Remove Data Processing Remove Data Transformation Remove Metadata Remove Testing
article thumbnail

Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

article thumbnail

The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Athena is used to run geospatial queries on the location data stored in the S3 buckets. You can test this solution yourself using the AWS Samples GitHub repository.

article thumbnail

Cross-account integration between SaaS platforms using Amazon AppFlow

AWS Big Data

On many occasions, they need to apply business logic to the data received from the source SaaS platform before pushing it to the target SaaS platform. AnyCompany’s marketing team hosted an event at the Anaheim Convention Center, CA. However, for quick testing purposes, we demonstrate how to manually run the flow on demand.

Sales 71
article thumbnail

Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

article thumbnail

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

FINRA centralizes all its data in Amazon Simple Storage Service (Amazon S3) with a remote Hive metastore on Amazon Relational Database Service (Amazon RDS) to manage their metadata information. Navigate to the side menu Virtual clusters , then select the HiveDemo cluster , You can see an entry for the SparkSQL test job.

article thumbnail

The Modern Data Stack Explained: What The Future Holds

Alation

As data science is growing in popularity and importance , if your organization uses data science, you’ll need to pay more attention to picking the right tools for this. An example of a data science tool is Dataiku. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.