Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners? What are the transformation rules? Data Governance.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

AWS Big Data

OCTOBER 30, 2024

Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone. For this use case, create a data source and import the technical metadata of four data assets— customers , order_items , orders , products , reviews , and shipments —from AWS Glue Data Catalog.

Visualization 119

Visualization Data Lake Testing Data Governance 119

Wayne Yaddow

FEBRUARY 18, 2025

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Data Transformation in the Modern Data Stack. How did the data transform exactly?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

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. This saves time over manually defining schemas.

Visualization 116

Visualization Metadata Data Transformation Testing 116

Alation

OCTOBER 26, 2021

Building a Data Culture Within a Finance Department. Our finance users tell us that their first exposure to the Alation Data Catalog often comes soon after the launch of organization-wide data transformation efforts. After all, finance is one of the greatest consumers of data within a business.

Finance 52

Finance Data Transformation Enterprise Metrics 52

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. Increase trust in AI outcomes.

Risk 70

Risk Modeling Management Metadata 70

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

AWS Big Data

MARCH 9, 2023

This can be done using the initiatePrint action: embeddedDashboard.initiatePrint(); The following code sample shows a loading animation, SDK code status, and dashboard interaction monitoring, along with initiating dashboard print from the application: Embedding demo $(document).ready(function()

Slice and Dice 98

Slice and Dice Dashboards Analytics Interactive 98

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

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. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 122

Analytics IoT Metadata Internet of Things 122

Cloudera

DECEMBER 9, 2022

Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. With NiFi you can configure your source processor and run it independently of any other processors to retrieve data. Enabling self-service for developers.

Testing 100

Testing Cost-Benefit Interactive Visualization 100

AWS Big Data

APRIL 19, 2023

This allows for a new way of thinking and new organizational elements—namely, a modern data community. However, today’s data mesh platform contains largely independent data products. Even with well-documented data products, knowing how to connect or join data products is a time-consuming job.

Technology 105

Technology Data-driven Machine Learning Sales 105

Cloudera

MARCH 14, 2023

A critical feature for every developer however is to get instantaneous feedback like configuration validations or performance metrics, as well as previewing data transformations for each step of their data flow. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Testing 84

Testing Publishing Metadata Interactive 84

Octopai

JUNE 9, 2024

Accurate data lineage rebuilt trust among decision-makers. HealthCo’s leadership could confidently rely on data-driven insights, knowing the data’s journey was well-documented and reliable. This trust empowered them to deploy new data products without fear of inaccuracies, driving innovation and operational improvements.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

Alation

NOVEMBER 22, 2022

A well-governed data landscape enables data users in the public sector to better understand the driving forces and needs to support public policy – and measure impact once a change is made. Efficient Access To Data. Citizens, companies, and government employees need access to data and documents.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Visualization 52

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 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.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MAY 1, 2023

Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more. addresses). Read carefully.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MARCH 14, 2024

This straightforward and user-friendly access to source data makes it easier for your business users to examine and extract insights from your core data systems. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric.

Analytics 52

Analytics Management Reporting Data Quality 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. The Source stage maintains raw data in its original form.

Data Transformation 57

Data Transformation Cost-Benefit Testing Data Lake 57

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.

Metrics 89

Metrics Cost-Benefit Metadata Data Lake 89

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130