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. These robust capabilities ensure that data within the data lake remains accurate, consistent, and reliable.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

FEBRUARY 6, 2023

Let’s look at some key metrics. After analyzing YARN logs by various metrics, you’re ready to design future EMR architectures. He also understands how to apply technologies to solve big data problems and build a well-designed data architecture. George Zhao is a Senior Data Architect at AWS ProServe.

Dashboards 98

Dashboards Optimization Data Lake Cost-Benefit 98

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Analytics 111

Analytics Dashboards Metadata Data Warehouse 111

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

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 98

Data Lake Dashboards Metrics Metadata 98

Birst BI

FEBRUARY 25, 2020

Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. Data never leaves Snowflake with Birst’s ability to support the reporting and self-service needs of both centralized IT and decentralized LOB teams.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

AWS Big Data

FEBRUARY 6, 2023

The results of the log analyzer reveal Hadoop workload insights with various views and metrics of the Hadoop applications shown in Amazon QuickSight dashboards, which leads to the design of a future EMR cluster. He also understands how to apply technologies to solve big data problems and build a well-designed data architecture.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. When treating a patient, a doctor may wish to study the patient’s vital metrics in comparison to those of their peer group. Visual Analytics Users are given data from which they can uncover new insights.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt.

Data Transformation 55

Data Transformation Cost-Benefit Testing Data Lake 55

AWS Big Data

MAY 12, 2025

Streaming pipelines used Spark Streaming to ingest real-time data from Kafka, writing raw datasets to an Amazon Simple Storage Service (Amazon S3) data lake while simultaneously loading them into BigQuery and Google Cloud Storage to build logical data layers. The following figure is an example of a lineage diagram from DataHub.

Metrics 85

Metrics Cost-Benefit Metadata Data Lake 85

DataKitchen

JANUARY 23, 2023

On the other hand, DataOps Observability refers to understanding the state and behavior of data as it flows through systems. It allows organizations to see how data is being used, where it is coming from, and how it is being transformed. Are problems with data tests? Which report tab is wrong? When did it last run?

Testing 130

Testing Data Governance Data Quality Data-driven 130