBER 5, 2024

Federated queries allow querying data across Amazon RDS for MySQL and PostgreSQL data sources without the need for extract, transform, and load (ETL) pipelines. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 108

IoT Data Warehouse Cost-Benefit Reporting 108

AWS Big Data

JANUARY 15, 2025

AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster. The data in the central data warehouse in Amazon Redshift is then processed for analytical needs and the metadata is shared to the consumers through Amazon DataZone.

IoT 102

IoT Machine Learning Metadata Data-driven 102

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. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 97

Management Data Warehouse Digital Transformation Dashboards 97

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. Satesh Sonti is a Sr.

Data Warehouse 110

Data Warehouse Insurance Statistics Software 110

AWS Big Data

NOVEMBER 9, 2023

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. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 120

Data Warehouse Testing Data Quality Reporting 120

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 105

Data Warehouse Analytics Data Lake Data Science 105

AWS Big Data

AUGUST 13, 2024

You will load the event data from the SFTP site, join it to the venue data stored on Amazon S3, apply transformations, and store the data in Amazon S3. The event and venue files are from the TICKIT dataset. For Node parents , select Rename Venue data and Rename Event data.

Data Processing 100

Data Processing Visualization Data Lake Data Processing 100

CIO Business Intelligence

APRIL 8, 2025

As data volumes and use cases scale especially with AI and real-time analytics trust must be an architectural principle, not an afterthought. Comparison of modern data architectures : Architecture Definition Strengths Weaknesses Best used when Data warehouse Centralized, structured and curated data repository.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. Education and enablement – Conduct learning interventions to upskill teams on understanding and using the data as a product approach.

Metadata 95

Metadata Data Governance Data Quality Data-driven 95

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. Cloudera Data Warehouse). Apache Hive.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

AWS Big Data

SEPTEMBER 19, 2023

Problem statement In order to keep up with the rapid movement of fraudsters, our decision platform must continuously monitor user events and respond in real-time. However, our legacy data warehouse-based solution was not equipped for this challenge. Amazon DynamoDB is another data source for our Streaming 2.0

Analytics 93

Analytics Risk Big Data Machine Learning 93

CIO Business Intelligence

DECEMBER 22, 2022

DataOps in practice To make the most of DataOps, enterprises must evolve their data management strategies to deal with data at scale and in response to real-world events as they happen, according to Dunning and Friedman. They also note DataOps fits well with microservices architectures.

Analytics 130

Analytics Machine Learning Data mining Software 130

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 105

Data Lake Data Warehouse Data-driven B2B 105

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 94

Cost-Benefit IoT Data Warehouse Manufacturing 94

AWS Big Data

OCTOBER 5, 2023

Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery. Architecture Let’s review the architecture to transfer data from Google BigQuery to Amazon S3 using Amazon AppFlow.

Data Warehouse 101

Data Warehouse Machine Learning Data Integration Data-driven 101

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 83

Data Lake Snapshot Optimization Data Transformation 83

AWS Big Data

AUGUST 1, 2023

You can do this by updating the CloudFormation stack with a flag that includes the CDC and data transformation steps. This will enable both the CDC steps and the data transformation steps for the Jira data. The DataBrew job performs data transformation and filtering tasks. Choose Update.

Data Lake 93

Data Lake Data Transformation Data-driven Cost-Benefit 93

IBM Big Data Hub

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 78

Reporting Metrics Optimization Data Lake 78

Sisense

MAY 11, 2021

When it comes to data modeling, function determines form. Let’s say you want to subject a dataset to some form of anomaly detection; your model might take the form of a singular event stream that can be read by an anomaly detection service. This design philosophy was adapted from our friends at Fishtown Analytics.).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

MARCH 15, 2023

Performance and scalability of both the data pipeline and API endpoint were key success criteria. The data pipeline needed to have sufficient performance to allow for fast turnaround in the event that data issues needed to be corrected.

Cost-Benefit 74

Cost-Benefit Data Processing Optimization Data-driven 74

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Dashboards 52

Dashboards Metrics Sales Reporting 52

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

JANUARY 17, 2024

His expertise lies in assisting customers with migrating intricate enterprise systems and databases to AWS, constructing enterprise data warehousing and data lake platforms. He is deeply passionate about applying ML/DL and big data techniques to solve real-world problems. Aditya Shah is a Software Development Engineer at AWS.

Data Lake 108

Data Lake Snapshot Big Data Data-driven 108

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 86

Data Analytics Analytics IoT Data Lake 86

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

NOVEMBER 7, 2023

The answer depends on your specific business needs and the nature of the data you are working with. Both methods have advantages and disadvantages: Replication involves periodically copying data from a source system to a data warehouse or reporting database. Empower your team to add new data sources on the fly.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

MAY 6, 2024

These tools excel at data integration, consolidating information from various financial systems (ERP, CRM, legacy) into a central hub. This eliminates data fragmentation, a major obstacle for AI. Additionally, they provide robust data transformation capabilities.

Finance 52

Finance Reporting Data Transformation Data-driven 52

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system. Privacy Policy.

Finance 52

Finance Reporting Data Integration Data Warehouse 52