AWS Big Data

OCTOBER 31, 2023

citibike-tripdata-destination-ACCOUNT_ID – The bucket used for storing the transformed dataset. When implementing the solution in this post, replace references to airflow-blog-bucket-ACCOUNT_ID and citibike-tripdata-destination-ACCOUNT_ID with the names of your own S3 buckets. Choose Next. Run the DAG Let’s look at how to run the DAGs.

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Data Processing Management Publishing Visualization 111

AWS Big Data

SEPTEMBER 5, 2024

The currently available choices include: The Amazon Redshift COPY command can load data from Amazon Simple Storage Service (Amazon S3), Amazon EMR , Amazon DynamoDB , or remote hosts over SSH. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

AUGUST 8, 2024

Oracle GoldenGate for Oracle Database and Big Data adapters Oracle GoldenGate is a real-time data integration and replication tool used for disaster recovery, data migrations, high availability. You can use temporary credentials; for more details, refer to Using temporary credentials with AWS resources.

Analytics 110

Analytics Big Data Software Data Integration 110

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. Means of ensuring data integrity.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

JULY 26, 2023

You can use your preferred IDE to implement AWS resource definition using the AWS Cloud Development Kit (AWS CDK) or AWS CloudFormation , and also the business logic of AWS Glue job scripts for data integration. To learn more about how to implement your AWS Glue job scripts locally, refer to Develop and test AWS Glue version 3.0

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AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Refer to the instructions in the README file for steps on how to provision and decommission this solution. You’re now ready to query the tables using Athena.

Analytics 121

Analytics IoT Metadata Internet of Things 121

AWS Big Data

AUGUST 26, 2024

Solution overview The following diagram illustrates the solution architecture: The solution uses AWS Glue as an ETL engine to extract data from the source Amazon RDS database. Built-in data transformations then scrub columns containing PII using pre-defined masking functions. PII detection and scrubbing.

Visualization 115

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AWS Big Data

FEBRUARY 26, 2024

Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

Dashboards 83

Dashboards Testing Metrics Optimization 83

AWS Big Data

JULY 25, 2023

For Host , enter the Redshift Serverless endpoint’s host URL. For more information on how to connect to a database, refer to tDBConnection. The output component defines that the data being processed in the job’s workflow will land in Redshift Serverless. For Host , enter the Redshift Serverless endpoint’s host URL.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

AWS Big Data

MARCH 3, 2023

The Delta tables created by the EMR Serverless application are exposed through the AWS Glue Data Catalog and can be queried through Amazon Athena. 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. EMR Serverless version 6.9.0

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

APRIL 25, 2023

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. Let’s take an example. The marketing team created leads based on the event in Adobe Marketo.

Sales 94

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AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. For an example, refer to How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform. Platform architects define a well-architected platform.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Select s3_crawler and choose Run.

Sales 52

Sales Data Warehouse Visualization Testing 52

Alation

JANUARY 17, 2023

A modern data stack relies on cloud computing, whereas a legacy data stack stores data on servers instead of in the cloud. Modern data stacks provide access for more data professionals than a legacy data stack. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 59

Cost-Benefit Informatics Optimization Management 59

Alation

OCTOBER 28, 2021

Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models. What is Data Governance in Healthcare? Data governance in healthcare refers to how data is collected and used by hospitals, pharmaceutical companies, and other healthcare organizations and service providers.

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AWS Big Data

JANUARY 27, 2023

For example, the Flink FileSystem connector has FileSystemTableFactory to read/write data in Hadoop Distributed File System (HDFS) or Amazon Simple Storage Service (Amazon S3), the Flink HBase connector has HBase2DynamicTableFactory to read/write data in HBase, and the Flink Kafka connector has KafkaDynamicTableFactory to read/write data in Kafka.

Data Lake 82

Data Lake Metadata Business Analysis Data-driven 82

Cloudera

NOVEMBER 22, 2021

In addition, more data is becoming available for processing / enrichment of existing and new use cases e.g., recently we have experienced a rapid growth in data collection at the edge and an increase in availability of frameworks for processing that data. As a result, alternative data integration technologies (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

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Metadata Data Quality Data Governance Modeling 52

AWS Big Data

FEBRUARY 25, 2025

Amazon EC2 to host and run a Jenkins build server. Solution walkthrough The solution architecture is shown in the preceding figure and includes: Continuous integration and delivery ( CI/CD) for data processing Data engineers can define the underlying data processing job within a JSON template.

Data Processing 54

Data Processing Machine Learning Data-driven Cost-Benefit 54

AWS Big Data

JANUARY 29, 2025

Additionally, we show you how to submit batch jobs to Amazon EMR using EMR steps for automated, scheduled data processing. This method is ideal for recurring tasks or large-scale data transformations. We accessed the data interactively using EMR Studio notebooks and processed it as a batch job using EMR steps.

Big Data 85

Big Data Data Analytics Analytics Interactive 85

Jet Global

MAY 1, 2023

that gathers data from many sources. Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Ask your vendors for references.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 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.

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Data Warehouse Reporting Data Transformation Visualization 52