AWS Big Data

OCTOBER 11, 2023

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.

Management 101

Management Metadata Analytics Dashboards 101

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.

Data Processing 86

Data Processing Management Publishing Testing 86

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 Data Warehouse Analytics Data Processing 52

O'Reilly on Data

JANUARY 17, 2023

” I, thankfully, learned this early in my career, at a time when I could still refer to myself as a software developer. Especially when you consider how Certain Big Cloud Providers treat autoML as an on-ramp to model hosting. Is autoML the bait for long-term model hosting? But that’s a story for another day.)

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

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 Transformation Business Intelligence 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 79

Data Lake Dashboards Metrics Metadata 79

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.

Data Governance 52

Data Governance Measurement Modeling Metrics 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 55

Cost-Benefit Informatics Optimization Management 55

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.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

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 60

Data Lake Metadata Business Analysis Data-driven 60

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 88

Data Processing Data Warehouse Enterprise Visualization 88

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 Sales 52

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