datapine

SEPTEMBER 29, 2022

These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

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. Lineage between dbt sources, models, and metrics.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

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. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 70

Risk Modeling Management Metadata 70

CIO Business Intelligence

AUGUST 3, 2023

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

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 107

Dashboards Analytics Metadata Data Warehouse 107

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 118

Management Metadata Analytics Dashboards 118

CIO Business Intelligence

APRIL 30, 2024

Einstein Copilot for Tableau remains in beta, but Tableau announced two new features for the AI assistant as well: AI-assisted data transformation. This feature can automate a data transformation pipeline with step-by-step suggestions for preparing data for analysis.

Analytics 96

Analytics Metrics Visualization Dashboards 96

CIO Business Intelligence

FEBRUARY 20, 2024

A number of industry leaders are already experimenting with advanced AI use cases, including Denso, a leading mobility supplier that develops advanced technology and components for nearly every vehicle make and model on the road today. Denso uses AI to verify the structuring of unstructured data from across its organisation.

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

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. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

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

AWS Big Data

AUGUST 26, 2024

In this post, I’ll walk you through how to copy data from one Amazon Relational Database Service (Amazon RDS) for PostgreSQL database to another, while scrubbing PII along the way using AWS Glue. Built-in data transformations then scrub columns containing PII using pre-defined masking functions. PII detection and scrubbing.

Visualization 107

Visualization Metadata Data Transformation Testing 107

erwin

MARCH 4, 2021

So companies will be forced to classify their data and to find mechanisms to share it with such platforms.”. GDPR is also proving to be the de facto model for data privacy across the United States.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

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 117

Data Lake Management Metrics Data Warehouse 117

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

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 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 98

Enterprise Data Warehouse Data Lake Optimization 98

Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. Integrating helpful metadata into user workflows gives all people, from data scientists to analysts , the context they need to use data more effectively. How was it used in the past?

Metadata 52

Metadata Cost-Benefit Data Transformation Predictive Modeling 52

AWS Big Data

MARCH 13, 2024

You can modify the Lambda function to fetch additional vehicle information from a separate data store (for example, a DynamoDB table or a Customer Relationship Management system) to enrich the data, before storing the results in an S3 bucket. In this model, the Lambda function is invoked for each incoming event. Choose Run.

Analytics 110

Analytics IoT Metadata Internet of Things 110

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

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Ontotext

NOVEMBER 18, 2021

OntoRefine is a data transformation tool that lets you unite plenty of data formats and get them into your triplestore. One of the core upsides of storing your data in that format is inference. You can think about that as metadata about the data, describing its relationships. Inferring new knowledge.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

JULY 20, 2023

This data is then used by various applications for streaming analytics, business intelligence, and reporting. Amazon SageMaker is used to build, train, and deploy a range of ML models. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

AWS Big Data

AUGUST 1, 2023

For GlueDatabaseName , enter a unique name for the Data Catalog database to hold the Jira data table metadata (the default is jiralake ). This mode will scan all data and disable the change data capture (CDC) features of the stack. The DataBrew job performs data transformation and filtering tasks.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

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 serverless architecture features auto scaling, high availability, and a pay-as-you-go billing model to increase agility and optimize costs.

Visualization 111

Visualization Dashboards Data-driven Gap analysis 111

Octopai

AUGUST 11, 2024

By reverse-engineering, parsing, and converting scripts, Octopai seamlessly connects all data points within and across organizational systems. While open-source tools such as Apache Atlas, Open Metadata, Egeria, Spline, and OpenLineage offer valuable capabilities, they come with their own sets of pros and cons.

Metadata 40

Metadata Visualization Data Quality Data Governance 40

Alation

NOVEMBER 22, 2022

It’s not uncommon for analysts to struggle to access mission-critical data – even if they need it for urgent projects. This is why public agencies are increasingly turning to an active governance model, which promotes data visibility alongside in-workflow guidance to ensure secure, compliant usage. Standardizing data formats.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Octopai

JUNE 9, 2024

They invested heavily in data infrastructure and hired a talented team of data scientists and analysts. The goal was to develop sophisticated data products, such as predictive analytics models to forecast patient needs, patient care optimization tools, and operational efficiency dashboards. This is where Octopai excels.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

Alation

JULY 18, 2022

And the highlight, for us data intelligence folks, was the Databricks’ announcement that Unity Catalog , its unified governance solution for all data assets on its Lakehouse platform, will soon be available on AWS and Azure in the upcoming weeks. A simple model to control access to data via a UI or SQL. and much more!

ROI 52

ROI Metadata Data Lake Digital Transformation 52

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

IBM Big Data Hub

JANUARY 18, 2023

Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. For these workloads, data lake vendors usually recommend extracting data into flat files to be used solely for model training and testing purposes.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

APRIL 19, 2023

A knowledge graph allows us to combine data from different sources to gain a better understanding of a specific problem domain. In Neptune, we combine the Customer product data with an additional data product: Sales Opportunity. With the AWS SDK for Pandas, we combine this data by running a query against the Neptune graph.

Technology 93

Technology Data-driven Machine Learning Sales 93

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 73

Cost-Benefit Data Processing Optimization Data-driven 73