AWS Big Data

JANUARY 30, 2025

Pattern 1: Data transformation, load, and unload Several of our data pipelines included significant data transformation steps, which were primarily performed through SQL statements executed by Amazon Redshift. The following Diagram 2 shows this workflow.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

Snapshot 118

Snapshot Data-driven Optimization Management 118

AWS Big Data

SEPTEMBER 5, 2024

With auto-copy, automation enhances the COPY command by adding jobs for automatic ingestion of data. 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 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. After you complete the checklist, you’ll have a better understanding of how to design the future architecture. For the compute-heavy workloads such as MapReduce or Hive-on-MR jobs, use CPU-optimized instances.

Dashboards 93

Dashboards Optimization Data Lake Cost-Benefit 93

CIO Business Intelligence

AUGUST 3, 2023

It also used device data to develop Lenovo Device Intelligence, which uses AI-driven predictive analytics to help customers understand and proactively prevent and solve potential IT issues. Lenovo Device Intelligence can also help to optimize IT support costs, reduce employee downtime, and improve the user experience, the company says.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. This ensures that the data is suitable for training purposes. The following diagram illustrates the solution architecture.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 107

Enterprise Data Warehouse Data Lake Optimization 107

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. Shashank Tewari is a Senior Technical Account Manager at AWS.

Data Warehouse 110

Data Warehouse Analytics Data Lake Data Science 110

Birst BI

FEBRUARY 25, 2020

Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. The Snowflake/Birst combination creates the optimal balance between IT control and end-user freedom, eliminating analytic silos once and for all.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

AWS Big Data

FEBRUARY 6, 2023

When migrating Hadoop workloads to Amazon EMR , it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. For more information, see the GitHub repo.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

Ontotext

MARCH 27, 2024

It accelerates data projects with data quality and lineage and contextualizes through ontologies , taxonomies, and vocabularies, making integrations easier. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards. Increasingly, organizations are using both.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

IBM Big Data Hub

JULY 5, 2023

The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale. Data may be stored in its raw original form or optimized into a different format suitable for consumption by specialized engines.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Monjumi Sarma is a Data Lab Solutions Architect at AWS.

Data Lake 97

Data Lake Dashboards Metrics Metadata 97

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

IBM Big Data Hub

JANUARY 18, 2023

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

APRIL 5, 2023

The company also used the opportunity to reimagine its data pipeline and architecture. A key architectural decision that Showpad took during this time was to create a portable data layer by decoupling the data transformation from visualization, ML, or ad hoc querying tools and centralizing its business logic.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

AUGUST 7, 2024

The company started its New Analytics Era initiative by migrating its data from outdated SQL servers to a modern AWS data lake. It then built a cutting-edge cloud-based analytics platform, designed with an innovative data architecture. It also crafted multiple machine learning and AI models to tackle business challenges.

IT 119

IT Insurance Cost-Benefit Testing 119

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

Jet Global

MAY 1, 2023

Reports In formats that are both static and interactive, these showcase tabular views of data. Strategic Objective Provide an optimal user experience regardless of where and how users prefer to access information. Data Environment First off, the solutions you consider should be compatible with your current data architecture.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

APRIL 29, 2025

At the BMW Group, our Cloud Efficiency Analytics (CLEA) team has developed a FinOps solution to optimize costs across over 10,000 cloud accounts. While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally.

52

52

AWS Big Data

DECEMBER 2, 2024

AWS Glue establishes a secure connection to HubSpot using OAuth for authorization and TLS for data encryption in transit. AWS Glue also supports the ability to apply complex data transformations, enabling efficient data integration and preparation to meet your needs.

Data Lake 99

Data Lake Testing Data Integration Metadata 99

AWS Big Data

APRIL 28, 2025

Technical recap The AWS Glue Data Catalog served as the primary source of truth for schema and table updates, with Amazon EventBridge capturing Data Catalog events to trigger synchronization workflows. AWS Lambda parsed event metadata and managed schema synchronization, while Apache Kafka buffered events for real-time processing.

Data Lake 52

Data Lake Metadata Cost-Benefit Snapshot 52

AWS Big Data

NOVEMBER 14, 2024

We use the built-in features of Data Firehose, including AWS Lambda for necessary data transformation and Amazon Simple Notification Service (Amazon SNS) for near real-time alerts. To maintain up-to-date data, an AWS Glue crawler reads and updates the AWS Glue Data Catalog from transformed Parquet files.

Data Lake 102

Data Lake Metadata Testing Data-driven 102