Wayne Yaddow

MARCH 5, 2025

The goal is to examine five major methods of verifying and validating data transformations in data pipelines with an eye toward high-quality data deployment. First, we look at how unit and integration tests uncover transformation errors at an early stage. Applicability by Transformation Type 2.

Testing 52

Testing Data Transformation Statistics Metadata 52

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

erwin

SEPTEMBER 17, 2020

Business terms and data policies should be implemented through standardized and documented business rules. Compliance with these business rules can be tracked through data lineage, incorporating auditability and validation controls across data transformations and pipelines to generate alerts when there are non-compliant data instances.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

CIO Business Intelligence

APRIL 30, 2024

Your AI strategy is only as good as your data strategy,” Tableau CMO Elizabeth Maxon said in a press conference Monday. But to us, it’s more than just having a data strategy; it’s also about building a great foundation of a data culture.”

Analytics 96

Analytics Metrics Visualization Dashboards 96

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

TDAN

AUGUST 15, 2023

Nearly every data leader I talk to is in the midst of a data transformation. As businesses look for ways to increase sales, improve customer experience, and stay ahead of the competition, they are realizing that data is their competitive advantage and the key to achieving their goals. And it’s no surprise, really.

Data Transformation 52

Data Transformation Sales Metadata Data Governance 52

AWS Big Data

APRIL 2, 2024

You can see the decompressed data has metadata information such as logGroup , logStream , and subscriptionFilters , and the actual data is included within the message field under logEvents (the following example shows an example of CloudTrail events in the CloudWatch Logs). You can connect with Ranjit on LinkedIn.

Metadata 98

Metadata Marketing Analytics Data Transformation 98

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 116

Data Lake Management Metrics Data Warehouse 116

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. The first image shows the dashboard without any active filters.

Measurement 93

Measurement Dashboards Data Warehouse Analytics 93

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

Octopai

JANUARY 19, 2021

Octopai is the first BI Intelligence platform to analyze Azure Data Factory in hybrid BI environments, providing automated data lineage and discovery and will continue to announce the early support of more platforms as part of an overall strategy to have one centralized view of the entire BI landscape. “We

Metadata 52

Metadata ROI Machine Learning Data Quality 52

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 110

Visualization Dashboards Data-driven Gap analysis 110

AWS Big Data

APRIL 19, 2023

Conclusion Data-driven organizations are transitioning to a data product way of thinking. Utilizing strategies like data mesh generates value on a large scale. We took this a step further by creating a blueprint to create smart recommendations by linking similar data products using graph technology and ML.

Technology 92

Technology Data-driven Machine Learning Sales 92

Alation

NOVEMBER 22, 2022

Identifying structured and unstructured data. Setting data management policies, like tagging data. A comprehensive data governance strategy ensures that you have quality data so you can leverage insights for data-driven decision making. Why Is Data Governance In The Public Sector Important?

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

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

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

Octopai

JUNE 9, 2024

This challenge is especially critical for executives responsible for data strategy and operations. Here’s how automated data lineage can transform these challenges into opportunities, as illustrated by the journey of a health services company we’ll call “HealthCo.” This is where Octopai excels.

IT 52

IT Data-driven Predictive Analytics Data Strategy 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. Use DeviceId as an additional prefix to write the objects to the bucket. Choose Run.

Analytics 109

Analytics IoT Metadata Internet of Things 109

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

AWS Big Data

JULY 20, 2023

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering.

Data Lake 93

Data Lake Analytics Snapshot Data Quality 93

AWS Big Data

APRIL 25, 2023

Implementing an effective data sharing strategy that satisfies compliance and regulatory requirements is complex. Customers often need to share data between disparate software as a service (SaaS) platforms within their organization or across organizations.

Sales 78

Sales Visualization Software Metadata 78

IBM Big Data Hub

JULY 17, 2023

foundation models to help users discover, augment, and enrich data with natural language. Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access.

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 Reporting 52

Ontotext

FEBRUARY 12, 2024

Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh. Once accomplished, an effective implementation spurs a mindset in which organizations prioritize and value data for decision-making, formulating strategies, and day-to-day operations.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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

AWS Big Data

JANUARY 17, 2024

Another popular transaction data lake use case is incremental query. Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. Melody Yang is a Senior Big Data Solution Architect for Amazon EMR at AWS.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

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 90

Data Lake Dashboards Metrics Metadata 90

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. Given this scenario, it would be a good idea to partition the data by report_type and bucket it by station_id. There are two folders: data and metadata.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

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

MARCH 14, 2024

Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric. It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance.

Analytics 52

Analytics Management Reporting Data Quality 52

Jet Global

MAY 1, 2023

Other money-making strategies include adding users in a per-seat structure or achieving price dominance in the market due. This strategy will ultimately increase sales, and prove a competitive advantage. Data Transformation and Enrichment Data can be enriched for analysis. addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

NOVEMBER 6, 2024

To learn more about how to process Firehose records using Lambda, see Transform source data in Amazon Data Firehose. After executing your Lambda function, Firehose looks for routing information and operations in the metadata fields (in the following format) provided by your Lambda function. b64decode(record['data']).decode('utf-8')

Metadata 108

Metadata Data Lake Management Internet of Things 108

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

AWS Big Data

FEBRUARY 18, 2025

These include managing complex extract, transform, and load (ETL) processes, handling schema validation, providing reliable delivery, and maintaining custom code for data transformations. Firehose delivers streaming data with configurable buffering options that can be optimized for near-zero latency.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76