Alation

AUGUST 11, 2022

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Dashboards 101

Dashboards Analytics Metadata Data Warehouse 101

Cloudera

MARCH 14, 2023

The data flow life cycle with Cloudera DataFlow for the Public Cloud (CDF-PC) Data flows in CDF-PC follow a bespoke life cycle that starts with either creating a new draft from scratch or by opening an existing flow definition from the Catalog.

Testing 82

Testing Publishing Metadata Interactive 82

erwin

MARCH 4, 2021

Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, it examined “ The What & Why of Data Governance.”. The What: Data Governance Defined. Data governance has no standard definition. But he cautions “this [notion] is something which is not really likely to happen.”.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog.

Measurement 86

Measurement Dashboards Data Warehouse Analytics 86

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

FEBRUARY 6, 2023

We then discuss a solution to further enhance end-to-end observability by modifying the task definitions that make up the data pipeline. For this post, we focus on task definitions for two services: AWS Glue and Amazon EMR­, however the same method can be applied across different services.

Management 86

Management Interactive Metadata Publishing 86

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

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. Data fabric promotes data discoverability.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

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 102

Analytics IoT Metadata Internet of Things 102

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The Data Catalog now contains references to the machine-readable data. Use the Data Catalog and transform the hospital price transparency data.

Visualization 104

Visualization Dashboards Data-driven Gap analysis 104

Alation

JANUARY 17, 2023

You should look for a data warehouse that is scalable, flexible, and efficient. Popular cloud data warehouses today include Snowflake, Databricks, and BigQuery. If your organization is large, you definitely need to look for robustness. Good data warehouses should be reliable. How Can I Build a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

APRIL 25, 2024

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

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 Let’s refer to this S3 bucket as the raw layer.

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

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 Reporting 52

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

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 110

Data Lake Management Metrics Data Warehouse 110

AWS Big Data

OCTOBER 30, 2024

Leveraging AWS’s managed service was crucial for us to access business insights faster, apply standardized data definitions, and tap into generative AI potential. Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone.

Visualization 110

Visualization Data Lake Testing Data Governance 110

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 96

Data Lake Data Warehouse B2B Data-driven 96

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic. It is now most definitely a need-to-have. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52